django/docs/topics/cache.txt

========================
Django's cache framework
========================

A fundamental trade-off in dynamic Web sites is, well, they're dynamic. Each
time a user requests a page, the Web server makes all sorts of calculations --
from database queries to template rendering to business logic -- to create the
page that your site's visitor sees. This is a lot more expensive, from a
processing-overhead perspective, than your standard
read-a-file-off-the-filesystem server arrangement.

For most Web applications, this overhead isn't a big deal. Most Web
applications aren't washingtonpost.com or slashdot.org; they're simply small-
to medium-sized sites with so-so traffic. But for medium- to high-traffic
sites, it's essential to cut as much overhead as possible.

That's where caching comes in.

To cache something is to save the result of an expensive calculation so that
you don't have to perform the calculation next time. Here's some pseudocode
explaining how this would work for a dynamically generated Web page::

    given a URL, try finding that page in the cache
    if the page is in the cache:
        return the cached page
    else:
        generate the page
        save the generated page in the cache (for next time)
        return the generated page

Django comes with a robust cache system that lets you save dynamic pages so
they don't have to be calculated for each request. For convenience, Django
offers different levels of cache granularity: You can cache the output of
specific views, you can cache only the pieces that are difficult to produce,
or you can cache your entire site.

Django also works well with "upstream" caches, such as `Squid
<http://www.squid-cache.org>`_ and browser-based caches. These are the types of
caches that you don't directly control but to which you can provide hints (via
HTTP headers) about which parts of your site should be cached, and how.

Setting up the cache
====================

The cache system requires a small amount of setup. Namely, you have to tell it
where your cached data should live -- whether in a database, on the filesystem
or directly in memory. This is an important decision that affects your cache's
performance; yes, some cache types are faster than others.

Your cache preference goes in the :setting:`CACHES` setting in your
settings file. Here's an explanation of all available values for
:setting:`CACHES`.

.. versionchanged:: 1.3
    The settings used to configure caching changed in Django 1.3. In
    Django 1.2 and earlier, you used a single string-based
    :setting:`CACHE_BACKEND` setting to configure caches. This has
    been replaced with the new dictionary-based :setting:`CACHES`
    setting.

Memcached
---------

By far the fastest, most efficient type of cache available to Django, Memcached
is an entirely memory-based cache framework originally developed to handle high
loads at LiveJournal.com and subsequently open-sourced by Danga Interactive.
It's used by sites such as Facebook and Wikipedia to reduce database access and
dramatically increase site performance.

Memcached is available for free at http://memcached.org/. It runs as a
daemon and is allotted a specified amount of RAM. All it does is provide a
fast interface for adding, retrieving and deleting arbitrary data in the cache.
All data is stored directly in memory, so there's no overhead of database or
filesystem usage.

After installing Memcached itself, you'll need to install a memcached
binding. There are several python memcached bindings available; the
two most common are `python-memcached`_ and `pylibmc`_.

.. _`python-memcached`: ftp://ftp.tummy.com/pub/python-memcached/
.. _`pylibmc`: http://sendapatch.se/projects/pylibmc/

.. versionchanged:: 1.2
    In Django 1.0 and 1.1, you could also use ``cmemcache`` as a binding.
    However, support for this library was deprecated in 1.2 due to
    a lack of maintenance on the ``cmemcache`` library itself. Support for
    ``cmemcache`` will be removed completely in Django 1.4.

.. versionchanged:: 1.3
    Support for ``pylibmc`` was added.

To use Memcached with Django:

    * Set :setting:`BACKEND <CACHES-BACKEND>` to
      ``django.core.cache.backends.memcached.MemcachedCache`` or
      ``django.core.cache.backends.memcached.PyLibMCCache`` (depending
      on your chosen memcached binding)

    * Set :setting:`LOCATION <CACHES-LOCATION>` to ``ip:port`` values,
      where ``ip`` is the IP address of the Memcached daemon and
      ``port`` is the port on which Memcached is running.

In this example, Memcached is running on localhost (127.0.0.1) port 11211, using
the ``python-memcached`` binding::

    CACHES = {
        'default': {
            'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
            'LOCATION': '127.0.0.1:11211',
        }
    }

One excellent feature of Memcached is its ability to share cache over multiple
servers. This means you can run Memcached daemons on multiple machines, and the
program will treat the group of machines as a *single* cache, without the need
to duplicate cache values on each machine. To take advantage of this feature,
include all server addresses in :setting:`BACKEND <CACHES-BACKEND>`, either
separated by semicolons or as a list.

