Caching tool for python, working with Redis single instance and Redis cluster mode
Installation
$ pip install cache-house
or with poetry
poetry add cache-house
Quick Start
cache decorator work with async and sync functions
from cache_house.backends.redis_backend import RedisCache
from cache_house.cache import cache
import asyncio
RedisCache.init()
@cache() # default expire time is 180 seconds
async def test_cache(a: int,b: int):
print("async cached")
return [a,b]
@cache()
def test_cache_1(a: int, b: int):
print("cached")
return [a, b]
if __name__ == "__main__":
print(test_cache_1(3,4))
print(asyncio.run(test_cache(1,2)))
Check stored cache key
➜ $ rdcli KEYS "*"
1) cachehouse:main:8f65aed1010f0062a783c83eb430aca0
2) cachehouse:main:f665833ea64e4fc32653df794257ca06
Setup Redis cache instance
You can pass all redis-py arguments to RedisCache.init method and additional arguments :
def RedisCache.init(
host: str = "localhost",
port: int = 6379,
encoder: Callable[..., Any] = ...,
decoder: Callable[..., Any] = ...,
namespace: str = ...,
key_prefix: str = ...,
key_builder: Callable[..., Any] = ...,
password: str = ...,
db: int = ...,
**kwargs
)
or you can set your own encoder and decoder functions
from cache_house.backends.redis_backend import RedisCache
def custom_encoder(data):
return json.dumps(data)
def custom_decoder(data):
return json.loads(data)
RedisCache.init(encoder=custom_encoder, decoder=custom_decoder)
Default encoder and decoder is pickle module.
Setup Redis Cluster cache instance
All manipulation with RedisCache same with a RedisClusterCache
from cache_house.backends.redis_cluster_backend import RedisClusterCache
from cache_house.cache import cache
RedisClusterCache.init()
@cache()
async def test_cache(a: int,b: int):
print("cached")
return [a,b]
def RedisClusterCache.init(
cls,
host="localhost",
port=6379,
encoder: Callable[..., Any] = pickle_encoder,
decoder: Callable[..., Any] = pickle_decoder,
startup_nodes=None,
cluster_error_retry_attempts: int = 3,
require_full_coverage: bool = True,
skip_full_coverage_check: bool = False,
reinitialize_steps: int = 10,
read_from_replicas: bool = False,
namespace: str = DEFAULT_NAMESPACE,
key_prefix: str = DEFAULT_PREFIX,
key_builder: Callable[..., Any] = key_builder,
**kwargs,
)
You can set expire time (seconds) , namespace and key prefix in cache decorator
@cache(expire=30, namespace="app", key_prefix="test")
async def test_cache(a: int,b: int):
print("cached")
return [a,b]
if __name__ == "__main__":
print(asyncio.run(test_cache(1,2)))
Check stored cache
rdcli KEYS "*"
1) test:app:f665833ea64e4fc32653df794257ca06
If your function works with non-standard data types, you can pass custom encoder and decoder functions to the cache decorator.
import asyncio
import json
from cache_house.backends.redis_backend import RedisCache
from cache_house.cache import cache
RedisCache.init()
def custom_encoder(data):
return json.dumps(data)
def custom_decoder(data):
return json.loads(data)
@cache(expire=30, encoder=custom_encoder, decoder=custom_decoder, namespace="custom")
async def test_cache(a: int, b: int):
print("async cached")
return {"a": a, "b": b}
@cache(expire=30)
def test_cache_1(a: int, b: int):
print("cached")
return [a, b]
if __name__ == "__main__":
print(asyncio.run(test_cache(1, 2)))
print(test_cache_1(3, 4))
Check stored cache
rdcli KEYS "*"
1) cachehouse:main:8f65aed1010f0062a783c83eb430aca0
2) cachehouse:custom:f665833ea64e4fc32653df794257ca06
22 Dec 20, 2022
67 Dec 14, 2022
379 Jan 3, 2023
2.1k Dec 31, 2022
2.8k Jan 4, 2023
871 Dec 25, 2022
46 Sep 1, 2022
7 Jan 2, 2023
16 Oct 7, 2022
0 Sep 24, 2022
1 Nov 28, 2021
54 Nov 26, 2022
1 Dec 15, 2021
2 Sep 06, 2021
69 Jan 06, 2023
450 Dec 29, 2022
31 Jan 10, 2023
1.3k Dec 31, 2022
249 Jan 06, 2023
562 Jan 01, 2023
358 Nov 28, 2022
2 Dec 15, 2021
5 Dec 23, 2022
1k Jan 02, 2023
3 Nov 27, 2022
31 Nov 30, 2022
291 Jan 06, 2023