{
    "info": {
        "author": "Andy McCurdy",
        "author_email": "sedrik@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Environment :: Console",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7"
        ],
        "description": "redis-py\n========\n\nThe Python interface to the Redis key-value store.\n\n.. image:: https://secure.travis-ci.org/andymccurdy/redis-py.svg?branch=master\n        :target: https://travis-ci.org/andymccurdy/redis-py\n.. image:: https://readthedocs.org/projects/redis-py/badge/?version=latest&style=flat\n        :target: https://redis-py.readthedocs.io/en/latest/\n.. image:: https://badge.fury.io/py/redis.svg\n        :target: https://pypi.org/project/redis/\n.. image:: https://codecov.io/gh/andymccurdy/redis-py/branch/master/graph/badge.svg\n  :target: https://codecov.io/gh/andymccurdy/redis-py\n\nInstallation\n------------\n\nredis-py requires a running Redis server. See `Redis's quickstart\n<https://redis.io/topics/quickstart>`_ for installation instructions.\n\nredis-py can be installed using `pip` similar to other Python packages. Do not use `sudo`\nwith `pip`. It is usually good to work in a\n`virtualenv <https://virtualenv.pypa.io/en/latest/>`_ or\n`venv <https://docs.python.org/3/library/venv.html>`_ to avoid conflicts with other package\nmanagers and Python projects. For a quick introduction see\n`Python Virtual Environments in Five Minutes <https://bit.ly/py-env>`_.\n\nTo install redis-py, simply:\n\n.. code-block:: bash\n\n    $ pip install redis\n\nor from source:\n\n.. code-block:: bash\n\n    $ python setup.py install\n\n\nGetting Started\n---------------\n\n.. code-block:: pycon\n\n    >>> import redis\n    >>> r = redis.Redis(host='localhost', port=6379, db=0)\n    >>> r.set('foo', 'bar')\n    True\n    >>> r.get('foo')\n    'bar'\n\nBy default, all responses are returned as `bytes` in Python 3 and `str` in\nPython 2. The user is responsible for decoding to Python 3 strings or Python 2\nunicode objects.\n\nIf **all** string responses from a client should be decoded, the user can\nspecify `decode_responses=True` to `Redis.__init__`. In this case, any\nRedis command that returns a string type will be decoded with the `encoding`\nspecified.\n\n\nUpgrading from redis-py 2.X to 3.0\n----------------------------------\n\nredis-py 3.0 introduces many new features but required a number of backwards\nincompatible changes to be made in the process. This section attempts to\nprovide an upgrade path for users migrating from 2.X to 3.0.\n\n\nPython Version Support\n^^^^^^^^^^^^^^^^^^^^^^\n\nredis-py 3.0 now supports Python 2.7 and Python 3.4+. Python 2.6 and 3.3\nsupport has been dropped.\n\n\nClient Classes: Redis and StrictRedis\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nredis-py 3.0 drops support for the legacy \"Redis\" client class. \"StrictRedis\"\nhas been renamed to \"Redis\" and an alias named \"StrictRedis\" is provided so\nthat users previously using \"StrictRedis\" can continue to run unchanged.\n\nThe 2.X \"Redis\" class provided alternative implementations of a few commands.\nThis confused users (rightfully so) and caused a number of support issues. To\nmake things easier going forward, it was decided to drop support for these\nalternate implementations and instead focus on a single client class.\n\n2.X users that are already using StrictRedis don't have to change the class\nname. StrictRedis will continue to work for the forseeable future.\n\n2.X users that are using the Redis class will have to make changes if they\nuse any of the following commands:\n\n* SETEX: The argument order has changed. The new order is (name, time, value).\n* LREM: The argument order has changed. The new order is (name, num, value).\n* TTL and PTTL: The return value is now always an int and matches the\n  official Redis command (>0 indicates the timeout, -1 indicates that the key\n  exists but that it has no expire time set, -2 indicates that the key does\n  not exist)\n\n\nSSL Connections\n^^^^^^^^^^^^^^^\n\nredis-py 3.0 changes the default value of the `ssl_cert_reqs` option from\n`None` to `'required'`. See\n`Issue 1016 <https://github.com/andymccurdy/redis-py/issues/1016>`_. This\nchange enforces hostname validation when accepting a cert from a remote SSL\nterminator. If the terminator doesn't properly set the hostname on the cert\nthis will cause redis-py 3.0 to raise a ConnectionError.\n\nThis check can be disabled by setting `ssl_cert_reqs` to `None`. Note that\ndoing so removes the security check. Do so at your own risk.\n\nIt has been reported that SSL certs received from AWS ElastiCache do not have\nproper hostnames and turning off hostname verification is currently required.\n\n\nMSET, MSETNX and ZADD\n^^^^^^^^^^^^^^^^^^^^^\n\nThese commands all accept a mapping of key/value pairs. In redis-py 2.X\nthis mapping could be specified as ``*args`` or as ``**kwargs``. Both of these\nstyles caused issues when Redis introduced optional flags to ZADD. Relying on\n``*args`` caused issues with the optional argument order, especially in Python\n2.7. Relying on ``**kwargs`` caused potential collision issues of user keys with\nthe argument names in the method signature.