Python Generators Practice Guide: Lazy Values

Start with a function that yields

A generator function looks like a normal function until it reaches yield. At that point it returns one value and remembers its local state. The next request continues on the following line. Use a for loop when you want every value, and next when you want one at a time.

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

for value in countdown(3):
    print(value)

Pause and resume

Generators are single-use

A generator object is an iterator. Once it is exhausted, asking for another value raises StopIteration. Create a new generator if you need to traverse the data again. This is different from a list, which can be iterated repeatedly.

def pair():
    yield 1
    yield 2

gen = pair()
print(list(gen))
print(list(gen))

The second pass is empty

Use expressions for short pipelines

A generator expression is compact when the transformation is simple. Parentheses are enough; you do not need a named function. The expression is still lazy, so wrapping it in list or sum is what actually requests values.

squares = (n * n for n in range(4))
print(sum(squares))

A one-line lazy pipeline

Chain small stages

A generator can consume another generator. This lets you separate reading, filtering, and formatting without building intermediate lists. Keep each stage small and give it a clear name when the pipeline grows beyond a single expression.

def evens(values):
    for value in values:
        if value % 2 == 0:
            yield value

print(list(evens(range(6))))

One stage at a time

Know when a list is better

Generators trade random access and repeatability for lazy memory use. If you need len, indexing, sorting, or several passes, materialize a list. Choose the data structure that matches the next operation, not the one that looks shortest.

values = list(n for n in range(3))
print(len(values))
print(values[1])

Materialize when needed

Your practice checklist

• Use yield when values can be produced on demand.
• Call next only when you need one value.
• Create a new generator for a second pass.
• Consume a generator expression with list, sum, or a loop.
• Materialize a list when you need indexing or length.

Common questions

Keep reading:

• Python Generators
• Python Exercises With Answers: How to Practice Without Copying
• Python Practice for Beginners: A Simple 4-Week Plan