pyappcache
==========
Pyappcache is a library to make it easier to use application-level
caching in Python.
- Allows putting arbitrary Python objects into the cache
- Uses PEP484 type hints to help you typecheck cache return values
- Supports Memcache, Redis and SQLite
- Supports working as a "read-through" and "write-through" cache
- Native support for key `"namespacing" <https://github.com/memcached/memcached/wiki/ProgrammingTricks#namespacing>`__
- Provides a few handy extras
- A plugin for the
`cachecontrol <https://pypi.org/project/CacheControl/>`__ library
so you can also use it as an HTTP cache with
`requests <https://pypi.org/project/requests/>`__
A simple example
----------------
.. code:: python
from datetime import date
from pyappcache.redis import RedisCache
from pyappcache.keys import Key, SimpleStringKey
cache = RedisCache()
# Annotate the type here to let mypy know this key is used for dates
key: Key[date] = SimpleStringKey("mifid start date")
cache.set(key, date(2018, 1, 3), ttl_seconds=3600)
... # later...
# This variable's type will be inferred as datetime.date
special_date = cache.get(key)
How it compares to alternatives
-------------------------------
Using the redis/memcache/sqlite client directly
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
- Explicit key objects allow for type inference and encapsulation of keying
- Keys are prefix to help prevent collisions
- Optional, pluggable, compression
- Hopefully the overhead is small (not yet tested!)
- Portable between redis/memcache/sqlite, etc
dogpile.cache
~~~~~~~~~~~~~
- Explicit key objects allow for type inference and encapsulation of keying
- dogpile.cache provides locking, pyappcache does not
- Reduced temptation to use the problematic decorator pattern
- This often causes import order problems as you need to have your cache at import time
- Pyappache doesn't provide DBM/file backends, SQLite instead
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