Throttling tools for py3.5+ asyncio.
asyncio and async/await are pretty awesome tools! Asynchronous stuff! In Python! Without insanity!
Well, unfortunately given the nature of this style of programming it’s not bloody easy sometimes.
Well, this project provides at least one tool to help ya out in a reasonably simple way.
asyncio_throttler is a throttling system for Python 3.5+, designed aiohttp throttling in mind but designed to be flexible enough to handle most throttling and rate limiting needs.
Well, get it:
$ pyvenv env/ $ . env/bin/activate $ pip install asyncio_throttler # Pin the damned version in setup.py # you bloody savage.
If you don’t have Python 3.5, check out pyenv (not to be confused with pyvenv), a Python version manager similar to rbenv.
If you really don’t want pyenv, brew install python3 will non-destructively install Python 3.5+.
Anyways, here’s the terrible usage example I wrote while developing the thing. The code is well documented, concise, and hopefully easily understandable by humans, but this should getcha started. I’ll make better docs, I promise. I gotta sleep at some point.
WARNING: THIS WILL NEVER COMPLETE, THE THROTTLE ERROR WILL BOUNCE AROUND FOREVER. ON PURPOSE. TO DEMONSTRATE THINGS DON’T GET LOST. SERIOUSLY.
"""Dump test module I built while writing this thing. Need to make real tests, but whatcha gonna do ya got schedules and stuff amirite? """ import logging import asyncio from asyncio_throttler import Throttler, ThrottleException # Demonstrates that windowing, throttling, and every other known feature # works, I think. if __name__ == '__main__': logger = logging.getLogger('testthrottler') logger.setLevel(logging.DEBUG) handler = logging.StreamHandler() format_template = '%(asctime)s:%(name)s:%(levelname)s – %(message)s' handler.setFormatter(logging.Formatter(fmt=format_template, datefmt='%Y-%m-%d %H:%M:%S')) logger.addHandler(handler) async def dummy_consumer(item): print("Item received:", item) await asyncio.sleep(2) import random async def dummy_task(): logger.info("Executed") return await asyncio.sleep(1, random.randrange(1, 1000)) async def bad_dummy_task(): logger.info("Executed and gonna throw a throttle") raise ThrottleException(bad_dummy_task()) loop = asyncio.get_event_loop() # roflcoptr todo_list = [dummy_task() for _ in range(1, 31)] todo_list.append(bad_dummy_task()) todo_list = todo_list + [dummy_task() for _ in range(1, 31)] throttler = Throttler( todo_list, dummy_consumer, time_window=10, per_time_window=20, concurrency=5, log_handler=logging.StreamHandler(), log_level=logging.DEBUG, loop=loop ) loop.run_until_complete(throttler.run()) loop.close()
How’s It Works
A Throttler is instantiated with a list of awaitables, an async function, and numerous keyword arg knobs you adjust to suit your purposes.
Inside are two asyncio.Queue objects, and one asyncio.LifoQueue.
exceptions is a Queue for non-throttle exceptions we catch.
processed is a Queue for processed output. This is what your consumer will consume from.
todo is a LifoQueue that holds your unprocessed task list. It’s initially fed from a reverse of the list you pass to Throttler, which is fast and an iterator. It’s LIFO just so we can pop throttled items back into it at the front.
Several internal functions are composed to create an async producer and consumer loop where items are processed as fast as possible given the restrictions imposed at Throttler instantiation. It’ll backoff time_window when throttled, only execute concurrency of your tasks at a time, and will wait time_window after triggering the processing of per_time_window items.
That oughta cover a few cases…
Anyways, the async consumer_fn you pass in will be executed as results become available, immediately, for writing to disk or somethin’.
This was painful.
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