5 Best Ways to Check if a String is a Suffix of Another in Python

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πŸ’‘ Problem Formulation: In Python programming, checking if one string is the suffix of another means determining whether the second string ends with the sequence of characters that forms the first string. For instance, if ‘world’ is our suffix string and ‘hello world’ is the other string, we want our check to return True because ‘hello world’ ends with ‘world’.

Method 1: Using the str.endswith Method

The str.endswith() method is a built-in Python function that checks if a string ends with a specified suffix. It returns True if the string ends with the specified value, otherwise False. This method is straightforward and efficient for checking suffixes.

Here’s an example:

base_string = 'hello world'
suffix = 'world'
result = base_string.endswith(suffix)
print(result)

Output:

True

This snippet demonstrates the use of str.endswith() by taking a base string and checking if the specified suffix is indeed its ending. The method then returns a boolean value.

Method 2: Using String Slicing

String slicing in Python can be used to extract a part of a string using indexing. To check for a suffix, you can slice the string from the end by the length of the suffix and compare the result with the suffix string.

Here’s an example:

base_string = 'Python is fun'
suffix = 'fun'
result = base_string[-len(suffix):] == suffix
print(result)

Output:

True

The code snippet slices the last part of the base string by using a negative index and the length of the suffix, and then compares it to the suffix string. It returns True if they match, indicating that the suffix is correct.

Method 3: Using Regular Expressions

Regular expressions (regex) provide a powerful way to search and match patterns in strings. To check for a suffix, you can use the re module with a pattern that signifies the end of a string, designated as '$'.

Here’s an example:

import re
base_string = 'Learning is lifelong'
suffix = 'lifelong'
result = re.search(suffix + '$', base_string) is not None
print(result)

Output:

True

By using the re.search() function from the re module, a regular expression is constructed by appending the '$' sign (which signifies the end of a string) to the suffix. The search will return a match object if the suffix is found at the end, otherwise None.

Method 4: Looping Over the Strings

Looping over the strings to compare each character can be used to verify if one string is the suffix of another. This approach is less common due to its verbosity but can be insightful for understanding string comparison at a low level.

Here’s an example:

base_string = 'A stitch in time saves nine'
suffix = 'nine'
result = all(base_string[i] == suffix[j] for i, j in zip(range(len(base_string) - len(suffix), len(base_string)), range(len(suffix))))
print(result)

Output:

True

The code compares each character of the purported suffix with the corresponding character at the end of the base string using a loop with all() and zip() to ensure that every character matches. It returns True if all comparisons are equal.

Bonus One-Liner Method 5: The in Keyword

While not specifically tailored to check for suffixes, the in keyword can be used as a quick one-liner to see if the suffix string exists at the end of the base string when combined with slicing.

Here’s an example:

base_string = 'The quick brown fox'
suffix = 'fox'
result = suffix in base_string and base_string[-len(suffix):] == suffix
print(result)

Output:

True

This snippet uses the in operator to check the presence of the suffix in the base string, combined with slicing to ensure that the match is at the end of the string. This method returns a boolean indicating if the suffix is correct.

Summary/Discussion

  • Method 1: str.endswith Method. This is the most straightforward and idiomatic way. It is both readable and reliable. However, it may not be as versatile if additional context matching is required.
  • Method 2: String Slicing. A simple and efficient method without the need for additional functions or modules. It might be less clear to newcomers or less explicit in terms of intent compared to str.endswith().
  • Method 3: Regular Expressions. Powerful and versatile for complex pattern matching. It can be overkill for simple suffix checks and less performant compared to other methods.
  • Method 4: Looping Over Strings. Offers a clear understanding of how string comparison works internally. However, it is verbose and less efficient, especially with large strings.
  • Method 5: The in Keyword. Quick and concise one-liner, but may be misleading as it checks for the presence of a substring anywhere within the string, not strictly as a suffix. It should be used with care and proper slicing.