What are Python generators and how are they different from iterators?

A generator is a special type of iterator that is defined using a function with the yield statement. When called, it returns a generator object that produces values lazily, generating each value only when requested via next() or a loop. Generators maintain their state between yields, allowing efficient memory usage for large or infinite sequences. An iterator, in general, is any object that implements the __iter__() and __next__() methods; it can be a list, a generator, or a custom class. All generators are iterators, but not all iterators are generators. The key differences are: generators use yield to produce values on the fly, whereas iterators may pre‑store all items; generators are defined by syntax, while iterators can be implemented manually; generators automatically handle StopIteration when exhausted. Use generators when you need to process large datasets, stream data, or implement lazy evaluation to save memory.