yapcache 0.1.8

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yapcache

Yet another Python cache library.

Table of Contents

• Installation
• Usage
• License

Installation

pip install yapcache

Usage

In memory cache:

import asyncio
from yapcache import memoize
from yapcache.caches.memory import InMemoryCache

cache = InMemoryCache(maxsize=1_000, key_prefix=f"example:")


@memoize(cache, ttl=60, cache_key=lambda n: f"slow-{n}")
async def slow_fn(n: int):
    await asyncio.sleep(n)


async def example():
    await slow_fn(3)
    await slow_fn(3)  # cached!


asyncio.run(example())

Redis cache:

# ...
from redis.asyncio.client import Redis
from yapcache.caches.redis import RedisCache


redis_client = Redis()
cache = RedisCache(redis_client, key_prefix=f"example:")

Multi-layer cache:

# ...
from yapcache.caches import MultiLayerCache

redis_client = Redis()

cache = MultiLayerCache(
    [InMemoryCache(maxsize=2_000), RedisCache(redis_client)],
    key_prefix=f"example:",
)

Use lock parameter to protect against thundering herd (only one coroutine/thread will do the work and update the cache):

# ...
from yapcache.distlock import RedisDistLock

@memoize(
    cache,
    ttl=60,
    cache_key=lambda n: f"slow-{n}",
    lock=lambda key: RedisDistLock(redis_client, key),
)
async def slow_fn(n: int):
    # ...

Use best_before to serve stale data (update the cache in background):

@memoize(
    cache,
    ttl=60,
    cache_key=lambda n: f"slow-{n}",
    best_before=lambda n: time.time() + 30
)
async def slow_fn(n: int):
    # ...

License

yapcache is distributed under the terms of the MIT license.