A fundamental trade-off in dynamic websites 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 “downstream” caches, such as Squid 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.
See also
The Cache Framework design philosophy explains a few of the design decisions of the framework.
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 CACHES setting in your
settings file. Here’s an explanation of all available values for
CACHES.
The fastest, most efficient type of cache supported natively by Django, Memcached is an entirely memory-based cache server, originally developed to handle high loads at LiveJournal.com and subsequently open-sourced by Danga Interactive. It is used by sites such as Facebook and Wikipedia to reduce database access and dramatically increase site performance.
Memcached 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 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.
To use Memcached with Django:
BACKEND to
django.core.cache.backends.memcached.MemcachedCache or
django.core.cache.backends.memcached.PyLibMCCache (depending
on your chosen memcached binding)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, or to a unix:path value, where
path is the path to a Memcached Unix socket file.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',
}
}
In this example, Memcached is available through a local Unix socket file
/tmp/memcached.sock using the python-memcached binding:
CACHES = {
'default': {
'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
'LOCATION': 'unix:/tmp/memcached.sock',
}
}
When using the pylibmc binding, do not include the unix:/ prefix:
CACHES = {
'default': {
'BACKEND': 'django.core.cache.backends.memcached.PyLibMCCache',
'LOCATION': '/tmp/memcached.sock',
}
}
One excellent feature of Memcached is its ability to share a 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
LOCATION, either as a semicolon or comma
delimited string, 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',
'172.19.26.242:11212',
'172.19.26.244:11213',
]
}
}
A final point about Memcached is that memory-based caching has a 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.
The LOCATION setting now supports defining
multiple servers as a comma-delimited string.
Django can store its cached data in your database. This works best if you’ve got a fast, well-indexed database server.
To use a database table as your cache backend:
BACKEND to
django.core.cache.backends.db.DatabaseCacheLOCATION to tablename, the name of the
database table. 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.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',
}
}
Before using the database cache, you must create the cache table with this command:
python manage.py createcachetable
This creates a table in your database that is in the proper format that
Django’s database-cache system expects. The name of the table is taken from
LOCATION.
If you are using multiple database caches, createcachetable creates
one table for each cache.
If you are using multiple databases, createcachetable observes the
allow_migrate() method of your database routers (see below).
Like migrate, createcachetable won’t touch an existing
table. It will only create missing tables.
To print the SQL that would be run, rather than run it, use the
createcachetable --dry-run option.
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_replica, and all write operations to
cache_primary. The cache table will only be synchronized onto
cache_primary:
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 replica"
if model._meta.app_label == 'django_cache':
return 'cache_replica'
return None
def db_for_write(self, model, **hints):
"All cache write operations go to primary"
if model._meta.app_label == 'django_cache':
return 'cache_primary'
return None
def allow_migrate(self, db, app_label, model_name=None, **hints):
"Only install the cache model on primary"
if app_label == 'django_cache':
return db == 'cache_primary'
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.
The file-based backend serializes and stores each cache value as a separate
file. To use this backend set BACKEND to
"django.core.cache.backends.filebased.FileBasedCache" and
LOCATION to a suitable directory. 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.
This is the default cache if another is not specified in your settings file. 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
per-process (see below) and thread-safe. To use it, set BACKEND to "django.core.cache.backends.locmem.LocMemCache". For
example:
CACHES = {
'default': {
'BACKEND': 'django.core.cache.backends.locmem.LocMemCache',
'LOCATION': 'unique-snowflake',
}
}
The cache LOCATION is used to identify individual
memory stores. If you only have one locmem cache, you can omit the
LOCATION; however, if you have more than 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.
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 BACKEND like so:
CACHES = {
'default': {
'BACKEND': 'django.core.cache.backends.dummy.DummyCache',
}
}
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
BACKEND of the 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.
Each cache backend can be given additional arguments to control caching
behavior. These arguments are provided as additional keys in the
CACHES setting. Valid arguments are as follows:
TIMEOUT: The default timeout, in
seconds, to use for the cache. This argument defaults to 300 seconds (5 minutes).
You can set TIMEOUT to None so that, by default, cache keys never
expire. A value of 0 causes keys to immediately expire (effectively
“don’t cache”).
OPTIONS: Any options that should be
passed to the cache backend. The list of valid options will vary
with each backend, and cache backends backed by a third-party library
will pass their options directly to the underlying cache library.
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 the entries when MAX_ENTRIES is reached. This argument
should be an integer and defaults to 3.
A value of 0 for CULL_FREQUENCY means that the
entire cache will be dumped when MAX_ENTRIES is reached.
On some backends (database in particular) this makes culling much
faster at the expense of more cache misses.
Memcached backends pass the contents of OPTIONS
as keyword arguments to the client constructors, allowing for more advanced
control of client behavior. For example usage, see below.
KEY_PREFIX: A string that will be
automatically included (prepended by default) to all cache keys
used by the Django server.
See the cache documentation for more information.
VERSION: The default version number
for cache keys generated by the Django server.
See the cache documentation for more information.
