How do you rate limit calls with aiohttp? https://quentin.pradet.me/blog/how-do-you-rate-limit-calls-with-aiohttp.html

ratelimiter.py

#!/usr/bin/env python3

import asyncio
import time

import aiohttp

START = time.monotonic()


class RateLimiter:
    """Rate limits an HTTP client that would make get() and post() calls.

    Calls are rate-limited by host.
    https://quentin.pradet.me/blog/how-do-you-rate-limit-calls-with-aiohttp.html
    This class is not thread-safe."""
    RATE = 1  # one request per second
    MAX_TOKENS = 10

    def __init__(self, client):
        self.client = client
        self.tokens = self.MAX_TOKENS
        self.updated_at = time.monotonic()

    async def get(self, *args, **kwargs):
        await self.wait_for_token()
        now = time.monotonic() - START
        print(f'{now:.0f}s: ask {args[0]}')
        return self.client.get(*args, **kwargs)

    async def wait_for_token(self):
        while self.tokens < 1:
            self.add_new_tokens()
            await asyncio.sleep(0.1)
        self.tokens -= 1

    def add_new_tokens(self):
        now = time.monotonic()
        time_since_update = now - self.updated_at
        new_tokens = time_since_update * self.RATE
        if self.tokens + new_tokens >= 1:
            self.tokens = min(self.tokens + new_tokens, self.MAX_TOKENS)
            self.updated_at = now


async def fetch_one(client, i):
        url = f'https://httpbin.org/get?i={i}'
        # Watch out for the extra 'await' here!
        async with await client.get(url) as resp:
            resp = await resp.json()
            now = time.monotonic() - START
            print(f"{now:.0f}s: got {resp['args']}")


async def main():
    async with aiohttp.ClientSession() as client:
        client = RateLimiter(client)
        tasks = [asyncio.ensure_future(fetch_one(client, i)) for i in range(20)]
        await asyncio.gather(*tasks)


if __name__ == '__main__':
    # Requires Python 3.7+
    asyncio.run(main())

# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.

When replacing asyncio with trio and integrating this into an existing class this works like a charm. Very efficient algorithm implementation.

Sorry, I don't receive notifications for gists (that's a limitation of gists): prefer commenting on the blog post so that I can answer.

@iamsuneeth Only one request can be sent at the same time, the others will be in asyncio.sleep(). Does that make sense?

@jonbesga I added real parallel execution to the example (and updated it to use Python 3.7). This should convince you that this actually works. (I've been using this in production for months.)