What are generators and iterators, and when would you use yield instead of returning a list?

An iterator is any object with __iter__ and __next__, producing values one at a time until it raises StopIteration. A generator is the easy way to write one: a function containing yield. Calling it does not run the body — it returns a generator object, and each next() runs until the next yield, then suspends with its local state intact.

def read_large_file(path):
    with open(path) as f:
        for line in f:
            yield line.strip()

Why use one instead of building a list:

• Memory. A list of ten million rows needs all ten million in RAM. A generator holds one at a time — this is the whole argument.
• Laziness. Work is done only as consumed, so an early break costs nothing.
• Composition. Generators chain into pipelines where each stage streams into the next.
• Infinite sequences become expressible at all.

The trade-offs: you can only iterate once, and you cannot index or take len(). If you need random access or multiple passes, build the list.

Note: A generator expression is the same thing in one line — sum(x*x for x in data) never materialises the intermediate sequence, unlike the list-comprehension version.