arate-limit 1.1.6

Asyncio rate limiter

arate-limit

A flexible and robust rate limiting library for Python applications, offering multiple implementation strategies including leaky bucket, token bucket, and Redis-based sliding window rate limiters.

Features

• Multiple rate limiting strategies:
  • Leaky bucket rate limiter
  • Token bucket rate limiter
  • Redis-based sliding window rate limiter
  • Redis-based sliding window API rate limiter
• Async/await support using asyncio
• Configurable time windows and burst allowances
• Safe for concurrent access within asyncio applications
• Redis integration for distributed rate limiting

Installation

pip install arate-limit

Usage

Leaky Bucket Rate Limiter

A rate limiter that implements the leaky bucket algorithm, which smooths out bursts of requests and processes them at a steady rate:

import asyncio

from rate_limiter import LeakyBucketRateLimiter

async def example():
    # Allow 100 requests per minute with some slack
    limiter = LeakyBucketRateLimiter(event_count=100, time_window=60, slack=10)

    async def limited_task():
        await limiter.wait()
        # Your rate-limited code here
        print("Task executed")

    # Execute multiple tasks
    tasks = [limited_task() for _ in range(10)]
    await asyncio.gather(*tasks)

Token Bucket Rate Limiter

More sophisticated rate limiting with burst support:

from datetime import timedelta

from rate_limiter import TokenBucketRateLimiter

async def example():
    # Allow 1000 requests per hour with burst of 100
    limiter = TokenBucketRateLimiter(
        event_count=1000,
        time_window=timedelta(hours=1),
        burst=100
    )

    await limiter.wait()  # Wait for rate limit

Redis Sliding Window Rate Limiter

Distributed rate limiting using Redis:

from rate_limiter import RedisSlidingWindowRateLimiter
import redis.asyncio as redis

async def example():
    redis_client = redis.Redis(host='localhost', port=6379)

    # Allow 1000 requests per minute with slack of 10
    limiter = RedisSlidingWindowRateLimiter(
        redis=redis_client,
        event_count=1000,
        time_window=60,
        slack=10
    )

    await limiter.wait()  # Wait for rate limit

Redis Sliding Window API Rate Limiter

Distributed API rate limiting using Redis:

from rate_limiter import RedisSlidingWindowApiRateLimiter
import redis.asyncio as redis

async def example():
    redis_client = redis.Redis(host='localhost', port=6379)

    # Allow 1000 requests per minute per user
    limiter = RedisSlidingWindowApiRateLimiter(
        redis=redis_client,
        event_count=1000,
        time_window=60,
    )

    result, time_remaining = await limiter.check("user-1")
    if not result:
        raise HTTPException(
            status_code=429,
            detail=f"Rate limit exceeded. Try again in {time_remaining} seconds"
        )

Configuration Options

All rate limiters accept these common parameters:

• event_count: Maximum number of events allowed in the time window
• time_window: Time period for the rate limit (accepts int/float seconds or timedelta)

Additional options per implementation:

LeakyBucketRateLimiter

• slack: Additional allowance for brief bursts (default: 10)

TokenBucketRateLimiter

• burst: Maximum burst size (default: 100)

RedisSlidingWindowRateLimiter

• redis: Redis compatible client/interface
• slack: Additional allowance for brief bursts (default: 10)
• key_prefix: Prefix for Redis keys (default: "rate_limiter:")

RedisSlidingWindowApiRateLimiter

• redis: Redis compatible client/interface
• key_prefix: Prefix for Redis keys (default: "rate_limiter:")

Error Handling

The rate limiters raise appropriate exceptions for invalid configurations:

• TypeError: When parameters are of incorrect type
• ValueError: When parameters have invalid values

Performance Considerations

• LeakyBucketRateLimiter: Best for scenarios requiring steady, predictable request rates
• TokenBucketRateLimiter: Efficient for bursty workloads
• RedisSlidingWindowRateLimiter: Suitable for distributed systems, but requires Redis or Redis compatible cache service
• RedisSlidingWindowApiRateLimiter: Suitable for distributed systems, but requires Redis or Redis compatible cache service

License

This project is licensed under the MIT License - see the LICENSE file for details.