List Comprehension in Python: Syntax and Use Cases

List comprehension is one of Python’s most elegant and powerful features. It allows you to create new lists by applying an expression to each item in an existing iterable (like a list, tuple, or range), all in a single line of code.

Whether you're filtering data, transforming values, or flattening nested lists, list comprehensions make your code more readable and concise.

Basic Syntax

Here’s the general syntax:

[expression for item in iterable if condition]

• expression: The value to store in the new list.

• item: The variable representing each element in the iterable.

• iterable: A sequence (like a list or range).

• condition (optional): A filter that determines whether the item should be included.

Simple Examples

1. Create a list of squares

squares = [x**2 for x in range(10)]

# Output: [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

2. Filter even numbers

evens = [x for x in range(20) if x % 2 == 0]

# Output: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]

3. Convert strings to uppercase

words = ["hello", "world", "python"]

upper_words = [word.upper() for word in words]

# Output: ['HELLO', 'WORLD', 'PYTHON']

Advanced Use Cases

4. Nested loops in list comprehension

pairs = [(x, y) for x in range(3) for y in range(3)]

# Output: [(0, 0), (0, 1), (0, 2), (1, 0), ..., (2, 2)]

5. Flatten a 2D list

matrix = [[1, 2], [3, 4], [5, 6]]

flat = [num for row in matrix for num in row]

# Output: [1, 2, 3, 4, 5, 6]

6. Apply a function conditionally

def square_even(x):

    return x**2 if x % 2 == 0 else x

result = [square_even(x) for x in range(10)]

# Output: [0, 1, 4, 3, 16, 5, 36, 7, 64, 9]

When Not to Use List Comprehension

While list comprehensions are concise, they can become hard to read if overused—especially with complex logic or deeply nested loops. In such cases, prefer regular for loops for clarity.

Try It Yourself

Here’s a quick challenge: 

Create a list of all numbers from 1 to 50 that are divisible by both 3 and 5.

divisible = [x for x in range(1, 51) if x % 3 == 0 and x % 5 == 0]

# Output: [15, 30, 45]

Final Thoughts

List comprehensions are a Pythonic way to write clean, efficient code. Mastering them will help you write better scripts, especially in data processing and machine learning workflows.

Next up in the series: map and filter methods