Generators are a type of function in Python that allow for the creation of iterators. They are used to generate a sequence of values, one at a time, instead of generating the entire sequence at once. This makes them memory efficient and allows for the processing of large data sets or infinite sequences. Generators are defined using the `yield` keyword instead of `return`. When a generator function is called, it returns an iterator object that can be iterated over using a loop or other iterator methods. Each time the `yield` statement is encountered, the generator function pauses and returns the value to the caller. The next time the generator is called, it resumes execution from where it left off, remembering the state of the function. The advantage of generators is that they generate values on the fly, only when needed, which saves memory and improves performance. They are particularly useful when dealing with large data sets or when the complete sequence is not required at once. Generators can also be used to create infinite sequences, such as an infinite stream of random numbers. To iterate over a generator, you can use a `for` loop or the `next()` function. The loop will automatically handle the StopIteration exception when the generator is exhausted. In summary, generators are a powerful feature in Python that allow for the creation of iterators. They provide a memory-efficient way to generate sequences of values on the fly, making them ideal for processing large data sets or infinite sequences.