Metadata-Version: 2.1
Name: async-rediscache
Version: 0.1.3
Summary: An easy to use asynchronous Redis cache
Home-page: https://github.com/python-discord/async-rediscache
Author: Python Discord
Author-email: staff@pythondiscord.com
License: MIT
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`](https://redis.io/download) 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:
        
        ```bash
        pip install async-rediscache
        ```
        
        Alternatively, to install `async-rediscache` with `fakeredis` run:
        
        ```bash
        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](https://docs.aiohttp.org/en/stable/faq.html#why-is-creating-a-clientsession-outside-of-an-event-loop-dangerous) for why).
        
        ```python
        import async_rediscache
        
        async def main():
            session = async_rediscache.RedisSession()
            await session.connect()
        
            # Do something interesting
            
            await session.close()
        ```
        
        ### `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:
        
        ```python
        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:
        
        ```python
        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:
        
        ```python
        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`. 
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 4 - Beta
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Framework :: AsyncIO
Classifier: Topic :: Database
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: ~=3.7
Description-Content-Type: text/markdown
Provides-Extra: fakeredis
