Oppiskele Semaphores for Rate Limiting

Pyyhkäise näyttääksesi valikon

A lock allows exactly one coroutine at a time. A semaphore allows up to n coroutines at a time. This makes it the right tool for rate limiting – preventing your program from hammering an API or exhausting a connection pool.

The Problem: Too Many Concurrent Requests

Without any limit, asyncio.gather() fires all requests simultaneously. For 100 posts, that's 100 connections at once – most APIs will throttle or reject them:


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import asyncio
import httpx
import nest_asyncio

nest_asyncio.apply()

# Fetching 20 posts with no concurrency limit
async def fetch_post(client, post_id):
    response = await client.get(
        f"https://jsonplaceholder.typicode.com/posts/{post_id}"
    )
    return response.json()["title"]

async def main():
    async with httpx.AsyncClient() as client:
        # All 20 requests fire simultaneously
        titles = await asyncio.gather(
            *[fetch_post(client, post_id) for post_id in range(1, 21)]
        )

    print(f"Fetched {len(titles)} titles")

asyncio.run(main())

Using `asyncio.Semaphore()`

Wrap each request with a semaphore to cap the number of concurrent connections:


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import asyncio
import httpx
import nest_asyncio

nest_asyncio.apply()

semaphore = asyncio.Semaphore(5)  # Maximum 5 concurrent requests

# Fetching a post with a concurrency limit
async def fetch_post(client, post_id):
    async with semaphore:  # Acquiring a semaphore slot
        response = await client.get(
            f"https://jsonplaceholder.typicode.com/posts/{post_id}"
        )
        return response.json()["title"]

async def main():
    async with httpx.AsyncClient() as client:
        titles = await asyncio.gather(
            *[fetch_post(client, post_id) for post_id in range(1, 21)]
        )

    print(f"Fetched {len(titles)} titles")

asyncio.run(main())

All 20 tasks are created immediately, but at most 5 can hold a semaphore slot at once. The rest wait until a slot is released.

Combining a Semaphore with a Timeout

Rate limiting and timeouts work well together – limit concurrency and fail fast if a request hangs:


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import asyncio
import httpx
import nest_asyncio

nest_asyncio.apply()

semaphore = asyncio.Semaphore(3)

# Fetching a post with both a semaphore and a per-request timeout
async def fetch_post(client, post_id):
    async with semaphore:
        try:
            response = await asyncio.wait_for(
                client.get(
                    f"https://jsonplaceholder.typicode.com/posts/{post_id}"
                ),
                timeout=4.0,
            )
            return response.json()["title"]
        except asyncio.TimeoutError:
            return f"Post {post_id} timed out"

async def main():
    async with httpx.AsyncClient() as client:
        titles = await asyncio.gather(
            *[fetch_post(client, post_id) for post_id in range(1, 11)]
        )

    for title in titles:
        print(title)

asyncio.run(main())

`Lock` vs `Semaphore`

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Osio 3. Luku 3

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Osio 3. Luku 3

Semaphores for Rate Limiting

The Problem: Too Many Concurrent Requests

Using asyncio.Semaphore()

Combining a Semaphore with a Timeout

Lock vs Semaphore

Using `asyncio.Semaphore()`

`Lock` vs `Semaphore`