In this example, the cache is shared over Memcached instances running on IP
address 172.19.26.240 and 172.19.26.242, both on port 11211::

    CACHES = {
        'default': {
            'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
            'LOCATION': [
                '172.19.26.240:11211',
                '172.19.26.242:11211',
            ]
        }
    }

In the following example, the cache is shared over Memcached instances running
on the IP addresses 172.19.26.240 (port 11211), 172.19.26.242 (port 11212), and
172.19.26.244 (port 11213)::

    CACHES = {
        'default': {
            'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
            'LOCATION': [
                '172.19.26.240:11211',
                '172.19.26.242:11211',
                '172.19.26.244:11213',
            ]
        }
    }

A final point about Memcached is that memory-based caching has one
disadvantage: Because the cached data is stored in memory, the data will be
lost if your server crashes. Clearly, memory isn't intended for permanent data
storage, so don't rely on memory-based caching as your only data storage.
Without a doubt, *none* of the Django caching backends should be used for
permanent storage -- they're all intended to be solutions for caching, not
storage -- but we point this out here because memory-based caching is
particularly temporary.

Database caching
----------------

To use a database table as your cache backend, first create a cache table in
your database by running this command::

    python manage.py createcachetable [cache_table_name]

...where ``[cache_table_name]`` is the name of the database table to create.
(This name can be whatever you want, as long as it's a valid table name that's
not already being used in your database.) This command creates a single table
in your database that is in the proper format that Django's database-cache
system expects.

Once you've created that database table, set your
:setting:`BACKEND <CACHES-BACKEND>` setting to
``"django.core.cache.backends.db.DatabaseCache"``, and
:setting:`LOCATION <CACHES-LOCATION>` to ``tablename`` -- the name of the
database table. In this example, the cache table's name is ``my_cache_table``::

    CACHES = {
        'default': {
            'BACKEND': 'django.core.cache.backends.db.DatabaseCache',
            'LOCATION': 'my_cache_table',
        }
    }


The database caching backend uses the same database as specified in your
settings file. You can't use a different database backend for your cache table.

Database caching works best if you've got a fast, well-indexed database server.

Database caching and multiple databases
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

If you use database caching with multiple databases, you'll also need
to set up routing instructions for your database cache table. For the
purposes of routing, the database cache table appears as a model named
``CacheEntry``, in an application named ``django_cache``. This model
won't appear in the models cache, but the model details can be used
for routing purposes.

For example, the following router would direct all cache read
operations to ``cache_slave``, and all write operations to
``cache_master``. The cache table will only be synchronized onto
``cache_master``::

    class CacheRouter(object):
        """A router to control all database cache operations"""

        def db_for_read(self, model, **hints):
            "All cache read operations go to the slave"
            if model._meta.app_label in ('django_cache',):
                return 'cache_slave'
            return None

        def db_for_write(self, model, **hints):
            "All cache write operations go to master"
            if model._meta.app_label in ('django_cache',):
                return 'cache_master'
            return None

        def allow_syncdb(self, db, model):
            "Only synchronize the cache model on master"
            if model._meta.app_label in ('django_cache',):
                return db == 'cache_master'
            return None

If you don't specify routing directions for the database cache model,
the cache backend will use the ``default`` database.

Of course, if you don't use the database cache backend, you don't need
to worry about providing routing instructions for the database cache
model.

Filesystem caching
------------------

To store cached items on a filesystem, use
``"django.core.cache.backends.filebased.FileBasedCache"`` for
:setting:`BACKEND <CACHES-BACKEND>`. For example, to store cached data in
``/var/tmp/django_cache``, use this setting::

    CACHES = {
        'default': {
            'BACKEND': 'django.core.cache.backends.filebased.FileBasedCache',
            'LOCATION': '/var/tmp/django_cache',
        }
    }


If you're on Windows, put the drive letter at the beginning of the path,
like this::

    CACHES = {
        'default': {
            'BACKEND': 'django.core.cache.backends.filebased.FileBasedCache',
            'LOCATION': 'c:/foo/bar',
        }
    }

The directory path should be absolute -- that is, it should start at the root
of your filesystem. It doesn't matter whether you put a slash at the end of the
setting.

Make sure the directory pointed-to by this setting exists and is readable and
writable by the system user under which your Web server runs. Continuing the
above example, if your server runs as the user ``apache``, make sure the
directory ``/var/tmp/django_cache`` exists and is readable and writable by the
user ``apache``.

Each cache value will be stored as a separate file whose contents are the
cache data saved in a serialized ("pickled") format, using Python's ``pickle``
module. Each file's name is the cache key, escaped for safe filesystem use.

Local-memory caching
--------------------

If you want the speed advantages of in-memory caching but don't have the
capability of running Memcached, consider the local-memory cache backend. This
cache is multi-process and thread-safe. To use it, set
:setting:`BACKEND <CACHES-BACKEND>` to
``"django.core.cache.backends.locmem.LocMemCache"``. For example::

    CACHES = {
        'default': {
            'BACKEND': 'django.core.cache.backends.locmem.LocMemCache',
            'LOCATION': 'unique-snowflake'
        }
    }

The cache :setting:`LOCATION <CACHES-LOCATION>` is used to identify individual
memory stores. If you only have one locmem cache, you can omit the
:setting:`LOCATION <CACHES-LOCATION>`; however, if you have more that one local
memory cache, you will need to assign a name to at least one of them in
order to keep them separate.

