asyncio-buffered-pipeline 0.0.4

Parallelize pipelines of Python async iterables/generators

asyncio-buffered-pipeline

Parallelise pipelines of Python async iterables/generators.

Installation

pip install asyncio-buffered-pipeline

Usage / What problem does this solve?

If you have a pipeline of async generators, even though each is async, only one runs at any given time. For example, the below runs in (just over) 30 seconds.

import asyncio

async def gen_1():
    for value in range(0, 10):
        await asyncio.sleep(1)  # Could be a slow HTTP request
        yield value

async def gen_2(it):
    async for value in it:
        await asyncio.sleep(1)  # Could be a slow HTTP request
        yield value * 2

async def gen_3(it):
    async for value in it:
        await asyncio.sleep(1)  # Could be a slow HTTP request
        yield value + 3

async def main():
    it_1 = gen_1()
    it_2 = gen_2(it_1)
    it_3 = gen_3(it_2)

    async for val in it_3:
        print(val)

asyncio.run(main())

The buffered_pipeline function allows you to make to a small change, passing each generator through its return value, to parallelise the generators to reduce this to (just over) 12 seconds.

import asyncio
from asyncio_buffer_iterable import buffered_pipeline

async def gen_1():
    for value in range(0, 10):
        await asyncio.sleep(1)  # Could be a slow HTTP request
        yield value

async def gen_2(it):
    async for value in it:
        await asyncio.sleep(1)  # Could be a slow HTTP request
        yield value * 2

async def gen_3(it):
    async for value in it:
        await asyncio.sleep(1)  # Could be a slow HTTP request
        yield value + 3

async def main():
    buffer_iterable = buffered_pipeline()
    it_1 = buffer_iterable(gen_1())
    it_2 = buffer_iterable(gen_2(it_1))
    it_3 = buffer_iterable(gen_3(it_2))

    async for val in it_3:
        print(val)

asyncio.run(main())

The buffered_pipeline ensures internal tasks are cancelled on any exception.