Python List Comprehensions — Write Cleaner, Faster Code

What Are List Comprehensions?

List comprehensions provide a concise way to create lists. They replace verbose for-loops with a single, readable line of code.

Basic Syntax

# Traditional for-loop
squares = []
for x in range(10):
    squares.append(x ** 2)

# List comprehension
squares = [x ** 2 for x in range(10)]
print(squares)  # [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

Adding Conditions

# Filter even numbers
evens = [x for x in range(20) if x % 2 == 0]

# If-else (expression comes before the if)
labels = ['even' if x % 2 == 0 else 'odd' for x in range(5)]
# ['even', 'odd', 'even', 'odd', 'even']

Nested Comprehensions

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

Dict and Set Comprehensions

# Dictionary comprehension
names = ['Alice', 'Bob', 'Charlie']
name_lengths = {name: len(name) for name in names}
# {'Alice': 5, 'Bob': 3, 'Charlie': 7}

# Invert a dictionary
inverted = {v: k for k, v in original.items()}

Real-World Examples

# Clean and transform data
raw_prices = [' $19.99 ', '$24.50', '$invalid', '$32.00 ']
clean_prices = [
    float(p.strip().replace('$', ''))
    for p in raw_prices
    if p.strip().replace('$', '').replace('.', '').isdigit()
]
print(clean_prices)  # [19.99, 24.5, 32.0]