Note that each process will have its own private cache instance, which means no
cross-process caching is possible. This obviously also means the local memory
cache isn't particularly memory-efficient, so it's probably not a good choice
for production environments. It's nice for development.

Dummy caching (for development)
-------------------------------

Finally, Django comes with a "dummy" cache that doesn't actually cache -- it
just implements the cache interface without doing anything.

This is useful if you have a production site that uses heavy-duty caching in
various places but a development/test environment where you don't want to cache
and don't want to have to change your code to special-case the latter. To
activate dummy caching, set :setting:`BACKEND <CACHES-BACKEND>` like so::

    CACHES = {
        'default': {
            'BACKEND': 'django.core.cache.backends.dummy.DummyCache',
        }
    }

Using a custom cache backend
----------------------------

While Django includes support for a number of cache backends out-of-the-box,
sometimes you might want to use a customized cache backend. To use an external
cache backend with Django, use the Python import path as the
:setting:`BACKEND <CACHES-BACKEND>` of the :setting:`CACHES` setting, like so::

    CACHES = {
        'default': {
            'BACKEND': 'path.to.backend',
        }
    }

If you're building your own backend, you can use the standard cache backends
as reference implementations. You'll find the code in the
``django/core/cache/backends/`` directory of the Django source.

Note: Without a really compelling reason, such as a host that doesn't support
them, you should stick to the cache backends included with Django. They've
been well-tested and are easy to use.

Cache arguments
---------------

In addition to the defining the engine and name of the each cache
backend, each cache backend can be given additional arguments to
control caching behavior. These arguments are provided as additional
keys in the :setting:`CACHES` setting. Valid arguments are as follows:

    * :setting:`TIMEOUT <CACHES-TIMEOUT>`: The default timeout, in
      seconds, to use for the cache. This argument defaults to 300
      seconds (5 minutes).

    * :setting:`OPTIONS <CACHES-OPTIONS>`: Any options that should be
      passed to cache backend. The list options understood by each
      backend vary with each backend.

      Cache backends that implement their own culling strategy (i.e.,
      the ``locmem``, ``filesystem`` and ``database`` backends) will
      honor the following options:

        * ``MAX_ENTRIES``: the maximum number of entries allowed in
          the cache before old values are deleted. This argument
          defaults to ``300``.

        * ``CULL_FREQUENCY``: The fraction of entries that are culled
          when ``MAX_ENTRIES`` is reached. The actual ratio is
          ``1/CULL_FREQUENCY``, so set ``CULL_FREQUENCY``: to ``2`` to
          cull half of the entries when ``MAX_ENTRIES`` is reached.

          A value of ``0`` for ``CULL_FREQUENCY`` means that the
          entire cache will be dumped when ``MAX_ENTRIES`` is reached.
          This makes culling *much* faster at the expense of more
          cache misses.

      Cache backends backed by a third-party library will pass their
      options directly to the underlying cache library. As a result,
      the list of valid options depends on the library in use.

    * :setting:`KEY_PREFIX <CACHES-KEY_PREFIX>`: A string that will be
      automatically included (prepended by default) to all cache keys
      used by the Django server.

      See the :ref:`cache documentation <cache_key_prefixing>` for
      more information.

    * :setting:`VERSION <CACHES-VERSION>`: The default version number
      for cache keys generated by the Django server.

      See the :ref:`cache documentation <cache_versioning>` for more
      information.

    * :setting:`KEY_FUNCTION <CACHES-KEY_FUNCTION>`
      A string containing a dotted path to a function that defines how
      to compose a prefix, version and key into a final cache key.

      See the :ref:`cache documentation <cache_key_transformation>`
      for more information.

In this example, a filesystem backend is being configured with a timeout
of 60 seconds, and a maximum capacity of 1000 items::

    CACHES = {
        'default': {
            'BACKEND': 'django.core.cache.backends.filebased.FileCache',
            'LOCATION': '127.0.0.1:11211',
            'TIMEOUT': 60,
            'OPTIONS': {
                'MAX_ENTRIES': 1000
            }
        }
    }

Invalid arguments are silently ignored, as are invalid values of known
arguments.

The per-site cache
==================

Once the cache is set up, the simplest way to use caching is to cache your
entire site. You'll need to add
``'django.middleware.cache.UpdateCacheMiddleware'`` and
``'django.middleware.cache.FetchFromCacheMiddleware'`` to your
``MIDDLEWARE_CLASSES`` setting, as in this example::

    MIDDLEWARE_CLASSES = (
        'django.middleware.cache.UpdateCacheMiddleware',
        'django.middleware.common.CommonMiddleware',
        'django.middleware.cache.FetchFromCacheMiddleware',
    )

.. note::

    No, that's not a typo: the "update" middleware must be first in the list,
    and the "fetch" middleware must be last. The details are a bit obscure, but
    see `Order of MIDDLEWARE_CLASSES`_ below if you'd like the full story.

