Python: generators and lazy evaluation

A generator produces values on demand. It is useful when the input is large or when a pipeline can process one item at a time.

def squares(limit: int):
    for number in range(limit):
        yield number * number


print(sum(squares(5)))  # 0 + 1 + 4 + 9 + 16 = 30

The generator keeps only its current state, so its auxiliary space is \(O(1)\). Collecting all results with list(squares(n)) instead requires \(O(n)\) space.

One pass

A generator is exhausted after iteration. Create another generator if you need to iterate again.