5 Best Ways to Python Program to Replace All Words Except the Given Word

💡 Problem Formulation: In Python programming, one might encounter the need to replace every word in a string with a placeholder or another word, except for a specific word that must remain unaltered. For example, given the input string “sunrise is beautiful except when it’s cloudy” and the word “beautiful”, the desired output would involve replacing all words except “beautiful” with a placeholder like “X” resulting in “X is beautiful X when it’s X”.

Method 1: Using String Split and Join

String split and join methods can be effectively used to replace all words except a given word. We split the string into words, iterate over these words, replace those that don’t match our target word, and join them back together into a single string.

Here’s an example:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = ' '.join([word if word == exception_word else placeholder for word in text.split()])

print(result)

Output:

X X X fox X X X X X

This code snippet uses list comprehension in combination with the split() and join() string methods. It efficiently iterates over each word, comparing it with the exception word, and either keeps it or replaces it with the placeholder, finally reassembling the string with the join() method.

Method 2: Using Regex Substitution

Regular expressions offer a powerful way to perform string manipulations based on patterns. We can use regex to replace all occurrences of words that are not the specified exception word.

Here’s an example:

import re

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
result = re.sub(r'\b(?<!\w)'+ re.escape(exception_word) + r'(?!\w)|\w+', placeholder, text)

print(result)

Output:

X X X fox X X X X X

This code snippet leverages the re.sub() function, a part of Python’s regex module, to replace all words except the exception word. We escape the exception word to ensure it’s treated as a literal string in the regex pattern. The substitution happens for all words that are not immediately preceded or followed by a word character.

Method 3: Using String Replacement and Word Boundaries

This method employs a combination of string replacement and detecting word boundaries by iterating over the string. This method is good when regex isn’t preferred or available.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
placeholder = "X"
words = text.split()
result = [word if word == exception_word else placeholder for word in words]
joined_result = ' '.join(result)

print(joined_result)

Output:

X X X fox X X X X X

The code uses split() to create a list of words, then processes each word with a list comprehension to keep the exception word while substituting all others with the placeholder. Finally, it uses join() to reconstruct the modified string.

Method 4: Using a Function and String Methods

Creating a specific function to carry out the operation allows for reusability and improved readability. We define a function that employs string methods to replace words conditionally.

Here’s an example:

def replace_except(text, exception_word, placeholder="X"):
    return ' '.join([word if word == exception_word else placeholder for word in text.split()])

text = "The quick brown fox jumps over the lazy dog"
print(replace_except(text, "fox"))

Output:

X X X fox X X X X X

This code snippet abstracts the logic into a separate function replace_except(), which follows the same strategy as Method 1 but with improved code organization and reusability.

Bonus One-Liner Method 5: Using Map and Lambda

Python’s functional programming capabilities like map() and lambda can provide succinct one-liners for this problem.

Here’s an example:

text = "The quick brown fox jumps over the lazy dog"
exception_word = "fox"
result = ' '.join(map(lambda word: word if word == exception_word else "X", text.split()))

print(result)

Output:

X X X fox X X X X X

This code snippet uses a lambda function within map() to apply a conditional replacement to each word, achieving what list comprehension does but in a more functional manner.

Summary/Discussion

• Method 1: Using String Split and Join. Pros: Simple and readable. Cons: Not the most efficient for very large texts.
• Method 2: Using Regex Substitution. Pros: Very fast and powerful for pattern matching. Cons: Regex can be less readable for those unfamiliar with it.
• Method 3: Using String Replacement and Word Boundaries. Pros: Straightforward iterative approach. Cons: Essentially similar to Method 1, with no significant advantages.
• Method 4: Using a Function and String Methods. Pros: Reusable and clean. Cons: Might be an overkill for one-off tasks.
• Bonus One-Liner Method 5: Using Map and Lambda. Pros: Succinct and elegant functional programming approach. Cons: May be less readable for those not comfortable with lambda functions and map.