Then, add the following required settings to your Django settings file:

* :setting:`CACHE_MIDDLEWARE_ALIAS` -- The cache alias to use for storage.
* :setting:`CACHE_MIDDLEWARE_SECONDS` -- The number of seconds each page should
  be cached.
* :setting:`CACHE_MIDDLEWARE_KEY_PREFIX` -- If the cache is shared across
  multiple sites using the same Django installation, set this to the name of
  the site, or some other string that is unique to this Django instance, to
  prevent key collisions. Use an empty string if you don't care.

The cache middleware caches every page that doesn't have GET or POST
parameters. Optionally, if the :setting:`CACHE_MIDDLEWARE_ANONYMOUS_ONLY`
setting is ``True``, only anonymous requests (i.e., not those made by a
logged-in user) will be cached. This is a simple and effective way of disabling
caching for any user-specific pages (include Django's admin interface). Note
that if you use :setting:`CACHE_MIDDLEWARE_ANONYMOUS_ONLY`, you should make
sure you've activated ``AuthenticationMiddleware``. The cache middleware
expects that a HEAD request is answered with the same response headers as
the corresponding GET request; in which case it can return a cached GET
response for HEAD request.

Additionally, the cache middleware automatically sets a few headers in each
:class:`~django.http.HttpResponse`:

    * Sets the ``Last-Modified`` header to the current date/time when a fresh
      (uncached) version of the page is requested.

    * Sets the ``Expires`` header to the current date/time plus the defined
      :setting:`CACHE_MIDDLEWARE_SECONDS`.

    * Sets the ``Cache-Control`` header to give a max age for the page --
      again, from the :setting:`CACHE_MIDDLEWARE_SECONDS` setting.

See :doc:`/topics/http/middleware` for more on middleware.

If a view sets its own cache expiry time (i.e. it has a ``max-age`` section in
its ``Cache-Control`` header) then the page will be cached until the expiry
time, rather than :setting:`CACHE_MIDDLEWARE_SECONDS`. Using the decorators in
``django.views.decorators.cache`` you can easily set a view's expiry time
(using the ``cache_control`` decorator) or disable caching for a view (using
the ``never_cache`` decorator). See the `using other headers`__ section for
more on these decorators.

.. _i18n-cache-key:

.. versionadded:: 1.2

If :setting:`USE_I18N` is set to ``True`` then the generated cache key will
include the name of the active :term:`language<language code>`.
This allows you to easily cache multilingual sites without having to create
the cache key yourself.

See :doc:`/topics/i18n/deployment` for more on how Django discovers the active
language.

__ `Controlling cache: Using other headers`_

The per-view cache
==================

.. function ``django.views.decorators.cache.cache_page``

A more granular way to use the caching framework is by caching the output of
individual views. ``django.views.decorators.cache`` defines a ``cache_page``
decorator that will automatically cache the view's response for you. It's easy
to use::

    from django.views.decorators.cache import cache_page

    @cache_page(60 * 15)
    def my_view(request):
        ...

``cache_page`` takes a single argument: the cache timeout, in seconds. In the
above example, the result of the ``my_view()`` view will be cached for 15
minutes. (Note that we've written it as ``60 * 15`` for the purpose of
readability. ``60 * 15`` will be evaluated to ``900`` -- that is, 15 minutes
multiplied by 60 seconds per minute.)

The per-view cache, like the per-site cache, is keyed off of the URL. If
multiple URLs point at the same view, each URL will be cached separately.
Continuing the ``my_view`` example, if your URLconf looks like this::

    urlpatterns = ('',
        (r'^foo/(\d{1,2})/$', my_view),
    )

then requests to ``/foo/1/`` and ``/foo/23/`` will be cached separately, as
you may expect. But once a particular URL (e.g., ``/foo/23/``) has been
requested, subsequent requests to that URL will use the cache.

``cache_page`` can also take an optional keyword argument, ``cache``,
which directs the decorator to use a specific cache alias when caching view
results. By default, the ``default`` alias will be used, but you can specify
any cache alias you want::

    @cache_page(60 * 15, cache="special_cache")
    def my_view(request):
        ...

You can also override the cache prefix on a per-view basis. ``cache_page``
takes an optional keyword argument, ``key_prefix``,
which works in the same way as the :setting:`CACHE_MIDDLEWARE_KEY_PREFIX`
setting for the middleware.  It can be used like this::

    @cache_page(60 * 15, key_prefix="site1")
    def my_view(request):
        ...

The two settings can also be combined. If you specify a ``cache`` *and*
a ``key_prefix``, you will get all the settings of the requested cache
alias, but with the key_prefix overridden.

Specifying per-view cache in the URLconf
----------------------------------------

The examples in the previous section have hard-coded the fact that the view is
cached, because ``cache_page`` alters the ``my_view`` function in place. This
approach couples your view to the cache system, which is not ideal for several
reasons. For instance, you might want to reuse the view functions on another,
cache-less site, or you might want to distribute the views to people who might
want to use them without being cached. The solution to these problems is to
specify the per-view cache in the URLconf rather than next to the view functions
themselves.

