Simple redis cache for Python functions
- Redis 5+
- Python 3.6+
pip install python-redis-cache
from redis import StrictRedis
from redis_cache import RedisCache
client = StrictRedis(host="redis", decode_responses=True)
cache = RedisCache(redis_client=client)
@cache.cache()
def my_func(arg1, arg2):
result = some_expensive_operation()
return result
# Use the function
my_func(1, 2)
# Call it again with the same arguments and it will use cache
my_func(1, 2)
# Invalidate a single value
my_func.invalidate(1, 2)
# Invalidate all values for function
my_func.invalidate_all()
Arguments and return types must be JSON serializable by default. You can override the serializer, but be careful with using Pickle. Make sure you understand the security risks. Pickle should not be used with untrusted values. https://security.stackexchange.com/questions/183966/safely-load-a-pickle-file
- ttl - is based on the time from when it's first inserted in the cache, not based on the last access
- limit - The limit will revoke keys (once it hits the limit) based on FIFO, not based on LRU
RedisCache(redis_client, prefix="rc", serializer=dumps, deserializer=loads)
RedisCache.cache(ttl=None, limit=None, namespace=None)
# Cached function API
# Returns a cached value, if it exists in cache. Saves value in cache if it doesn't exist
cached_func(*args, *kwargs)
# Invalidates a single value
cached_func.invalidate(*args, **kwargs)
# Invalidates all values for cached function
cached_func.invalidate_all()
- prefix - The string to prefix the redis keys with
- serializer/deserializer - functions to convert arguments and return value to a string (user JSON by default)
- ttl - The time in seconds to cache the return value
- namespace - The string namespace of the cache. This is useful for allowing multiple functions to use the same cache. By default its
f'{function.__module__}.{function.__file__}'