Caching¶
When adding an API to your site, it’s important to understand that most consumers of the API will not be people, but instead machines. This means that the traditional “fetch-read-click” cycle is no longer measured in minutes but in seconds or milliseconds.
As such, caching is a very important part of the deployment of your API. Tastypie ships with two classes to make working with caching easier. These caches store at the object level, reducing access time on the database.
However, it’s worth noting that these do NOT cache serialized representations. For heavy traffic, we’d encourage the use of a caching proxy, especially Varnish, as it shines under this kind of usage. It’s far faster than Django views and already neatly handles most situations.
Usage¶
Using these classes is simple. Simply provide them (or your own class) as a
Meta
option to the Resource
in question. For example:
from django.contrib.auth.models import User
from tastypie.cache import SimpleCache
from tastypie.resources import ModelResource
class UserResource(ModelResource):
class Meta:
queryset = User.objects.all()
resource_name = 'auth/user'
excludes = ['email', 'password', 'is_superuser']
# Add it here.
cache = SimpleCache()
Caching Options¶
Tastypie ships with the following Cache
classes:
NoCache
¶
The no-op cache option, this does no caching but serves as an api-compatible plug. Very useful for development.
SimpleCache
¶
This option does basic object caching, attempting to find the object in the
cache & writing the object to the cache. It uses Django’s current
CACHE_BACKEND
to store cached data.
Implementing Your Own Cache¶
Implementing your own Cache
class is as simple as subclassing NoCache
and overriding the get
& set
methods. For example, a json-backed
cache might look like:
import json
from django.conf import settings
from tastypie.cache import NoCache
class JSONCache(NoCache):
def _load(self):
data_file = open(settings.TASTYPIE_JSON_CACHE, 'r')
return json.load(data_file)
def _save(self, data):
data_file = open(settings.TASTYPIE_JSON_CACHE, 'w')
return json.dump(data, data_file)
def get(self, key):
data = self._load()
return data.get(key, None)
def set(self, key, value, timeout=60):
data = self._load()
data[key] = value
self._save(data)
Note that this is NOT necessarily an optimal solution, but is simply
demonstrating how one might go about implementing your own Cache
.