https://github.com/calpaterson/pyappcache

A library for application-level caching
https://github.com/calpaterson/pyappcache

cache library

Last synced: 12 months ago
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A library for application-level caching

• Host: GitHub
• URL: https://github.com/calpaterson/pyappcache
• Owner: calpaterson
• License: gpl-3.0
• Created: 2020-06-15T16:34:18.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2024-04-05T10:45:28.000Z (about 2 years ago)
• Last Synced: 2025-03-22T18:03:53.410Z (over 1 year ago)
• Topics: cache, library
• Language: Python
• Homepage: https://pyappcache.readthedocs.io/en/latest/
• Size: 159 KB
• Stars: 21
• Watchers: 3
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.rst
  • Changelog: CHANGELOG.md
  • License: COPYING

Awesome Lists containing this project

README

          
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" `__

-  Provides a few handy extras

   -  A plugin for the

      `cachecontrol `__ library

      so you can also use it as an HTTP cache with

      `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