\n\nTo resolve this, redis-py 3.0 has changed these three commands to all accept\na single positional argument named mapping that is expected to be a dict. For\nMSET and MSETNX, the dict is a mapping of key-names -> values. For ZADD, the\ndict is a mapping of element-names -> score.\n\nMSET, MSETNX and ZADD now look like:\n\n.. code-block:: pycon\n\n    def mset(self, mapping):\n    def msetnx(self, mapping):\n    def zadd(self, name, mapping, nx=False, xx=False, ch=False, incr=False):\n\nAll 2.X users that use these commands must modify their code to supply\nkeys and values as a dict to these commands.\n\n\nZINCRBY\n^^^^^^^\n\nredis-py 2.X accidentally modified the argument order of ZINCRBY, swapping the\norder of value and amount. ZINCRBY now looks like:\n\n.. code-block:: pycon\n\n    def zincrby(self, name, amount, value):\n\nAll 2.X users that rely on ZINCRBY must swap the order of amount and value\nfor the command to continue to work as intended.\n\n\nEncoding of User Input\n^^^^^^^^^^^^^^^^^^^^^^\n\nredis-py 3.0 only accepts user data as bytes, strings or numbers (ints, longs\nand floats). Attempting to specify a key or a value as any other type will\nraise a DataError exception.\n\nredis-py 2.X attempted to coerce any type of input into a string. While\noccasionally convenient, this caused all sorts of hidden errors when users\npassed boolean values (which were coerced to 'True' or 'False'), a None\nvalue (which was coerced to 'None') or other values, such as user defined\ntypes.\n\nAll 2.X users should make sure that the keys and values they pass into\nredis-py are either bytes, strings or numbers.\n\n\nLocks\n^^^^^\n\nredis-py 3.0 drops support for the pipeline-based Lock and now only supports\nthe Lua-based lock. In doing so, LuaLock has been renamed to Lock. This also\nmeans that redis-py Lock objects require Redis server 2.6 or greater.\n\n2.X users that were explicitly referring to \"LuaLock\" will have to now refer\nto \"Lock\" instead.\n\n\nLocks as Context Managers\n^^^^^^^^^^^^^^^^^^^^^^^^^\n\nredis-py 3.0 now raises a LockError when using a lock as a context manager and\nthe lock cannot be acquired within the specified timeout. This is more of a\nbug fix than a backwards incompatible change. However, given an error is now\nraised where none was before, this might alarm some users.\n\n2.X users should make sure they're wrapping their lock code in a try/catch\nlike this:\n\n.. code-block:: pycon\n\n    try:\n        with r.lock('my-lock-key', blocking_timeout=5) as lock:\n            # code you want executed only after the lock has been acquired\n    except LockError:\n        # the lock wasn't acquired\n\n\nAPI Reference\n-------------\n\nThe `official Redis command documentation <https://redis.io/commands>`_ does a\ngreat job of explaining each command in detail. redis-py attempts to adhere\nto the official command syntax. There are a few exceptions:\n\n* **SELECT**: Not implemented. See the explanation in the Thread Safety section\n  below.\n* **DEL**: 'del' is a reserved keyword in the Python syntax. Therefore redis-py\n  uses 'delete' instead.\n* **MULTI/EXEC**: These are implemented as part of the Pipeline class. The\n  pipeline is wrapped with the MULTI and EXEC statements by default when it\n  is executed, which can be disabled by specifying transaction=False.\n  See more about Pipelines below.\n* **SUBSCRIBE/LISTEN**: Similar to pipelines, PubSub is implemented as a separate\n  class as it places the underlying connection in a state where it can't\n  execute non-pubsub commands. Calling the pubsub method from the Redis client\n  will return a PubSub instance where you can subscribe to channels and listen\n  for messages. You can only call PUBLISH from the Redis client (see\n  `this comment on issue #151\n  <https://github.com/andymccurdy/redis-py/issues/151#issuecomment-1545015>`_\n  for details).\n* **SCAN/SSCAN/HSCAN/ZSCAN**: The \\*SCAN commands are implemented as they\n  exist in the Redis documentation. In addition, each command has an equivalent\n  iterator method. These are purely for convenience so the user doesn't have\n  to keep track of the cursor while iterating. Use the\n  scan_iter/sscan_iter/hscan_iter/zscan_iter methods for this behavior.\n\n\nMore Detail\n-----------\n\nConnection Pools\n^^^^^^^^^^^^^^^^\n\nBehind the scenes, redis-py uses a connection pool to manage connections to\na Redis server. By default, each Redis instance you create will in turn create\nits own connection pool. You can override this behavior and use an existing\nconnection pool by passing an already created connection pool instance to the\nconnection_pool argument of the Redis class. You may choose to do this in order\nto implement client side sharding or have finer grain control of how\nconnections are managed.\n\n.. code-block:: pycon\n\n    >>> pool = redis.ConnectionPool(host='localhost', port=6379, db=0)\n    >>> r = redis.Redis(connection_pool=pool)\n\nConnections\n^^^^^^^^^^^\n\nConnectionPools manage a set of Connection instances. redis-py ships with two\ntypes of Connections. The default, Connection, is a normal TCP socket based\nconnection. The UnixDomainSocketConnection allows for clients running on the\nsame device as the server to connect via a unix domain socket. To use a\nUnixDomainSocketConnection connection, simply pass the unix_socket_path\nargument, which is a string to the unix domain socket file. Additionally, make\nsure the unixsocket parameter is defined in your redis.conf file. It's\ncommented out by default.