11.11. Async iterators

An async iterator is the asyncio version of an iterator. The Python Overview introduced the synchronous iterator protocol – __iter__ and __next__ – and the for loop that drives it. Async iterators add an await to each step, so the iterator can wait between values without blocking the event loop.

11.11.1. The protocol

A class is an async iterator when it implements

• __aiter__(self) – returns the iterator object, usually self.

• async def __anext__(self) – returns the next value, or raises StopAsyncIteration when there are no more.

The corresponding loop construct is async for:

import asyncio


class FrameCounter:
    """Yield N integers, one per frame period."""

    def __init__(self, n, period_ms):
        self._n = n
        self._period_ms = period_ms
        self._i = 0

    def __aiter__(self):
        return self

    async def __anext__(self):
        if self._i >= self._n:
            raise StopAsyncIteration
        await asyncio.sleep_ms(self._period_ms)
        self._i += 1
        return self._i

async def main():
    async for n in FrameCounter(5, 200):
        print(n)

The async for loop awaits each call to __anext__, so the coroutine running the loop yields to the event loop between values just like any other await.

11.11.2. When to reach for it

Whenever the application has a source of data that arrives over time and the consumer should iterate it lazily. A sensor that produces a sample per period, a network socket that delivers messages, a frame generator – anywhere the shape while True: x = await source.next(); process(x) fits, async for x in source is the cleaner spelling.

For sources that emit until a finite end condition, the iterator raises StopAsyncIteration and async for exits normally. For sources that never end – a continuous sensor stream, a long-running subscription – the loop runs until the coroutine it lives in is cancelled or its task is torn down.