Doing so is easy: simply wrap the view function with ``cache_page`` when you
refer to it in the URLconf. Here's the old URLconf from earlier::

    urlpatterns = ('',
        (r'^foo/(\d{1,2})/$', my_view),
    )

Here's the same thing, with ``my_view`` wrapped in ``cache_page``::

    from django.views.decorators.cache import cache_page

    urlpatterns = ('',
        (r'^foo/(\d{1,2})/$', cache_page(my_view, 60 * 15)),
    )

If you take this approach, don't forget to import ``cache_page`` within your
URLconf.

Template fragment caching
=========================

If you're after even more control, you can also cache template fragments using
the ``cache`` template tag. To give your template access to this tag, put
``{% load cache %}`` near the top of your template.

The ``{% cache %}`` template tag caches the contents of the block for a given
amount of time. It takes at least two arguments: the cache timeout, in seconds,
and the name to give the cache fragment. For example:

.. code-block:: html+django

    {% load cache %}
    {% cache 500 sidebar %}
        .. sidebar ..
    {% endcache %}

Sometimes you might want to cache multiple copies of a fragment depending on
some dynamic data that appears inside the fragment. For example, you might want a
separate cached copy of the sidebar used in the previous example for every user
of your site. Do this by passing additional arguments to the ``{% cache %}``
template tag to uniquely identify the cache fragment:

.. code-block:: html+django

    {% load cache %}
    {% cache 500 sidebar request.user.username %}
        .. sidebar for logged in user ..
    {% endcache %}

It's perfectly fine to specify more than one argument to identify the fragment.
Simply pass as many arguments to ``{% cache %}`` as you need.

If :setting:`USE_I18N` is set to ``True`` the per-site middleware cache will
:ref:`respect the active language<i18n-cache-key>`. For the ``cache`` template
tag you could use one of the
:ref:`translation-specific variables<template-translation-vars>` available in
templates to archieve the same result:

.. code-block:: html+django

    {% load i18n %}
    {% load cache %}

    {% get_current_language as LANGUAGE_CODE %}

    {% cache 600 welcome LANGUAGE_CODE %}
        {% trans "Welcome to example.com" %}
    {% endcache %}

The cache timeout can be a template variable, as long as the template variable
resolves to an integer value. For example, if the template variable
``my_timeout`` is set to the value ``600``, then the following two examples are
equivalent:

.. code-block:: html+django

    {% cache 600 sidebar %} ... {% endcache %}
    {% cache my_timeout sidebar %} ... {% endcache %}

This feature is useful in avoiding repetition in templates. You can set the
timeout in a variable, in one place, and just reuse that value.

The low-level cache API
=======================

.. highlight:: python

Sometimes, caching an entire rendered page doesn't gain you very much and is,
in fact, inconvenient overkill.

Perhaps, for instance, your site includes a view whose results depend on
several expensive queries, the results of which change at different intervals.
In this case, it would not be ideal to use the full-page caching that the
per-site or per-view cache strategies offer, because you wouldn't want to
cache the entire result (since some of the data changes often), but you'd still
want to cache the results that rarely change.

For cases like this, Django exposes a simple, low-level cache API. You can use
this API to store objects in the cache with any level of granularity you like.
You can cache any Python object that can be pickled safely: strings,
dictionaries, lists of model objects, and so forth. (Most common Python objects
can be pickled; refer to the Python documentation for more information about
pickling.)

The cache module, ``django.core.cache``, has a ``cache`` object that's
automatically created from the ``'default'`` entry in the :setting:`CACHES`
setting::

    >>> from django.core.cache import cache

The basic interface is ``set(key, value, timeout)`` and ``get(key)``::

    >>> cache.set('my_key', 'hello, world!', 30)
    >>> cache.get('my_key')
    'hello, world!'

The ``timeout`` argument is optional and defaults to the ``timeout``
argument of the ``'default'`` backend in :setting:`CACHES` setting
(explained above). It's the number of seconds the value should be stored
in the cache.

If the object doesn't exist in the cache, ``cache.get()`` returns ``None``::

    # Wait 30 seconds for 'my_key' to expire...

    >>> cache.get('my_key')
    None

We advise against storing the literal value ``None`` in the cache, because you
won't be able to distinguish between your stored ``None`` value and a cache
miss signified by a return value of ``None``.

``cache.get()`` can take a ``default`` argument. This specifies which value to
return if the object doesn't exist in the cache::

    >>> cache.get('my_key', 'has expired')
    'has expired'

To add a key only if it doesn't already exist, use the ``add()`` method.
It takes the same parameters as ``set()``, but it will not attempt to
update the cache if the key specified is already present::

    >>> cache.set('add_key', 'Initial value')
    >>> cache.add('add_key', 'New value')
    >>> cache.get('add_key')
    'Initial value'

If you need to know whether ``add()`` stored a value in the cache, you can
check the return value. It will return ``True`` if the value was stored,
``False`` otherwise.

