List Comprehensions and Generators

Compact collection building, generator expressions, and the yield keyword.

List Comprehensions

A concise way to create lists from an iterable, optionally filtering elements:

# [expression for item in iterable if condition]
squares = [x**2 for x in range(1, 6)]
print(squares)   # [1, 4, 9, 16, 25]

evens = [x for x in range(20) if x % 2 == 0]

words = ["hello", "world"]
upper = [w.upper() for w in words]

Dict and Set Comprehensions

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

unique_squares = {x**2 for x in [-2, -1, 0, 1, 2]}
# {0, 1, 4}

Generator Expressions

Like list comprehensions but lazy — they produce values one at a time without storing all in memory:

gen = (x**2 for x in range(1000000))  # no memory spike
print(next(gen))   # 0
print(next(gen))   # 1

yield and Generator Functions

def fibonacci(n):
    a, b = 0, 1
    for _ in range(n):
        yield a
        a, b = b, a + b

for num in fibonacci(10):
    print(num, end=" ")
# 0 1 1 2 3 5 8 13 21 34