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