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 cache documentation 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.FileBasedCache',
'LOCATION': '/var/tmp/django_cache',
'TIMEOUT': 60,
'OPTIONS': {
'MAX_ENTRIES': 1000
}
}
}
Here’s an example configuration for a python-memcached based backend with
an object size limit of 2MB:
CACHES = {
'default': {
'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
'LOCATION': '127.0.0.1:11211',
'OPTIONS': {
'server_max_value_length': 1024 * 1024 * 2,
}
}
}
Here’s an example configuration for a pylibmc based backend that enables
the binary protocol, SASL authentication, and the ketama behavior mode:
CACHES = {
'default': {
'BACKEND': 'django.core.cache.backends.memcached.PyLibMCCache',
'LOCATION': '127.0.0.1:11211',
'OPTIONS': {
'binary': True,
'username': 'user',
'password': 'pass',
'behaviors': {
'ketama': True,
}
}
}
}
Memcached backends can now be configured using OPTIONS.
In older versions, you could pass pylibmc behavior settings directly
inside OPTIONS. This is deprecated in favor of setting them under a
behaviors key within OPTIONS instead.
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 setting, as in this example:
MIDDLEWARE = [
'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 below if you’d like the full story.
Then, add the following required settings to your Django settings file:
CACHE_MIDDLEWARE_ALIAS – The cache alias to use for storage.CACHE_MIDDLEWARE_SECONDS – The number of seconds each page should
be cached.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.FetchFromCacheMiddleware caches GET and HEAD responses with status 200,
where the request and response headers allow. Responses to requests for the same
URL with different query parameters are considered to be unique pages and are
cached separately. This 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, UpdateCacheMiddleware automatically sets a few headers in each
HttpResponse:
Expires header to the current date/time plus the defined
CACHE_MIDDLEWARE_SECONDS.Cache-Control header to give a max age for the page –
again, from the CACHE_MIDDLEWARE_SECONDS setting.In older versions, the Last-Modified header was also set.
See 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 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.
If USE_I18N is set to True then the generated cache key will
include the name of the active language – see also
How Django discovers language preference). This allows you to easily
cache multilingual sites without having to create the cache key yourself.
Cache keys also include the active language when
USE_L10N is set to True and the current time zone when USE_TZ is set to True.
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 = [
url(r'^foo/([0-9]{1,2})/$', my_view),
]
then requests to /foo/1/ and /foo/23/ will be cached separately, as
you may expect. But once a particular URL (e.g., /foo/23/) has been
requested, subsequent requests to that URL will use the cache.
cache_page can also take an optional keyword argument, cache,
which directs the decorator to use a specific cache (from your
CACHES setting) when caching view results. By default, the
default cache will be used, but you can specify any cache you
want:
@cache_page(60 * 15, cache="special_cache")
def my_view(request):
...
You can also override the cache prefix on a per-view basis. cache_page
takes an optional keyword argument, key_prefix,
which works in the same way as the CACHE_MIDDLEWARE_KEY_PREFIX
setting for the middleware. It can be used like this:
@cache_page(60 * 15, key_prefix="site1")
def my_view(request):
...
The key_prefix and cache arguments may be specified together. The
key_prefix argument and the KEY_PREFIX
specified under CACHES will be concatenated.
The examples in the previous section have hard-coded the fact that the view is
cached, because cache_page alters the my_view function in place. This
approach couples your view to the cache system, which is not ideal for several
reasons. For instance, you might want to reuse the view functions on another,
cache-less site, or you might want to distribute the views to people who might
want to use them without being cached. The solution to these problems is to
specify the per-view cache in the URLconf rather than next to the view functions
themselves.
Doing so is easy: simply wrap the view function with cache_page when you
refer to it in the URLconf. Here’s the old URLconf from earlier:
urlpatterns = [
url(r'^foo/([0-9]{1,2})/$', my_view),
]
Here’s the same thing, with my_view wrapped in cache_page:
from django.views.decorators.cache import cache_page
urlpatterns = [
url(r'^foo/([0-9]{1,2})/$', cache_page(60 * 15)(my_view)),
]
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. The name will be taken as is, do not
use a variable. For example:
{% 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:
{% 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 USE_I18N is set to True the per-site middleware cache will
respect the active language. For the cache template
tag you could use one of the
translation-specific variables available in
templates to achieve the same result:
{% 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:
{% 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.
By default, the cache tag will try to use the cache called “template_fragments”.
If no such cache exists, it will fall back to using the default cache. You may
select an alternate cache backend to use with the using keyword argument,
which must be the last argument to the tag.
{% cache 300 local-thing ... using="localcache" %}
It is considered an error to specify a cache name that is not configured.
django.core.cache.utils.make_template_fragment_key(fragment_name, vary_on=None)¶If you want to obtain the cache key used for a cached fragment, you can use
make_template_fragment_key. fragment_name is the same as second argument
to the cache template tag; vary_on is a list of all additional arguments
passed to the tag. This function can be useful for invalidating or overwriting
a cached item, for example:
>>> from django.core.cache import cache
>>> from django.core.cache.utils import make_template_fragment_key
# cache key for {% cache 500 sidebar username %}
>>> key = make_template_fragment_key('sidebar', [username])
>>> cache.delete(key) # invalidates cached template fragment
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.)
django.core.cache.caches¶You can access the caches configured in the CACHES setting
through a dict-like object: django.core.cache.caches. Repeated
requests for the same alias in the same thread will return the same
object.
