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Python List Comprehensions Guide with Examples

Python List Comprehensions Guide with Examples | Rustcode

Python List Comprehensions Guide with Examples

List comprehensions are a Pythonic way to create new lists from existing iterables using concise, readable, one-line syntax. They simplify code that builds lists with for loops and enable transformations, filtering, and even nesting in a few words. Let’s see how they work, why you should use them, and the most useful patterns with real code examples.

Table of Content

Why Use List Comprehensions?

  • Conciseness: Write in one line what would take several with a loop.
  • Readability: Express your intent more clearly (“what” not “how”).
  • Performance: Often faster than equivalent for loops in pure Python.

Syntax & Structure

[expression for item in iterable if condition]
  • expression: Value or operation to include in the new list.
  • item: Variable name for each element in iterable.
  • iterable: Original list, range, or any object you loop over.
  • if condition (optional): Only include items that meet this condition.

Basic Examples

1. Create a list of squares from 0 to 9

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

Output

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

2. Double each value in a list

numbers = [1, 2, 3, 4]
doubled = [num * 2 for num in numbers]
print(doubled)

Output

[2, 4, 6, 8]

3. Convert a list of words to lowercase

words = ["Python", "List", "Comprehension"]
lowercased = [w.lower() for w in words]
print(lowercased)

Output

['python', 'list', 'comprehension']

Filtering with If Clauses

Add an if clause to include items only if they meet a condition.

1. Only even numbers from 0 to 9

even = [x for x in range(10) if x % 2 == 0]
print(even)

Output

[0, 2, 4, 6, 8]

2. Keep fruits that contain the letter 'a'

fruits = ["apple", "banana", "cherry", "kiwi", "mango"]
with_a = [x for x in fruits if "a" in x]
print(with_a)

Output

['apple', 'banana', 'mango']

If-Else in List Comprehension

You can use an if-else statement to assign different values based on a condition.

1. Label numbers as Even or Odd

numbers = range(1, 6)
labels = ["Even" if x % 2 == 0 else "Odd" for x in numbers]
print(labels)

Output

['Odd', 'Even', 'Odd', 'Even', 'Odd']

2. Square even, cube odd numbers

result = [x**2 if x % 2 == 0 else x**3 for x in range(1, 6)]
print(result)

Output

[1, 4, 27, 16, 125]

Nested List Comprehensions

List comprehensions can be nested to work with multiple loops or build complex structures.

1. Flatten a 2D list (matrix)

matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
flat = [num for row in matrix for num in row]
print(flat)

Output

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

2. Create coordinate pairs for a grid

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

Output

[(0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2), (2, 0), (2, 1), (2, 2)]

Comparison Table: Loop vs List Comprehension

Pattern for Loop Version List Comprehension Output
Squares of numbers (0–4) 
result = []
for x in range(5):
    result.append(x*x)
 
[x*x for x in range(5)]
 [0, 1, 4, 9, 16]
Words with 5+ letters 
selected = []
for word in words:
    if len(word) >= 5:
        selected.append(word)
 
[word for word in words if len(word) >= 5]
 Words with ≥5 letters

Useful Tips

  • Keep it readable: For complex logic, a standard for loop is sometimes clearer.
  • Performance: List comprehensions are often faster for simple transformations, but not always for deeply nested or side-effect code.
  • Side effects: Avoid assignments or printing inside the comprehension. Stick to producing the list, not actions.
  • Use generator expressions (...) instead of [...] when you don't need the entire list in memory.
  • Mutability: Each run of the comprehension creates a new list; changing one list won’t affect the original.

Conclusion

List comprehensions are one of Python’s most powerful features for generating, transforming, and filtering lists in a succinct and readable way. Practice with the patterns above, and soon writing efficient, elegant one-liners will become second nature.

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