Chapter 16 – Django sessions
最后更新于：2022-04-01 04:48:09
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 creating the page that your site visitors see. 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, its essential to cut as much overhead as possible.
Thats 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. Heres 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](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.
[TOC=3]
## 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 caches performance.
Your cache preference goes in the `CACHES` setting in your settings file.
### Memcached
The fastest, most efficient type of cache supported natively by Django, [Memcached](http://memcached.org/) 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](ftp://ftp.tummy.com/pub/python-memcached/) and [pylibmc](http://sendapatch.se/projects/pylibmc/).
To use Memcached with Django:
* Set `BACKEND <CACHES-BACKEND>` to `django.core.cache.backends.memcached.MemcachedCache` or`django.core.cache.backends.memcached.PyLibMCCache` (depending on your chosen memcached binding)
* Set `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, 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',
}
}
~~~
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 <CACHES-LOCATION>`, 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',
'172.19.26.242:11212',
'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.
### Database caching
Django can store its cached data in your database. This works best if youve got a fast, well-indexed database server.
To use a database table as your cache backend:
* Set `BACKEND <CACHES-BACKEND>` to `django.core.cache.backends.db.DatabaseCache`
* Set `LOCATION <CACHES-LOCATION>` to `tablename`, the name of the database table. This name can be whatever you want, as long as its a valid table name thats not already being used in your database.
In this example, the cache tables name is `my_cache_table`:
~~~
CACHES = {
'default': {
'BACKEND': 'django.core.cache.backends.db.DatabaseCache',
'LOCATION': 'my_cache_table',
}
}
~~~
#### CREATING THE 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 <CACHES-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``` wont touch an existing table. It will only create missing tables.
#### 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_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 in ('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 in ('django_cache',):
return 'cache_primary'
return None
def allow_migrate(self, db, model):
"Only install the cache model on primary"
if model._meta.app_label in ('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.
### Filesystem caching
The file-based backend serializes and stores each cache value as a separate file. To use this backend set`BACKEND <CACHES-BACKEND>` to `"django.core.cache.backends.filebased.FileBasedCache"` and `LOCATION <CACHES-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 youre 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`.
### Local-memory caching
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 <CACHES-LOCATION>` is used to identify individual memory stores. If you only have one`locmem` cache, you can omit the `LOCATION <CACHES-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 isnt particularly memory-efficient, so its probably not a good choice for production environments. Its nice for development.
### Dummy caching (for development)
Finally, Django comes with a dummy cache that doesnt 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 <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 `BACKEND <CACHES-BACKEND>` of the `CACHES` setting, like so:
~~~
CACHES = {
'default': {
'BACKEND': 'path.to.backend',
}
}
~~~
If youre building your own backend, you can use the standard cache backends as reference implementations. Youll 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. Theyve been well-tested and are easy to use.
### Cache arguments
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 <CACHES-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 dont cache).
* `OPTIONS <CACHES-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.
* `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 cache documentation for more information.
* `VERSION <CACHES-VERSION>`: The default version number for cache keys generated by the Django server.
See the cache documentation for more information.
* `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 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
}
}
}
~~~
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. Youll 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, thats 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](http://masteringdjango.com/django%c2%92-cache-framework/#order-of-middleware-classes) below if youd 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 dont 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`:
* Sets the `Last-Modified` header to the current date/time when a fresh (not cached) version of the page is requested.
* Sets the `Expires` header to the current date/time plus the defined `CACHE_MIDDLEWARE_SECONDS`.
* Sets the `Cache-Control` header to give a max age for the page again, from the `CACHE_MIDDLEWARE_SECONDS`setting.
See Chapter 19 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 views expiry time (using the `cache_control` decorator) or disable caching for a view (using the `never_cache` decorator). See the [using other headers](http://masteringdjango.com/django%c2%92-cache-framework/#controlling-cache-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](http://masteringdjango.com/django%c2%92-cache-framework/chapter_20.html#term-language-code) 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](http://masteringdjango.com/django%c2%92-cache-framework/chapter_20.html#term-language-code) when `USE_L10N` is set to `True` and the current time zone when`USE_TZ` is set to `True`.
