An easy to use asynchronous Redis cache
Project description
Asynchronous Redis Cache
This package offers several data types to ease working with a Redis cache in an asynchronous workflow. The package is currently in development and it's not recommended to start using it in production at this point.
Installation
Prerequisites
To use async-rediscache
, make sure that redis
is installed and running on your system. Alternatively, you could use fakeredis
as a back-end for testing purposes and local development.
Install using pip
To install async-rediscache
run the following command:
pip install async-rediscache
Alternatively, to install async-rediscache
with fakeredis
run:
pip install async-rediscache[fakeredis]
Basic use
Creating a RedisSession
To use a RedisCache
, you first have to create a RedisSession
instance that manages the connection pool to Redis. You can create the RedisSession
at any point but make sure to call the connect
method from an asynchronous context (see this explanation for why).
import async_rediscache
async def main():
session = async_rediscache.RedisSession()
await session.connect()
# Do something interesting
await session.close()
Creating a RedisSession
with a network connection
async def main():
connection = {"address": "redis://127.0.0.1:6379"}
async_rediscache.RedisSession(**connection)
RedisCache
A RedisCache
is the most basic data type provided by async-rediscache
. It works like a dictionary in that you can associate keys with values. To prevent key collisions, each RedisCache
instance should use a unique namespace
identifier that will be prepended to the key when storing the pair to Redis.
Creating a RedisCache
instance
When creating a RedisCache
instance, it's important to make sure that it has a unique namespace
. This can be done directly by passing a namespace
keyword argument to the constructor:
import async_rediscache
birthday_cache = async_rediscache.RedisCache(namespace="birthday")
Alternatively, if you assign a class attribute to a RedisCache
instance, a namespace will be automatically generated using the name of the owner class and the name of attribute assigned to the cache:
import async_rediscache
class Channel:
topics = async_rediscache.RedisCache() # The namespace be set to `"Channel.topics"`
Note: There is nothing preventing you from reusing the same namespace, although you should be aware this could lead to key collisions (i.e., one cache could interfere with the values another cache has stored).
Using a RedisCache
instance
Using a RedisCache
is straightforward: Just call and await the methods you want to use and it should just work. There's no need to pass a RedisSession
around as the session is fetched internally by the RedisCache
. Obviously, one restriction is that you have to make sure that the RedisSession
is still open and connected when trying to use a RedisCache
.
Here are some usage examples:
import async_rediscache
async def main():
session = async_rediscache.RedisSession()
await session.connect()
cache = async_rediscache.RedisCache(namespace="python")
# Simple key/value manipulation
await cache.set("Guido", "van Rossum")
print(await cache.get("Guido")) # Would print `van Rossum`
# A contains check works as well
print(await cache.contains("Guido")) # True
print(await cache.contains("Kyle")) # False
# You can iterate over all key, value pairs as well:
item_view = await cache.items()
for key, value in item_view:
print(key, value)
# Other options:
number_of_pairs = await cache.length()
pairs_in_dict = await cache.to_dict()
popped_item = await cache.pop("Raymond", "Default value")
await cache.update({"Brett": 10, "Barry": False})
await cache.delete("Barry")
await cache.increment("Brett", 1) # Increment Brett's int by 1
await cache.clear()
await session.close()
RedisQueue
A RedisQueue
implements the same interface as a queue.SimpleQueue
object, except that all the methods are coroutines. Creating an instance works the same as with a RedisCache
.
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