Generators & Lazy Iteration

16 min 40 XP

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Lesson 1 of 6 · View course roadmap

Step 1

Learn the idea

A generator is a function that produces values one at a time instead of building a whole list in memory. Swap return for yield and Python gives you a pausable function:

yield value — hands one value to the caller and freezes the function right there, local variables intact
next(gen) — resumes execution until the next yield
A for loop calls next() for you until the generator is exhausted

This is lazy evaluation: values are computed only when asked for. A generator over a 10 GB log file uses a few kilobytes of memory, because only one line exists at a time.

Generator expressions look like list comprehensions with round brackets: (n * n for n in range(10**9)) is created instantly — nothing is computed until you iterate.

Where you'll use this

Generators are how Python streams anything bigger than RAM: Django querysets, csv.reader, database cursors and every line-by-line log processor are lazy iterators. Data engineers chain generators into pipelines that crunch terabytes on a laptop.

Common mistakes

A generator is exhausted after one pass — looping over it a second time silently yields nothing. Recreate it or store the results if you need them twice.
Calling a generator function doesn't run any of its code: countdown(3) returns a generator object; the body only runs when you iterate.
Using len() on a generator → TypeError. A lazy stream has no length until it's consumed.

Pro tip

yield from delegates to another iterable in one line: def walk(tree): yield from tree.left; yield tree.value; yield from tree.right. It's the secret to elegant recursive generators.

Step 2

Try it yourself

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PYexample.py

⌘ + Enter to run

Output appears here…

Step 3

Pass the challenge +40 XP

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Write a generator function countdown(n) that yields the numbers from n down to 1. Loop over countdown(3) printing each value on its own line, then print Liftoff!.

Target output

3
2
1
Liftoff!

PYchallenge.py

def countdown(n):
    while n > 0:
        yield n
        n -= 1

for value in countdown(3):
    print(value)
print("Liftoff!")

Run your code to check it…

Step 4

Check your understanding

1. What makes a function a generator? Calling it with next() Containing at least one yield Returning a list The @generator decorator

2. Why can a generator represent an infinite sequence? It can't — Python would crash Values are produced one at a time, only when requested It compresses the values Python allocates infinite memory lazily

Last step

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