There's also a ``get_many()`` interface that only hits the cache once.
``get_many()`` returns a dictionary with all the keys you asked for that
actually exist in the cache (and haven't expired)::

    >>> cache.set('a', 1)
    >>> cache.set('b', 2)
    >>> cache.set('c', 3)
    >>> cache.get_many(['a', 'b', 'c'])
    {'a': 1, 'b': 2, 'c': 3}

.. versionadded:: 1.2

To set multiple values more efficiently, use ``set_many()`` to pass a dictionary
of key-value pairs::

    >>> cache.set_many({'a': 1, 'b': 2, 'c': 3})
    >>> cache.get_many(['a', 'b', 'c'])
    {'a': 1, 'b': 2, 'c': 3}

Like ``cache.set()``, ``set_many()`` takes an optional ``timeout`` parameter.

You can delete keys explicitly with ``delete()``. This is an easy way of
clearing the cache for a particular object::

    >>> cache.delete('a')

.. versionadded:: 1.2

If you want to clear a bunch of keys at once, ``delete_many()`` can take a list
of keys to be cleared::

    >>> cache.delete_many(['a', 'b', 'c'])

.. versionadded:: 1.2

Finally, if you want to delete all the keys in the cache, use
``cache.clear()``.  Be careful with this; ``clear()`` will remove *everything*
from the cache, not just the keys set by your application. ::

    >>> cache.clear()

You can also increment or decrement a key that already exists using the
``incr()`` or ``decr()`` methods, respectively. By default, the existing cache
value will incremented or decremented by 1. Other increment/decrement values
can be specified by providing an argument to the increment/decrement call. A
ValueError will be raised if you attempt to increment or decrement a
nonexistent cache key.::

    >>> cache.set('num', 1)
    >>> cache.incr('num')
    2
    >>> cache.incr('num', 10)
    12
    >>> cache.decr('num')
    11
    >>> cache.decr('num', 5)
    6

.. note::

    ``incr()``/``decr()`` methods are not guaranteed to be atomic. On those
    backends that support atomic increment/decrement (most notably, the
    memcached backend), increment and decrement operations will be atomic.
    However, if the backend doesn't natively provide an increment/decrement
    operation, it will be implemented using a two-step retrieve/update.

.. _cache_key_prefixing:

Cache key prefixing
-------------------

.. versionadded:: 1.3

If you are sharing a cache instance between servers, or between your
production and development environments, it's possible for data cached
by one server to be used by another server. If the format of cached
data is different between servers, this can lead to some very hard to
diagnose problems.

To prevent this, Django provides the ability to prefix all cache keys
used by a server. When a particular cache key is saved or retrieved,
Django will automatically prefix the cache key with the value of the
:setting:`KEY_PREFIX <CACHES-KEY_PREFIX>` cache setting.

By ensuring each Django instance has a different
:setting:`KEY_PREFIX <CACHES-KEY_PREFIX>`, you can ensure that there will be no
collisions in cache values.

.. _cache_versioning:

Cache versioning
----------------

.. versionadded:: 1.3

When you change running code that uses cached values, you may need to
purge any existing cached values. The easiest way to do this is to
flush the entire cache, but this can lead to the loss of cache values
that are still valid and useful.

Django provides a better way to target individual cache values.
Django's cache framework has a system-wide version identifier,
specified using the :setting:`VERSION <CACHES-VERSION>` cache setting.
The value of this setting is automatically combined with the cache
prefix and the user-provided cache key to obtain the final cache key.

By default, any key request will automatically include the site
default cache key version. However, the primitive cache functions all
include a ``version`` argument, so you can specify a particular cache
key version to set or get. For example::

    # Set version 2 of a cache key
    >>> cache.set('my_key', 'hello world!', version=2)
    # Get the default version (assuming version=1)
    >>> cache.get('my_key')
    None
    # Get version 2 of the same key
    >>> cache.get('my_key', version=2)
    'hello world!'

The version of a specific key can be incremented and decremented using
the :func:`incr_version()` and :func:`decr_version()` methods. This
enables specific keys to be bumped to a new version, leaving other
keys unaffected. Continuing our previous example::

    # Increment the version of 'my_key'
    >>> cache.incr_version('my_key')
    # The default version still isn't available
    >>> cache.get('my_key')
    None
    # Version 2 isn't available, either
    >>> cache.get('my_key', version=2)
    None
    # But version 3 *is* availble
    >>> cache.get('my_key', version=3)
    'hello world!'

.. _cache_key_transformation:

Cache key transformation
------------------------

.. versionadded:: 1.3

As described in the previous two sections, the cache key provided by a
user is not used verbatim -- it is combined with the cache prefix and
key version to provide a final cache key. By default, the three parts
are joined using colons to produce a final string::

    def make_key(key, key_prefix, version):
        return ':'.join([key_prefix, str(version), smart_str(key)])

If you want to combine the parts in different ways, or apply other
processing to the final key (e.g., taking a hash digest of the key
parts), you can provide a custom key function.

The :setting:`KEY_FUNCTION <CACHES-KEY_FUNCTION>` cache setting
specifies a dotted-path to a function matching the prototype of
:func:`make_key()` above. If provided, this custom key function will
be used instead of the default key combining function.

