A Python async rate limiter using Redis and Lua with sliding window algorithm. Supports retries, exponential backoff, and optional exception handling.
Project description
Async Rate Limiter (Sliding Window + Lua + Redis)
A Python async rate limiter using Redis and Lua with sliding window algorithm.
Supports retries, exponential backoff, and optional exception handling.
Installation
pip install redis asyncio
Usage
Basic usage with inline function
import asyncio
import redis.asyncio as aioredis
from rate_limit_module import RateLimit # replace with your module
from rate_limiter.exceptions import RetryLimitReached
redis_client = aioredis.Redis(host='localhost', port=6379, db=0)
rate_limit = RateLimit(
redis=redis_client,
limit=5,
window=10,
retries=3,
backoff_ms=200,
backoff_factor=2.0,
retry_on_exceptions=(ValueError,),
)
async def my_task():
print('Task executed.')
return 42
wrapped = rate_limit(fn=my_task, key='task_key')
try:
result = await wrapped()
print(result)
except RetryLimitReached:
print('All retry attempts exhausted.')
Using as a decorator
rate_limit = RateLimit(
redis=redis_client,
limit=3,
window=5,
retries=4,
backoff_ms=100,
backoff_factor=1.5,
)
@rate_limit(key='decorated_task')
async def my_decorated_task():
print('Decorated task executed.')
return 'done'
try:
await my_decorated_task()
except RetryLimitReached:
print('Rate limit retry attempts exhausted.')
Exception behavior
After all retries are used without success, the limiter raises RetryLimitReached exception
instead—making it easier to handle failure explicitly in your code.
Features
- Sliding window rate limiting using Redis + Lua
- Async-friendly
- Retries with exponential backoff configurable
- Optional exception-based retry logic
- Raises
RetryLimitReachedwhen retry attempts are exhausted - Supports both inline wrapper and decorator syntax
License
MIT License
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