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Django cache backend for Amazon ElastiCache (memcached)

Project description

Simple Django cache backend for Amazon ElastiCache (memcached based). It uses pylibmc and setup connection to each node in cluster using auto discovery function.

Requirements

  • pylibmc
  • Django 1.3+.

It was written and tested on Python 2.7.

Installation

Get it from pypi:

pip install django-pylibmc

or github:

pip install -e git://github.com/gusdan/django-elasticache.git#egg=django-elasticache

Usage

Your cache backend should look something like this:

CACHES = {
    'default': {
        'BACKEND': 'django_elasticache.memcached.ElastiCache',
        'LOCATION': 'cache-c.drtgf.cfg.use1.cache.amazonaws.com:11211',
    }
}

By the first call to cache it connects to cluster (using LOCATION param), gets list of all nodes and setup pylibmc client using full list of nodes. As result your cache will work with all nodes in cluster and automatically detect new nodes in cluster. List of nodes are stored in class-level cached, so any changes in cluster take affect only after restart of working process. But if you’re using gunicorn or mod_wsgi you usually have max_request settings which restart process after some count of processed requests, so auto discovery will work fine.

Django-elasticache changes default pylibmc params to increase performance.

Testing

Run the tests like this:

nosetest

Project details


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