pyappcache

Pyappcache is a library to make it easier to use application-level caching in Python.

• Allows putting arbitrary Python objects into the cache

  • And provides type hints so you can typecheck what you get back from the cache

• 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-hypernode.com/project/CacheControl/>__ library so you can also use it as an HTTP cache with requests <https://pypi-hypernode.com/project/requests/>__

A simple example

.. code:: python

from datetime import date

import redis
from pyappcache.redis import RedisCache
from pyappcache.keys import Key, GenericStringKey

client = redis.Redis()
cache = RedisCache(client)

# Annotate the type here to let mypy know this key is used for dates
key: Key[date] = GenericStringKey("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
- Key prefixing
- Optional 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
- As yet there is no locking in pyappcache
- Reduced temptation to use the problematic decorator pattern
  - This often causes import order problems as you need to have your cache at import time
- SQLite backend instead of DBM/file backends