Generators and yield

A generator is a function that uses yield to produce values one at a time, instead of return to produce a single result. Calling a generator function does not run its body; it returns a generator object. Each call to next runs the function up to the next yield, then suspends.

Return ends a function and sends a single value to the caller. Yield produces a value and suspends the function, preserving its state so it can resume later. A function with any yield becomes a generator function. Return inside a generator signals StopIteration with the returned value.

Generators produce values lazily, computing each one on demand. They use constant memory regardless of the total number of values, while a list of equivalent contents uses memory proportional to the number of elements. Generators are ideal for streaming data, infinite sequences, and pipelines.

Yield from delegates iteration to a sub-generator or any iterable. It is equivalent to a for loop that yields each value, but it also forwards values sent to the outer generator and propagates return values. It is essential for cleanly composing generators.

Send passes a value into a paused generator, which becomes the result of the corresponding yield expression. Throw raises an exception inside the generator at the point of yield. Close raises GeneratorExit, asking the generator to clean up and stop. These methods enable coroutine-like patterns.

A generator pipeline is a chain of generators where each consumes the output of the previous. Each stage processes one item at a time without holding the entire dataset in memory. Pipelines are a powerful way to express data transformations clearly while maintaining low memory use. ---