Cache key warnings
------------------

.. versionadded:: 1.3

Memcached, the most commonly-used production cache backend, does not allow
cache keys longer than 250 characters or containing whitespace or control
characters, and using such keys will cause an exception. To encourage
cache-portable code and minimize unpleasant surprises, the other built-in cache
backends issue a warning (``django.core.cache.backends.base.CacheKeyWarning``)
if a key is used that would cause an error on memcached.

If you are using a production backend that can accept a wider range of keys (a
custom backend, or one of the non-memcached built-in backends), and want to use
this wider range without warnings, you can silence ``CacheKeyWarning`` with
this code in the ``management`` module of one of your
:setting:`INSTALLED_APPS`::

     import warnings

     from django.core.cache import CacheKeyWarning

     warnings.simplefilter("ignore", CacheKeyWarning)

If you want to instead provide custom key validation logic for one of the
built-in backends, you can subclass it, override just the ``validate_key``
method, and follow the instructions for `using a custom cache backend`_. For
instance, to do this for the ``locmem`` backend, put this code in a module::

    from django.core.cache.backends.locmem import LocMemCache

    class CustomLocMemCache(LocMemCache):
        def validate_key(self, key):
            """Custom validation, raising exceptions or warnings as needed."""
            # ...

...and use the dotted Python path to this class in the
:setting:`BACKEND <CACHES-BACKEND>` portion of your :setting:`CACHES` setting.

Upstream caches
===============

So far, this document has focused on caching your *own* data. But another type
of caching is relevant to Web development, too: caching performed by "upstream"
caches. These are systems that cache pages for users even before the request
reaches your Web site.

Here are a few examples of upstream caches:

    * Your ISP may cache certain pages, so if you requested a page from
      http://example.com/, your ISP would send you the page without having to
      access example.com directly. The maintainers of example.com have no
      knowledge of this caching; the ISP sits between example.com and your Web
      browser, handling all of the caching transparently.

    * Your Django Web site may sit behind a *proxy cache*, such as Squid Web
      Proxy Cache (http://www.squid-cache.org/), that caches pages for
      performance. In this case, each request first would be handled by the
      proxy, and it would be passed to your application only if needed.

    * Your Web browser caches pages, too. If a Web page sends out the
      appropriate headers, your browser will use the local cached copy for
      subsequent requests to that page, without even contacting the Web page
      again to see whether it has changed.

Upstream caching is a nice efficiency boost, but there's a danger to it:
Many Web pages' contents differ based on authentication and a host of other
variables, and cache systems that blindly save pages based purely on URLs could
expose incorrect or sensitive data to subsequent visitors to those pages.

For example, say you operate a Web e-mail system, and the contents of the
"inbox" page obviously depend on which user is logged in. If an ISP blindly
cached your site, then the first user who logged in through that ISP would have
his user-specific inbox page cached for subsequent visitors to the site. That's
not cool.

Fortunately, HTTP provides a solution to this problem. A number of HTTP headers
exist to instruct upstream caches to differ their cache contents depending on
designated variables, and to tell caching mechanisms not to cache particular
pages. We'll look at some of these headers in the sections that follow.

.. _using-vary-headers:

Using Vary headers
==================

The ``Vary`` header defines which request headers a cache
mechanism should take into account when building its cache key. For example, if
the contents of a Web page depend on a user's language preference, the page is
said to "vary on language."

By default, Django's cache system creates its cache keys using the requested
path (e.g., ``"/stories/2005/jun/23/bank_robbed/"``). This means every request
to that URL will use the same cached version, regardless of user-agent
differences such as cookies or language preferences. However, if this page
produces different content based on some difference in request headers -- such
as a cookie, or a language, or a user-agent -- you'll need to use the ``Vary``
header to tell caching mechanisms that the page output depends on those things.

To do this in Django, use the convenient ``vary_on_headers`` view decorator,
like so::

    from django.views.decorators.vary import vary_on_headers

    @vary_on_headers('User-Agent')
    def my_view(request):
        # ...

In this case, a caching mechanism (such as Django's own cache middleware) will
cache a separate version of the page for each unique user-agent.

The advantage to using the ``vary_on_headers`` decorator rather than manually
setting the ``Vary`` header (using something like
``response['Vary'] = 'user-agent'``) is that the decorator *adds* to the
``Vary`` header (which may already exist), rather than setting it from scratch
and potentially overriding anything that was already in there.

You can pass multiple headers to ``vary_on_headers()``::

    @vary_on_headers('User-Agent', 'Cookie')
    def my_view(request):
        # ...

This tells upstream caches to vary on *both*, which means each combination of
user-agent and cookie will get its own cache value. For example, a request with
the user-agent ``Mozilla`` and the cookie value ``foo=bar`` will be considered
different from a request with the user-agent ``Mozilla`` and the cookie value
``foo=ham``.

Because varying on cookie is so common, there's a ``vary_on_cookie``
decorator. These two views are equivalent::

    @vary_on_cookie
    def my_view(request):
        # ...

