List Comprehensions

Writing Pythonic Code

In Python, we often want to create a new list by transforming or filtering another list. You could use a for loop for this, but Python offers a more concise and elegant way: List Comprehensions.

Traditional Loop vs. Comprehension

Imagine you want to create a list of square numbers.

Using a For Loop:

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numbers = [1, 2, 3, 4, 5]
squares = []

for n in numbers:
    squares.append(n * n)

print(squares) # [1, 4, 9, 16, 25]

Using a List Comprehension:

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numbers = [1, 2, 3, 4, 5]
squares = [n * n for n in numbers]

print(squares) # [1, 4, 9, 16, 25]

The Syntax

new_list = [expression for item in iterable]

1. expression: What you want to do to each item.
2. item: The temporary variable name.
3. iterable: The original collection (list, range, etc.).

Adding a Condition (Filtering)

You can also add an if statement to the end to filter items.

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numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

# Only include even numbers
evens = [n for n in numbers if n % 2 == 0]

print(evens) # [2, 4, 6, 8, 10]

Why use them?

• Shorter: You can do in 1 line what usually takes 3-4.
• Readable: Once you’re used to them, they are very easy to scan.
• Performance: They are slightly faster than manual .append() calls.

Interactive Practice

Try writing a comprehension that takes a list of strings and creates a new list with all strings converted to uppercase using .upper().