## The per-view cache
`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 views response for you. Its 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 weve 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})/$', my_view),
]
~~~
then requests to `/foo/1/` and `/foo/23/` will be cached separately, as you may expect. But once a particular URL (e.g., `/foo/23/`) has been requested, subsequent requests to that URL will use the cache.
`cache_page` can also take an optional keyword argument, `cache`, which directs the decorator to use a specific cache (from your `CACHES` setting) when caching view results. By default, the `default` cache will be used, but you can specify any cache you want:
~~~
@cache_page(60 * 15, cache="special_cache")
def my_view(request):
...
~~~
You can also override the cache prefix on a per-view basis. `cache_page` takes an optional keyword argument, `key_prefix`, which works in the same way as the `CACHE_MIDDLEWARE_KEY_PREFIX` setting for the middleware. It can be used like this:
~~~
@cache_page(60 * 15, key_prefix="site1")
def my_view(request):
...
~~~
The ```key_prefix and ``cache``` arguments may be specified together. The `key_prefix` argument and the`KEY_PREFIX <CACHES-KEY_PREFIX>` specified under `CACHES` will be concatenated.
### Specifying per-view cache in the URLconf
The examples in the previous section have hard-coded the fact that the view is cached, because `cache_page`alters the `my_view` function in place. This approach couples your view to the cache system, which is not ideal for several reasons. For instance, you might want to reuse the view functions on another, cache-less site, or you might want to distribute the views to people who might want to use them without being cached. The solution to these problems is to specify the per-view cache in the URLconf rather than next to the view functions themselves.
Doing so is easy: simply wrap the view function with `cache_page` when you refer to it in the URLconf. Heres the old URLconf from earlier:
~~~
urlpatterns = [
url(r'^foo/([0-9]{1,2})/$', my_view),
]
~~~
Heres 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)),
]
~~~
## Template fragment caching
If youre 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 %}
~~~
Its 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
~~~
## The low-level cache API
Sometimes, caching an entire rendered page doesnt 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 wouldnt want to cache the entire result (since some of the data changes often), but youd 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.)
### Accessing the cache
`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']`.
### Basic usage
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 appropriate backend in the`CACHES` setting (explained above). Its 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` wont cache the value.
If the object doesnt 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 wont 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 doesnt exist in the cache:
~~~
>>> cache.get('my_key', 'has expired')
'has expired'
~~~
To add a key only if it doesnt 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.
Theres 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 havent 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 doesnt 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 dont implement `close` methods it is a no-op.
### Cache key prefixing
If you are sharing a cache instance between servers, or between your production and development environments, its 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 <CACHES-KEY_PREFIX>` cache setting.
By ensuring each Django instance has a different `KEY_PREFIX <CACHES-KEY_PREFIX>`, you can ensure that there will be no collisions in cache values.
### Cache versioning
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. Djangos cache framework has a system-wide version identifier, specified using the `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 `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!'
~~~
### Cache key transformation
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 <CACHES-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.
### Cache key warnings
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](http://masteringdjango.com/django%c2%92-cache-framework/#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 <CACHES-BACKEND>` portion of your `CACHES`setting.
## Downstream 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 downstream caches. These are systems that cache pages for users even before the request reaches your Web site.
Here are a few examples of downstream caches:
* Your ISP may cache certain pages, so if you requested a page from [http://example.com/](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/](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.
Downstream caching is a nice efficiency boost, but theres 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. Thats 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. Well look at some of these headers in the sections that follow.
## 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 users language preference, the page is said to vary on language.
By default, Djangos cache system creates its cache keys using the requested fully-qualified URL e.g.,`"http://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 youll 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 Djangos 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, theres 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.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 `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](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: their own browser cache (a private cache) and their providers cache (a public cache). A public cache is used by multiple users and controlled by someone else. This poses problems with sensitive datayou dont 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 pages 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 `django.utils.cache.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
~~~
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 isnt 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()`. Heres 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](http://www.w3.org/Protocols/rfc2616/rfc2616-sec14.html#sec14.9).
(Note that the caching middleware already sets the cache headers max-age with the value of the`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 wont be cached by browsers or other caches. Example:
~~~
from django.views.decorators.cache import never_cache
@never_cache
def myview(request):
# ...
~~~
## Order of MIDDLEWARE_CLASSES
If you use caching middleware, its important to put each half in the right place within the`MIDDLEWARE_CLASSES` setting. Thats 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.