List, Set, and Dictionary Comprehensions

List, Set, and Dictionary Comprehensions in Python

Python provides comprehensions as a concise way to create lists, sets, and dictionaries in a single line. They make code more readable and efficient.

1. List Comprehensions

• Create a list by applying an expression to each item in an iterable.

• Optional condition to filter items.

Syntax:

[expression for item in iterable if condition]

Examples:

# Square of numbers
numbers = [1, 2, 3, 4, 5]
squares = [x**2 for x in numbers]
print(squares)  # [1, 4, 9, 16, 25]

# Even numbers only
even_numbers = [x for x in numbers if x % 2 == 0]
print(even_numbers)  # [2, 4]

# Nested loops
pairs = [(x, y) for x in [1, 2] for y in [3, 4]]
print(pairs)  # [(1, 3), (1, 4), (2, 3), (2, 4)]

2. Set Comprehensions

• Similar to list comprehensions but create sets.

• Removes duplicates automatically.

Syntax:

{expression for item in iterable if condition}

Examples:

numbers = [1, 2, 2, 3, 4, 4, 5]
squared_set = {x**2 for x in numbers}
print(squared_set)  # {1, 4, 9, 16, 25}

# Set of even numbers
even_set = {x for x in numbers if x % 2 == 0}
print(even_set)  # {2, 4}

3. Dictionary Comprehensions

• Create dictionaries using key-value pairs in a concise format.

Syntax:

{key_expression: value_expression for item in iterable if condition}

Examples:

# Numbers and their squares
numbers = [1, 2, 3, 4, 5]
squares_dict = {x: x**2 for x in numbers}
print(squares_dict)  # {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

# Filter only even numbers
even_dict = {x: x**2 for x in numbers if x % 2 == 0}
print(even_dict)  # {2: 4, 4: 16}

# Swapping keys and values
original = {'a': 1, 'b': 2}
swapped = {v: k for k, v in original.items()}
print(swapped)  # {1: 'a', 2: 'b'}

4. Key Points

• Comprehensions provide compact syntax for constructing sequences.

• Can include conditions (if) and nested loops.

• List comprehension → list

• Set comprehension → set

• Dictionary comprehension → dictionary

• Improves readability and efficiency over traditional loops.