>>> from django.core.cache import caches
>>> cache1 = caches['myalias']
>>> cache2 = caches['myalias']
>>> cache1 is cache2
True
If the named key does not exist, InvalidCacheBackendError will be
raised.
To provide thread-safety, a different instance of the cache backend will be returned for each thread.
django.core.cache.cache¶As a shortcut, the default cache is available as
django.core.cache.cache:
>>> from django.core.cache import cache
This object is equivalent to caches['default'].
The basic interface is set(key, value, timeout) and get(key):
>>> cache.set('my_key', 'hello, world!', 30)
>>> cache.get('my_key')
'hello, world!'
key should be a str (or unicode on Python 2), and value can be
any picklable Python object.
The timeout argument is optional and defaults to the timeout argument
of the appropriate backend in the CACHES setting (explained above).
It’s the number of seconds the value should be stored in the cache. Passing in
None for timeout will cache the value forever. A timeout of 0
won’t cache the value.
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.
If you want to get a key’s value or set a value if the key isn’t in the cache,
there is the get_or_set() method. It takes the same parameters as get()
but the default is set as the new cache value for that key, rather than simply
returned:
>>> cache.get('my_new_key') # returns None
>>> cache.get_or_set('my_new_key', 'my new value', 100)
'my new value'
You can also pass any callable as a default value:
>>> import datetime
>>> cache.get_or_set('some-timestamp-key', datetime.datetime.now)
datetime.datetime(2014, 12, 11, 0, 15, 49, 457920)
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}
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')
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'])
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.
You can close the connection to your cache with close() if implemented by
the cache backend.
>>> cache.close()
Note
For caches that don’t implement close methods it is a no-op.
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
KEY_PREFIX cache setting.
By ensuring each Django instance has a different
KEY_PREFIX, you can ensure that there will be no
collisions in cache values.
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 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 incr_version() and 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* available
>>> cache.get('my_key', version=3)
'hello world!'
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), 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 KEY_FUNCTION cache setting
specifies a dotted-path to a function matching the prototype of
make_key() above. If provided, this custom key function will
be used instead of the default key combining function.
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
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
BACKEND portion of your CACHES setting.
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 “downstream” caches. These are systems that cache pages for users even before the request reaches your website.
Here are a few examples of downstream caches:
Downstream 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 email 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 their 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 downstream 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.
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
fully-qualified URL – e.g.,
"https://www.example.com/stories/2005/?order_by=author". 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
django.views.decorators.vary.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 downstream 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
django.views.decorators.vary.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.shortcuts import render
from django.utils.cache import patch_vary_headers
def my_view(request):
...
response = render(request, 'template_name', context)
patch_vary_headers(response, ['Cookie'])
return response
patch_vary_headers takes an 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.
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: their own browser cache (a private cache) and their 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.
Note that the cache control settings “private” and “public” are mutually
exclusive. The decorator ensures that the “public” directive is removed if
“private” should be set (and vice versa). An example use of the two directives
would be a blog site that offers both private and public entries. Public
entries may be cached on any shared cache. The following code uses
patch_cache_control(), the manual way to modify the
cache control header (it is internally called by the
cache_control() decorator):
from django.views.decorators.cache import patch_cache_control
from django.views.decorators.vary import vary_on_cookie
@vary_on_cookie
def list_blog_entries_view(request):
if request.user.is_anonymous:
response = render_only_public_entries()
patch_cache_control(response, public=True)
else:
response = render_private_and_public_entries(request.user)
patch_cache_control(response, private=True)
return response
You can control downstream caches in other ways as well (see RFC 7234 for details on HTTP caching). For example, even if you don’t use Django’s server-side cache framework, you can still tell clients to cache a view for a certain amount of time with the max-age directive:
from django.views.decorators.cache import cache_control
@cache_control(max_age=3600)
def my_view(request):
...
(If you do use the caching middleware, it already sets the max-age with
the value of the CACHE_MIDDLEWARE_SECONDS setting. In that case,
the custom max_age from the
cache_control() decorator will take
precedence, and the header values will be merged correctly.)
Any valid Cache-Control response directive is valid in cache_control().
Here are some more examples:
no_transform=Truemust_revalidate=Truestale_while_revalidate=num_secondsThe full list of known directives can be found in the IANA registry (note that not all of them apply to responses).
If you want to use headers to disable caching altogether,
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):
...
MIDDLEWARE¶If you use caching middleware, it’s important to put each half in the right
place within the MIDDLEWARE 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 CookieGZipMiddleware adds Accept-EncodingLocaleMiddleware adds Accept-LanguageFetchFromCacheMiddleware, 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.
Jun 22, 2017