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A library for application-level caching

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