    @vary_on_headers('Cookie')
    def my_view(request):
        # ...

The headers you pass to ``vary_on_headers`` are not case sensitive;
``"User-Agent"`` is the same thing as ``"user-agent"``.

You can also use a helper function, ``django.utils.cache.patch_vary_headers``,
directly. This function sets, or adds to, the ``Vary header``. For example::

    from django.utils.cache import patch_vary_headers

    def my_view(request):
        # ...
        response = render_to_response('template_name', context)
        patch_vary_headers(response, ['Cookie'])
        return response

``patch_vary_headers`` takes an :class:`~django.http.HttpResponse` instance as
its first argument and a list/tuple of case-insensitive header names as its
second argument.

For more on Vary headers, see the `official Vary spec`_.

.. _`official Vary spec`: http://www.w3.org/Protocols/rfc2616/rfc2616-sec14.html#sec14.44

Controlling cache: Using other headers
======================================

Other problems with caching are the privacy of data and the question of where
data should be stored in a cascade of caches.

A user usually faces two kinds of caches: his or her own browser cache (a
private cache) and his or her provider's cache (a public cache). A public cache
is used by multiple users and controlled by someone else. This poses problems
with sensitive data--you don't want, say, your bank account number stored in a
public cache. So Web applications need a way to tell caches which data is
private and which is public.

The solution is to indicate a page's cache should be "private." To do this in
Django, use the ``cache_control`` view decorator. Example::

    from django.views.decorators.cache import cache_control

    @cache_control(private=True)
    def my_view(request):
        # ...

This decorator takes care of sending out the appropriate HTTP header behind the
scenes.

There are a few other ways to control cache parameters. For example, HTTP
allows applications to do the following:

    * Define the maximum time a page should be cached.

    * Specify whether a cache should always check for newer versions, only
      delivering the cached content when there are no changes. (Some caches
      might deliver cached content even if the server page changed, simply
      because the cache copy isn't yet expired.)

In Django, use the ``cache_control`` view decorator to specify these cache
parameters. In this example, ``cache_control`` tells caches to revalidate the
cache on every access and to store cached versions for, at most, 3,600 seconds::

    from django.views.decorators.cache import cache_control

    @cache_control(must_revalidate=True, max_age=3600)
    def my_view(request):
        # ...

Any valid ``Cache-Control`` HTTP directive is valid in ``cache_control()``.
Here's a full list:

    * ``public=True``
    * ``private=True``
    * ``no_cache=True``
    * ``no_transform=True``
    * ``must_revalidate=True``
    * ``proxy_revalidate=True``
    * ``max_age=num_seconds``
    * ``s_maxage=num_seconds``

For explanation of Cache-Control HTTP directives, see the `Cache-Control spec`_.

(Note that the caching middleware already sets the cache header's max-age with
the value of the :setting:`CACHE_MIDDLEWARE_SECONDS` setting. If you use a custom
``max_age`` in a ``cache_control`` decorator, the decorator will take
precedence, and the header values will be merged correctly.)

If you want to use headers to disable caching altogether,
``django.views.decorators.cache.never_cache`` is a view decorator that adds
headers to ensure the response won't be cached by browsers or other caches.
Example::

    from django.views.decorators.cache import never_cache

    @never_cache
    def myview(request):
        # ...

.. _`Cache-Control spec`: http://www.w3.org/Protocols/rfc2616/rfc2616-sec14.html#sec14.9

Other optimizations
===================

Django comes with a few other pieces of middleware that can help optimize your
site's performance:

    * ``django.middleware.http.ConditionalGetMiddleware`` adds support for
      modern browsers to conditionally GET responses based on the ``ETag``
      and ``Last-Modified`` headers.

    * :class:`django.middleware.gzip.GZipMiddleware` compresses responses for all
      moderns browsers, saving bandwidth and transfer time.

Order of MIDDLEWARE_CLASSES
===========================

If you use caching middleware, it's important to put each half in the right
place within the :setting:`MIDDLEWARE_CLASSES` setting. That's because the cache
middleware needs to know which headers by which to vary the cache storage.
Middleware always adds something to the ``Vary`` response header when it can.

``UpdateCacheMiddleware`` runs during the response phase, where middleware is
run in reverse order, so an item at the top of the list runs *last* during the
response phase. Thus, you need to make sure that ``UpdateCacheMiddleware``
appears *before* any other middleware that might add something to the ``Vary``
header. The following middleware modules do so:

    * ``SessionMiddleware`` adds ``Cookie``
    * ``GZipMiddleware`` adds ``Accept-Encoding``
    * ``LocaleMiddleware`` adds ``Accept-Language``

``FetchFromCacheMiddleware``, on the other hand, runs during the request phase,
where middleware is applied first-to-last, so an item at the top of the list
runs *first* during the request phase. The ``FetchFromCacheMiddleware`` also
needs to run after other middleware updates the ``Vary`` header, so
``FetchFromCacheMiddleware`` must be *after* any item that does so.