List and Dictionary Comprehensions

Comprehensions provide a concise way to create lists and dictionaries from iterables.

List Comprehensions

List comprehensions create lists in a single line.

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

# With condition
even_squares = [x**2 for x in range(10) if x % 2 == 0]
print(even_squares)  # [0, 4, 16, 36, 64]

# Nested list comprehension
matrix = [[i*j for j in range(3)] for i in range(3)]
print(matrix)  # [[0, 0, 0], [0, 1, 2], [0, 2, 4]]

Dictionary Comprehensions

Dictionary comprehensions create dictionaries.

# Basic dictionary comprehension
squares_dict = {x: x**2 for x in range(5)}
print(squares_dict)  # {0: 0, 1: 1, 2: 4, 3: 9, 4: 16}

# With condition
even_squares_dict = {x: x**2 for x in range(10) if x % 2 == 0}
print(even_squares_dict)  # {0: 0, 2: 4, 4: 16, 6: 36, 8: 64}

# From two lists
keys = ['a', 'b', 'c']
values = [1, 2, 3]
my_dict = {k: v for k, v in zip(keys, values)}
print(my_dict)  # {'a': 1, 'b': 2, 'c': 3}

Set Comprehensions

You can also create sets using comprehensions.

# Set comprehension
squares_set = {x**2 for x in range(10)}
print(squares_set)  # {0, 1, 4, 9, 16, 25, 36, 49, 64, 81}

Advantages of Comprehensions

• More concise than traditional loops

• Often faster than equivalent loop code

• Can be more readable for simple operations

Equivalent Code

List comprehension:

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

Equivalent with loop:

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