Fixed #16886 -- Memcached socket file documentation. Thanks ddbeck for the report and patch.
git-svn-id: http://code.djangoproject.com/svn/django/trunk@16858 bcc190cf-cafb-0310-a4f2-bffc1f526a37
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@ -100,8 +100,9 @@ To use Memcached with Django:
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on your chosen memcached binding)
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on your chosen memcached binding)
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* Set :setting:`LOCATION <CACHES-LOCATION>` to ``ip:port`` values,
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* Set :setting:`LOCATION <CACHES-LOCATION>` to ``ip:port`` values,
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where ``ip`` is the IP address of the Memcached daemon and
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where ``ip`` is the IP address of the Memcached daemon and ``port`` is the
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``port`` is the port on which Memcached is running.
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port on which Memcached is running, or to a ``unix:path`` value, where
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``path`` is the path to a Memcached Unix socket file.
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In this example, Memcached is running on localhost (127.0.0.1) port 11211, using
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In this example, Memcached is running on localhost (127.0.0.1) port 11211, using
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the ``python-memcached`` binding::
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the ``python-memcached`` binding::
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@ -113,6 +114,16 @@ the ``python-memcached`` binding::
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}
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}
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}
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}
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In this example, Memcached is available through a local Unix socket file
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:file:`/tmp/memcached.sock` using the ``python-memcached`` binding::
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CACHES = {
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'default': {
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'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
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'LOCATION': 'unix:/tmp/memcached.sock',
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}
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}
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One excellent feature of Memcached is its ability to share cache over multiple
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One excellent feature of Memcached is its ability to share cache over multiple
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servers. This means you can run Memcached daemons on multiple machines, and the
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servers. This means you can run Memcached daemons on multiple machines, and the
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program will treat the group of machines as a *single* cache, without the need
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program will treat the group of machines as a *single* cache, without the need
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