# redis-cached
Python cache decorator that uses Redis or KeyDB as storage. This is very handy for replicated apps (e.g. Kubernetes), AWS Lambda functions, and other stateless apps.
Features:
* Function result and kwarg values are [pickled](https://docs.python.org/3/library/pickle.html), so you can work with complex structures like [pydantic](https://docs.pydantic.dev/latest/)'s `BaseModel`
* Prevents multiple simultaneous cache updates when a function is called concurrently and there is no cached value.
* Cache invalidation is available
Limitations:
* Only async functions are supported.
* Only keyword arguments are supported. It will raise an error if you pass non-kwargs while calling your function.
# Installation
```shell
pip install redis_cached
```
# Usage
Basic usage:
```python
import asyncio
from redis_cached import Cache
cache = Cache()
@cache.cached(5)
async def get_user_data(user_id: int):
# expensive API call here
return {'user_id': user_id, 'name': 'John Doe'}
async def main():
user_data = await get_user_data(user_id=1) # result is cached for 5 seconds
# To invalidate the cache for the user with ID 1, pass the same kwargs:
await cache.invalidate_cache('get_user_data', user_id=1)
asyncio.run(main())
```
Optionally, add salt to `cache_key_salt` to avoid clashing with the same-named functions in other modules or other apps that use the same Redis database.
You can also use your custom-configured async Redis instance with the cache.
```python
import asyncio
from redis.asyncio.client import Redis
from redis_cached import Cache
custom_redis = Redis(
host='localhost',
port=6379,
db=0
)
cache = Cache(
cache_key_salt='qhDwh9Y',
redis_=custom_redis
)
@cache.cached(5)
async def get_user_data(user_id: int):
# expensive API call here
return {'user_id': user_id, 'name': 'John Doe'}
async def main():
user_data = await get_user_data(user_id=1) # cached
await cache.invalidate_cache('get_user_data', user_id=1) # invalidated
asyncio.run(main())
```
# Contributing
Contributions are welcome. Please refer to the [maintenance readme](./maintenance/README.md) for more details.
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"description": "# redis-cached\nPython cache decorator that uses Redis or KeyDB as storage. This is very handy for replicated apps (e.g. Kubernetes), AWS Lambda functions, and other stateless apps.\n\nFeatures:\n* Function result and kwarg values are [pickled](https://docs.python.org/3/library/pickle.html), so you can work with complex structures like [pydantic](https://docs.pydantic.dev/latest/)'s `BaseModel`\n* Prevents multiple simultaneous cache updates when a function is called concurrently and there is no cached value.\n* Cache invalidation is available\n\nLimitations:\n* Only async functions are supported.\n* Only keyword arguments are supported. It will raise an error if you pass non-kwargs while calling your function.\n\n# Installation\n\n```shell\npip install redis_cached\n```\n\n# Usage\n\nBasic usage:\n\n```python\nimport asyncio\nfrom redis_cached import Cache\n\ncache = Cache()\n\n@cache.cached(5)\nasync def get_user_data(user_id: int):\n # expensive API call here\n return {'user_id': user_id, 'name': 'John Doe'}\n\nasync def main():\n user_data = await get_user_data(user_id=1) # result is cached for 5 seconds\n \n # To invalidate the cache for the user with ID 1, pass the same kwargs:\n await cache.invalidate_cache('get_user_data', user_id=1)\n\nasyncio.run(main())\n```\n\n\nOptionally, add salt to `cache_key_salt` to avoid clashing with the same-named functions in other modules or other apps that use the same Redis database.\n\nYou can also use your custom-configured async Redis instance with the cache.\n\n```python\nimport asyncio\nfrom redis.asyncio.client import Redis\nfrom redis_cached import Cache\n\ncustom_redis = Redis(\n host='localhost',\n port=6379,\n db=0\n)\ncache = Cache(\n cache_key_salt='qhDwh9Y',\n redis_=custom_redis\n)\n\n@cache.cached(5)\nasync def get_user_data(user_id: int):\n # expensive API call here\n return {'user_id': user_id, 'name': 'John Doe'}\n\nasync def main():\n user_data = await get_user_data(user_id=1) # cached\n await cache.invalidate_cache('get_user_data', user_id=1) # invalidated\n\nasyncio.run(main())\n```\n\n# Contributing\n\nContributions are welcome. Please refer to the [maintenance readme](./maintenance/README.md) for more details.\n",
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