Async caching library with Redis, Memory, L1/L2, AutoSerializer (orjson/msgspec)
Project description
Light Cache
Light Cache é uma biblioteca Python para caching assíncrono com suporte a Redis, memória, L1/L2, decorators fáceis, orjson e msgspec.
Projetada para FastAPI, Granian, ML/BRMS e qualquer aplicação async Python.
🔹 Recursos principais
- Cache assíncrono com múltiplos backends:
- Redis (com senha e TLS)
- Memória local (L1)
- Cache em camadas (LayeredCache: L1 + L2)
- Decorator
@cache_responsepara funções async - Serializadores rápidos:
AutoSerializer(orjson)MsgspecSerializer(msgspec.Struct)
- Dogpile protection (evita múltiplas execuções pesadas)
- TTL com jitter (evita stampede)
- Métricas simples: hits / misses
- Suporta versionamento de chaves (
key_version) - Seguro: falhas no cache não quebram a aplicação
🔹 Instalação
pip install async_cache
Exemplo
import msgspec
from fastapi import FastAPI
import asyncio
import random
import uvicorn
class QuoteResult(msgspec.Struct):
product_id: str
price: float
discount: float
from light_cache.backends import (
MemoryCacheBackend,
RedisCacheBackend,
LayeredCacheBackend,
)
from light_cache.core.decorators import cache_response
from light_cache.core.serializers import MsgspecSerializer
memory_cache = MemoryCacheBackend()
redis_cache = RedisCacheBackend(
redis_url="redis://localhost:6379/0",
prefix="fastapi-demo",
)
cache = LayeredCacheBackend(
l1=memory_cache,
l2=redis_cache,
l1_ttl=2,
)
app = FastAPI(title="Async Cache Demo")
@app.get("/health")
@cache_response(
cache=cache,
key_prefix="health",
ttl=60,
use_lock=False,
)
async def health():
return {
"status": "ok",
"value": random.random(),
}
@app.get("/quote/{product_id}")
@cache_response(
cache=cache,
key_prefix="quote",
ttl=60,
serializer=MsgspecSerializer(),
)
async def calculate_quote(product_id: str):
# simula cálculo pesado
await asyncio.sleep(1)
return QuoteResult(
product_id=product_id,
price=round(random.uniform(100, 500), 2),
discount=round(random.uniform(0, 0.3), 2),
)
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=8000)
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