Deep Asyncio (ix) asynchronous generators

Async Generators:yield Inside Async def functions

If you use yield in async def, the answer is to generate an asynchronous generator function, which can be confusing if you have a generator, a framework such as twisted, tornado, or a yield from experience.

Therefore, before continuing to study, we should bear in mind these several points:
1. The Cheng generator is a completely different concept;
2. The asynchronous generator is similar to the normal generator;
3. For iterations with IO, async for replace the normal one for .

The previous chapter uses asynchronous iterators to demonstrate interaction with Redis, which is actually easier with asynchronous generators.

import asynciofrom aioredis import create_redisasync def main():    redis = await create_redis((‘localhost‘, 6379))    keys = [‘America‘, ‘Africa‘, ‘Europe‘, ‘Asia‘]    async for value in one_at_a_time(redis, keys):   # 1        await process(value)async def one_at_a_time(redis, keys):   # 2    for k in keys:        value = await redis.get(k)  # 3        yield value    # 4asyncio.get_event_loop().run_until_complete(main())

1. Almost the same, just changed a name;

2. Now that the function is declared with async def, and yield is used within the function, it can be identified as an asynchronous generator function;

3. Do not need to be as complex as the previous example, directly let loop to deal with;

4. Yield values like a common generator.

Just as the common generator makes the code shorter, asynchronous generators also have the same advantages in asynchronous programming, and may be a bit more complicated for beginners, but they can be adapted to practice a bit more.

Deep Asyncio (ix) asynchronous generators