Redis Cache For Python
Project description
Redis cache for Python
- Simple python redis cache library, mostly used for distributed caching, where applications is running on separated processes such as Gunicorn workers, K8s replicas, Cloud, ...
- Asyncio Support for FastAPI, Starlette
Requirements
- Redis 5+
- Python 3.6+
Installation
$ pip install redis-cache-py
Simple usage
from redis_cache_py import RedisCache
# init redis_cache instance and connection
# make sure you have redis running on `127.0.0.1:6379`
redis_cache = RedisCache(
host="127.0.0.1",
port=6379,
)
@redis_cache.cache(ttl=10) # Expire after 10 seconds
def concate_list(a: list, b: list):
print("This function is called")
return a + b
result = concate_list([1, 2, 3], [4, 5, 6])
print(result)
# This function is called
# [1, 2, 3, 4, 5, 6]
# Now result is cached, next time you call this function, result will returned
# from redis
result = concate_list([1, 2, 3], [4, 5, 6])
print(result)
# [1, 2, 3, 4, 5, 6]
Asynchronous with asyncio
import asyncio
from redis_cache_py.asyncio import AsyncRedisCache
# init redis_cache instance and connection
# Make sure you have redis running on `127.0.0.1:6379`
redis_cache = AsyncRedisCache(
host="127.0.0.1",
port=6379,
verbose=1 # Turn on logging for demonstration, set to 0 for silent caching
)
@redis_cache.aio_cache(ttl=10) # Expire after 10 seconds
async def concate_list(a: list, b: list):
print("This function is called")
return a + b
async def test_async_cache():
result = await concate_list([1, 2, 3], [4, 5, 6])
print(result)
# Now the result is cached
result2 = await concate_list([1, 2, 3], [4, 5, 6])
print(result2)
loop = asyncio.get_event_loop()
loop.run_until_complete(test_async_cache())
# Output:
# This function is called
# [1, 2, 3, 4, 5, 6]
# [1, 2, 3, 4, 5, 6]
Advanced usage
for further examples and use cases please visit examples
Testing
NOTE: Please make sure you have redis running on 127.0.0.1:6379
to run test.
$ python3 -m unittest discover tests
Project details
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