Metadata-Version: 2.1
Name: CacheMan
Version: 2.2.0
Summary: A dependent cache manager
Home-page: https://github.com/MSeal/py_cache_manager
Download-URL: https://github.com/MSeal/py_cache_manager/tarball/v2.2.0
Author: Matthew Seal
Author-email: mseal007@gmail.com
License: New BSD
Keywords: tables,data,analysis,extraction
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Utilities
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
License-File: LICENSE
Requires-Dist: psutil (>=2.1.0)

|Build Status|

CacheMan
========

A Python interface for managing dependent caches.

‘Ba-Bop-Ba-Dop-Bop’

Description
-----------

This module acts as a dependency manager for caches and is ideal for
instances where a program has many repeated computations that could be
safely persisted. This usually entails a DB layer to house key value
pairs. However, such a layer is sometimes overkill and managing a DB
along with a project can be more effort than it’s worth. That’s where
CacheMan comes in and provides an interface through which you can define
savers, loaders, builders, and dependencies with disk-based defaults.

By default all caches will auto save when 10k changes occur over 60
seconds, 10 changes occur over 300 seconds (but after 60 seconds), or 1
change occurs within 900 seconds (after 300 seconds). This behavior can
be changed by instantiating an AutoSyncCache from the autosync
submodule.

Dependencies
------------

psutil – for asynchronous cache saving

Features
--------

-  Drop in replacement for local memory dictionaries
-  Default persistent pickle caches
-  Non-persistent caching
-  Cache load/save/delete hooks w/ defaults
-  Cache validation hooks
-  Cache builder hooks
-  Dependent invalidation
-  Auto-Syncing caches

How to use
----------

Below are some simple examples for how to use the repository.

Setting up a simple persistent cache
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

::

   from cacheman import cacher

   manager = cacher.get_cache_manager() # Optional manager name argument can be used here
   cache = manager.register_cache('my_simple_cache') # You now have a cache!
   print cache.get('my_key') # `None` first run, 'my_value' if this code was executed earlier
   cache['my_key'] = 'my_value'
   cache.save() # Changes are now persisted to disk
   manager.save_cache_contents('my_simple_cache') # Alternative way to save a cache

Non-persistent caches
~~~~~~~~~~~~~~~~~~~~~

::

   from cacheman import cacher

   manager = cacher.get_cache_manager()
   cache = manager.register_custom_cache('my_simple_cache', persistent=False) # You cache won't save to disk
   cache.save() # This is a no-op

Registering hooks
~~~~~~~~~~~~~~~~~

::

   from cacheman import cacher
   from cacheman import cachewrap

   def my_saver(cache_name, contents):
       print("Save requested on {} cache content: {}".format(cache_name, contents))

   def my_loader(cache_name):
       return { 'load': 'faked' }

   manager = cacher.get_cache_manager()

   cache = cachewrap.PersistentCache('my_cache', saver=my_saver, loader=my_loader)
   # Can also use manager to set savers/loaders
   #manager.retrieve_cache('my_cache')
   #manager.register_saver('my_cache', my_saver)
   #manager.register_loader('my_cache', my_loader)

   cache.save() # Will print 'Save ... : { 'load': 'faked' }'
   cache['new'] = 'real' # Add something to the cache
   cache.save() # Will print 'Save ... : { 'load': 'faked', 'new': 'real' }'

Dependent caches
~~~~~~~~~~~~~~~~

::

   from cacheman import cacher

   manager = cacher.get_cache_manager()
   edge_cache = manager.retrieve_cache('edge_cache')
   root_cache = manager.register_cache('root_cache')
   manager.register_dependent_cache('root_cache', 'edge_cache')

   def set_processed_value():
       # Computes and caches 'processed' from root's 'raw' value
       processed = edge_cache.get('processed')
       if processed is None:
           processed = (root_cache.get('raw') or 0) * 5
           edge_cache['processed'] = processed
       return processed

   # A common problem with caching computed or dependent values:
   print set_processed_value() # 0 without raw value
   root_cache['raw'] = 1
   print set_processed_value() # still 0 because it's cache in edge

   # Now we use cache invalidation to tell downstream caches they're no longer valid
   root_cache.invalidate() # Invalidates dependent caches
   print edge_cache # Prints {} even though we only invalidated the root_cache
   root_cache['raw'] = 1
   print set_processed_value() # Now 5 because the edge was cleared before the request
   print edge_cache # Can see {'processed': 5} propogated

Setting cache directory
~~~~~~~~~~~~~~~~~~~~~~~

::

   from cacheman import cacher

   # Default cache directory is '/tmp/general_cacher' or 'user\appadata\local\temp\general_cache'
   # All pickle caches now save to namespaced directories within the base_cache_directory directory
   manager = cacher.get_cache_manager(base_cache_directory='secret/cache/location')

   cache = manager.register_cache('my_cache')
   cache['new'] = 'real' # Add something to the cache
   cache.save('my_cache') # Will save contents to 'secret/cache/location/general_cache/my_cache.pkl'

Navigating the Repo
-------------------

.. _cacheman-1:

cacheman
~~~~~~~~

Package wrapper for the repo.

tests
~~~~~

All unit tests for the repo.

Language Preferences
--------------------

-  Google Style Guide
-  Object Oriented (with a few exceptions)

TODO
----

-  Better argument checks
-  Changelog

Author
------

Author(s): Matthew Seal

.. |Build Status| image:: https://travis-ci.org/MSeal/py_cache_manager.svg?branch=master
   :target: https://travis-ci.org/MSeal/py_cache_manager
