Calculating Word Scores in Python: A Guide to 5 Effective Methods

💡 Problem Formulation: You’ve got a list of words and you want to calculate a score for each word based on a certain criterion. For example, one common scoring system assigns a point value to each letter (e.g., a=1, b=2, …, z=26) and sums them to get the total word score. Given an input list like [“dog”, “cat”, “python”], you want to output the scores [26, 24, 98] respectively.

Method 1: Using a for loop and a dictionary

This method involves creating a dictionary to map each letter to its score and then using a for loop to iterate over each word, adding up the total score. It is straightforward and easy to follow.

Here’s an example:

def calculate_word_scores(words):
    letter_scores = {chr(i+96): i for i in range(1, 27)}
    word_scores = []
    for word in words:
        score = sum(letter_scores[letter] for letter in word)
        word_scores.append(score)
    return word_scores

words = ["dog", "cat", "python"]
print(calculate_word_scores(words))

Output:

[26, 24, 98]

This function calculate_word_scores() starts by creating a dictionary letter_scores where each letter of the alphabet corresponds to its position in the alphabet. It then calculates the total score for each word in the input list by summing the scores of individual letters using a for loop and returns a list of scores.

Method 2: Using list comprehension

List comprehension offers a more concise and Pythonic way of calculating word scores. This method keeps the code clean and easy to read.

Here’s an example:

def calculate_word_scores(words):
    letter_scores = {chr(i+96): i for i in range(1, 27)}
    return [sum(letter_scores[letter] for letter in word) for word in words]

words = ["dog", "cat", "python"]
print(calculate_word_scores(words))

Output:

[26, 24, 98]

The function calculate_word_scores() again uses a dictionary of letter scores, but this time it returns the scores as a list comprehension. This single line inside the function replaces the for loop from Method 1.

Method 3: Using map and lambda functions

The map() function applies the lambda function to each word in the list to calculate the scores. This method is functional and compact.

Here’s an example:

def calculate_word_scores(words):
    letter_scores = {chr(i+96): i for i in range(1, 27)}
    return list(map(lambda word: sum(letter_scores[letter] for letter in word), words))

words = ["dog", "cat", "python"]
print(calculate_word_scores(words))

Output:

[26, 24, 98]

Instead of list comprehension, the calculate_word_scores() function now uses map() to apply a lambda function that calculates the word score, to each word in the list.

Method 4: Using a custom scoring function

Instead of hardcoding the letter scores, you can write a custom function to calculate the score based on more complex rules or criteria.

Here’s an example:

def letter_score(letter):
    return ord(letter.lower()) - 96

def calculate_word_scores(words, score_function):
    return [sum(score_function(letter) for letter in word) for word in words]

words = ["dog", "cat", "python"]
print(calculate_word_scores(words, letter_score))

Output:

[26, 24, 98]

The calculate_word_scores() function is now flexible, taking any scoring function as a parameter. The letter_score() function is used to calculate the score for each letter.

Bonus One-Liner Method 5: Using generator expressions with sum()

For a succinct one-liner, you can directly calculate the word scores within the sum() function using generator expressions.

Here’s an example:

words = ["dog", "cat", "python"]
print([sum(ord(letter.lower()) - 96 for letter in word) for word in words])

Output:

[26, 24, 98]

This one-liner does not define any functions. It calculates the score of each word directly within a list comprehension, using generator expressions to iterate through each letter.

Summary/Discussion

• Method 1: Using a for loop and dictionary. Straightforward. Good for beginners. Less Pythonic.
• Method 2: Using list comprehension. Concise. Pythonic. May become less readable with complex scoring rules.
• Method 3: Using map and lambda functions. Functional approach. Compact. Can be less intuitive for those not familiar with functional programming.
• Method 4: Using a custom scoring function. Highly flexible. Allows for custom score calculations. Requires defining an extra function.
• Bonus One-Liner Method 5: Very concise. Ideal for quick scripts. May sacrifice some readability.