Python List comprehensions

List comprehensions in Python provide a concise way to create lists. They are used to generate new lists by applying an expression to each item in an existing iterable. List comprehensions can also include conditional logic to filter items from the iterable.

Basic Syntax

The basic syntax for a list comprehension is:

[expression for item in iterable]

This translates to: "Generate a list by evaluating the expression for each item in the iterable."

Examples

1. Simple List Comprehension:

   Create a list of squares of numbers 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. List Comprehension with Condition:

Create a list of even numbers from 0 to 9.

evens = [x for x in range(10) if x % 2 == 0] print(evens) # Output: [0, 2, 4, 6, 8]

3. Nested List Comprehensions:

Create a 2D list (matrix) using nested list comprehensions.

matrix = [[i + j for j in range(3)] for i in range(3)] print(matrix) # Output: [[0, 1, 2], [1, 2, 3], [2, 3, 4]]

Combining Multiple Conditions

You can combine multiple conditions within a list comprehension.

numbers = [x for x in range(20) if x % 2 == 0 if x % 3 == 0] print(numbers) # Output: [0, 6, 12, 18]

Using Functions in List Comprehensions

You can also use functions within list comprehensions.

def is_prime(num): if num < 2: return False for i in range(2, int(num**0.5) + 1): if num % i == 0: return False return True primes = [x for x in range(50) if is_prime(x)] print(primes) # Output: [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47]

List Comprehension with else

If you want to include an else condition, it needs to be part of the expression itself using a ternary conditional operator.

even_odd = ["Even" if x % 2 == 0 else "Odd" for x in range(10)] print(even_odd) # Output: ['Even', 'Odd', 'Even', 'Odd', 'Even', 'Odd', 'Even', 'Odd', 'Even', 'Odd']

Dictionary and Set Comprehensions

List comprehension syntax can be adapted to create dictionaries and sets as well.

Dictionary Comprehension:

squares_dict = {x: x**2 for x in range(10)} print(squares_dict) # Output: {0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81}

Set Comprehension:

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

Summary

• Basic Syntax: [expression for item in iterable]
• Conditionals: [expression for item in iterable if condition]
• Nested Comprehensions: [[expression for item in iterable] for item in iterable]
• Multiple Conditions: [expression for item in iterable if condition1 if condition2]
• Functions in Comprehensions: Apply functions within comprehensions.
• Ternary Operators: Use ["Even" if x % 2 == 0 else "Odd" for x in iterable] for including else.
• Dictionary Comprehensions: {key_expression: value_expression for item in iterable}
• Set Comprehensions: {expression for item in iterable}

List comprehensions provide a powerful, readable, and efficient way to create lists, dictionaries, and sets in Python.