Generators

Generators

A generator is a function that produces values lazily using yield. Unlike lists, generators don't store all values in memory at once — they compute each value on demand.

yield

def count_up(start, end):
    n = start
    while n <= end:
        yield n     # produce a value, then pause
        n += 1

for x in count_up(1, 5):
    print(x)  # 1, 2, 3, 4, 5

Infinite Generators

Generators can be infinite — only compute as many values as you need:

def naturals():
    n = 0
    while True:
        yield n
        n += 1

next()

Pull values one at a time with next():

gen = count_up(1, 3)
next(gen)  # 1
next(gen)  # 2
next(gen)  # 3
next(gen)  # raises StopIteration

Generator Expressions

Like list comprehensions, but lazy:

squares = (x**2 for x in range(1_000_000))  # no memory cost
next(squares)  # 0

itertools

itertools has powerful tools for working with iterables: islice, chain, cycle, accumulate, etc.

from itertools import islice
first_five = list(islice(naturals(), 5))  # [0, 1, 2, 3, 4]

Your Task

Implement fibonacci() — an infinite generator that yields Fibonacci numbers starting from 0, 1, 1, 2, 3, 5, 8, 13, ...