Produce values one at a time.
✍️ 3 exercises + code challenge in this lessonAn iterator is an object you can loop over, one value at a time. iter() creates one and next() gets the next value.
A generator is a function that uses yield instead of return. It produces values lazily, so it can represent huge or even infinite sequences without using much memory.
Generator expressions look like list comprehensions with round brackets: (x * x for x in range(10)).
Mastering Python Iterators & Generators helps you write clean and reliable Python code. Follow standard conventions, test edge cases, and keep logic simple. Try running the code example below and complete the exercises to build confidence.
it = iter(["a", "b", "c"])
print(next(it), next(it), next(it))
def fibonacci(limit):
a, b = 0, 1
while a < limit:
yield a
a, b = b, a + b
print(list(fibonacci(100)))
total = sum(x * x for x in range(1_000_000))
print("Sum of squares:", total)Check what you learned in “Python Iterators & Generators”.
Produce values one at a time in a generator.
def count_up(n):
for i in range(n):
i
Which function gets the next value from an iterator?
Write a generator evens(n) that yields even numbers below n, and print list(evens(10)).
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