AsyncIO-enabled rate limiter - limit the rate of API calls!
Public APIs such as Wiktionary may apply rate limits at which one may call any part of their API. A generous API will inform you of this rate limit through a well structured error. Other cases, however, may not be so graceous. It may respond with a general purpose status code 500; a generic, non-informative HTML error page; or even outright close the connection lacking any response whatsoever. For these cases, a rate limiter can help avoid triggering such a response altogether.
AsyncRateLimiter is partly inspired by ratelimiter. The main difference is that AsyncRateLimiter is designed for asynchronous usage, whereas ratelimiter is designed for sequential API calls - further wrap-around code is needed to enable asynchronous code. AsyncRateLimiter integrates with AsyncIO for convenience.
Simply install via pip install asyncratelimiter
There is a single dependency for convenience: requests
AsyncRateLimiter supports two distinct usage styles:
- Threaded style - incorporates sequential APIs such as requests with rate-limited AsyncIO
- Async style - limits calls to AsyncIO-based APIs
Threaded style revolves around the ThreadedRateLimiter.dispatch(fun, /, *args, **kwargs) method. fun is enqueued with Python's standard concurrent.futures.ThreadPoolExecutor, which is particularly useful to dispatch multiple I/O-dependent tasks and waiting on their completion simultaneously.
from asyncratelimiter import ThreadedRateLimiter
import asyncio
async def main():
with ThreadedRateLimiter(max_rate=10, interval=1) as limiter:
futures = []
for _ in range(100):
futures.append(limiter.dispatch())
asyncio.run(main())A simple derivation of ThreadedRateLimiter exposing get, post, put, delete, and request methods; one may still access ThreadedRateLimiter.dispatch as normal.
from asyncratelimiter import RequestLimiter
import asyncio
async def main():
futures = []
with RequestLimiter(max_rate=10, interval=2) as requests:
for _ in range(100):
futures.append(requests.get('https://google.com'))
await asyncio.gather(*futures)
# Should take ~18-20 seconds - the last batch need not necessarily take the full 2s interval
asyncio.run(main())Async style behaves much like ratelimiter, except AsyncIO-integrated.
from asyncratelimiter import AsyncRateLimiter
import asyncio
async def foo():
return 42
async def main():
ratelimiter = AsyncRateLimiter(max_rate=10, interval=1)
for _ in range(100):
async with ratelimiter:
await foo()
asyncio.run(main())For concurrently running tasks, async style still exposes a dispatch(aw: Awaitable) method:
from asyncratelimiter import AsyncRateLimiter
import asyncio
async def foo(delay: float):
await asyncio.sleep(delay)
return 42
async def main():
ratelimiter = AsyncRateLimiter(max_rate=10, interval=1)
aws = []
for _ in range(100):
aws.append(ratelimiter.dispatch(foo(0.5)))
await asyncio.gatcher(*aws)MIT License
Copyright (c) 2021 Kiruse
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