How to use `async for` in Python?

But it is hard for me to understand what I got by use async for here instead of simple for.

The underlying misunderstanding is expecting async for to automatically parallelize the iteration. It doesn’t do that, it simply allows sequential iteration over an async source. For example, you can use async for to iterate over lines coming from a TCP stream, messages from a websocket, or database records from an async DB driver.

None of the above would work with an ordinary for, at least not without blocking the event loop. This is because for calls __next__ as a blocking function and doesn’t await its result. You cannot manually await elements obtained by for because for expects __next__ to signal the end of iteration by raising StopIteration. If __next__ is a coroutine, the StopIteration exception won’t be visible before awaiting it. This is why async for was introduced, not just in Python, but also in other languages with async/await and generalized for.

If you want to run the loop iterations in parallel, you need to start them as parallel coroutines and use asyncio.as_completed or equivalent to retrieve their results as they come:

async def x(i):
    print(f"start {i}")
    await asyncio.sleep(1)
    print(f"end {i}")
    return i

# run x(0)..x(10) concurrently and process results as they arrive
for f in asyncio.as_completed([x(i) for i in range(10)]):
    result = await f
    # ... do something with the result ...

If you don’t care about reacting to results immediately as they arrive, but you need them all, you can make it even simpler by using asyncio.gather:

# run x(0)..x(10) concurrently and process results when all are done
results = await asyncio.gather(*[x(i) for i in range(10)])