by memcachier
GitHub Readme.md
This is an example Django app that uses MemCachier to cache algebraic computations.
This example is written with Django 1.8.16. Unless you specifically need an old Django version you should check out a newer example.
You can view a working version of this app here that uses MemCachier on Heroku. Running this app on your local machine in development will work as well, although then you won't be using MemCachier -- you'll be using a local dummy cache. MemCachier is currently only available with various cloud providers.
Setting up MemCachier to work in Django is very easy. You need to make changes to requirements.txt, settings.py, and any app code that you want cached. These changes are covered in detail below.
You can deploy this app yourself to Heroku to play with.
It is best to use the python virtualenv
tool to build locally:
$ virtualenv-2.7 venv
$ source venv/bin/activate
$ pip install -r requirements.txt
$ DEVELOPMENT=1 python manage.py runserver
Then visit http://localhost:8000
to view the app. Alternatively you
can use foreman and gunicorn to run the server locally (after copying
dev.env
to .env
):
$ foreman start
Run the following commands to deploy the app to Heroku:
$ git clone https://github.com/memcachier/examples-django.git
$ cd examples-django
$ heroku create
$ heroku addons:add memcachier:dev
$ git push heroku master:master
$ heroku open
MemCachier has been tested with the pylibmc memcache client, but the default client doesn't support SASL authentication. Run the following commands to install the necessary pips:
$ sudo brew install libmemcached
$ pip install django-pylibmc pylibmc
Don't forget to update your requirements.txt file with these new pips. requirements.txt should have the following two lines:
django-pylibmc==0.6.1
pylibmc==1.5.1
To configure Django to use pylibmc with SASL authentication. You'll also need
to setup your environment, because pylibmc expects different environment
variables than MemCachier provides. Somewhere in your settings.py
file you
should have the following lines:
os.environ['MEMCACHE_SERVERS'] = os.environ.get('MEMCACHIER_SERVERS', '').replace(',', ';')
os.environ['MEMCACHE_USERNAME'] = os.environ.get('MEMCACHIER_USERNAME', '')
os.environ['MEMCACHE_PASSWORD'] = os.environ.get('MEMCACHIER_PASSWORD', '')
CACHES = {
'default': {
# Use pylibmc
'BACKEND': 'django_pylibmc.memcached.PyLibMCCache',
# Use binary memcache protocol (needed for authentication)
'BINARY': True,
# TIMEOUT is not the connection timeout! It's the default expiration
# timeout that should be applied to keys! Setting it to `None`
# disables expiration.
'TIMEOUT': None,
'OPTIONS': {
# Enable faster IO
'tcp_nodelay': True,
# Keep connection alive
'tcp_keepalive': True,
# Timeout settings
'connect_timeout': 2000, # ms
'send_timeout': 750 * 1000, # us
'receive_timeout': 750 * 1000, # us
'_poll_timeout': 2000, # ms
# Better failover
'ketama': True,
'remove_failed': 1,
'retry_timeout': 2,
'dead_timeout': 30,
}
}
}
By default, Django doesn't use persistent connections with memcached. This is a huge performance problem, especially when using SASL authentication as the connection setup is even more expensive than normal.
You can fix this by putting the following code in your wsgi.py
file:
# Fix django closing connection to MemCachier after every request (#11331)
from django.core.cache.backends.memcached import BaseMemcachedCache
BaseMemcachedCache.close = lambda self, **kwargs: None
There is a bug file against Django for this issue (#11331).
In your application, use django.core.cache methods to access MemCachier. A description of the low-level caching API can be found here. All the built-in Django caching tools will work, too.
Take a look at memcachier_algebra/views.py in this repository for an example.
We are happy to receive bug reports, fixes, documentation enhancements, and other improvements.
Please report bugs via the github issue tracker.
Master git repository:
git clone git://github.com/memcachier/examples-django.git
This library is BSD-licensed.