Python ยท Chapter 30 of 45
Iterators & Generators
An ITERATOR yields values one at a time via the `__next__` protocol. A GENERATOR is a simple way to write iterators using `yield`.
Generators are memory-efficient โ they compute values on demand rather than building a whole list.
yield
Any function containing `yield` becomes a generator. Calling it returns a generator object, not the value.
When to use
For large or infinite sequences, streaming data, or lazily transforming an iterable.
Example 1 (python)
def count_up(n):
i = 1
while i <= n:
yield i
i += 1
for x in count_up(3):
print(x)Output
1
2
3yield produces one value per iteration.
Example 2 (python)
squares = (x*x for x in range(4))
print(list(squares))Output
[0, 1, 4, 9]Generator expression uses () instead of [].
Key points
- `yield` turns a function into a generator.
- Lazy: values are produced on demand.
- Memory-efficient for large data.
- Generator expression: `(x for x in ...)`.
๐ก Note: You can iterate a generator only ONCE โ call the function again to get a fresh generator.