\n\n.. code-block:: pycon\n\n    >>> r = redis.Redis(unix_socket_path='/tmp/redis.sock')\n\nYou can create your own Connection subclasses as well. This may be useful if\nyou want to control the socket behavior within an async framework. To\ninstantiate a client class using your own connection, you need to create\na connection pool, passing your class to the connection_class argument.\nOther keyword parameters you pass to the pool will be passed to the class\nspecified during initialization.\n\n.. code-block:: pycon\n\n    >>> pool = redis.ConnectionPool(connection_class=YourConnectionClass,\n                                    your_arg='...', ...)\n\nConnections maintain an open socket to the Redis server. Sometimes these\nsockets are interrupted or disconnected for a variety of reasons. For example,\nnetwork appliances, load balancers and other services that sit between clients\nand servers are often configured to kill connections that remain idle for a\ngiven threshold.\n\nWhen a connection becomes disconnected, the next command issued on that\nconnection will fail and redis-py will raise a ConnectionError to the caller.\nThis allows each application that uses redis-py to handle errors in a way\nthat's fitting for that specific application. However, constant error\nhandling can be verbose and cumbersome, especially when socket disconnections\nhappen frequently in many production environments.\n\nTo combat this, redis-py can issue regular health checks to assess the\nliveliness of a connection just before issuing a command. Users can pass\n``health_check_interval=N`` to the Redis or ConnectionPool classes or\nas a query argument within a Redis URL. The value of ``health_check_interval``\nmust be an integer. A value of ``0``, the default, disables health checks.\nAny positive integer will enable health checks. Health checks are performed\njust before a command is executed if the underlying connection has been idle\nfor more than ``health_check_interval`` seconds. For example,\n``health_check_interval=30`` will ensure that a health check is run on any\nconnection that has been idle for 30 or more seconds just before a command\nis executed on that connection.\n\nIf your application is running in an environment that disconnects idle\nconnections after 30 seconds you should set the ``health_check_interval``\noption to a value less than 30.\n\nThis option also works on any PubSub connection that is created from a\nclient with ``health_check_interval`` enabled. PubSub users need to ensure\nthat ``get_message()`` or ``listen()`` are called more frequently than\n``health_check_interval`` seconds. It is assumed that most workloads already\ndo this.\n\nIf your PubSub use case doesn't call ``get_message()`` or ``listen()``\nfrequently, you should call ``pubsub.check_health()`` explicitly on a\nregularly basis.\n\nParsers\n^^^^^^^\n\nParser classes provide a way to control how responses from the Redis server\nare parsed. redis-py ships with two parser classes, the PythonParser and the\nHiredisParser. By default, redis-py will attempt to use the HiredisParser if\nyou have the hiredis module installed and will fallback to the PythonParser\notherwise.\n\nHiredis is a C library maintained by the core Redis team. Pieter Noordhuis was\nkind enough to create Python bindings. Using Hiredis can provide up to a\n10x speed improvement in parsing responses from the Redis server. The\nperformance increase is most noticeable when retrieving many pieces of data,\nsuch as from LRANGE or SMEMBERS operations.\n\nHiredis is available on PyPI, and can be installed via pip just like redis-py.\n\n.. code-block:: bash\n\n    $ pip install hiredis\n\nResponse Callbacks\n^^^^^^^^^^^^^^^^^^\n\nThe client class uses a set of callbacks to cast Redis responses to the\nappropriate Python type. There are a number of these callbacks defined on\nthe Redis client class in a dictionary called RESPONSE_CALLBACKS.\n\nCustom callbacks can be added on a per-instance basis using the\nset_response_callback method. This method accepts two arguments: a command\nname and the callback. Callbacks added in this manner are only valid on the\ninstance the callback is added to. If you want to define or override a callback\nglobally, you should make a subclass of the Redis client and add your callback\nto its RESPONSE_CALLBACKS class dictionary.\n\nResponse callbacks take at least one parameter: the response from the Redis\nserver. Keyword arguments may also be accepted in order to further control\nhow to interpret the response. These keyword arguments are specified during the\ncommand's call to execute_command. The ZRANGE implementation demonstrates the\nuse of response callback keyword arguments with its \"withscores\" argument.\n\nThread Safety\n^^^^^^^^^^^^^\n\nRedis client instances can safely be shared between threads. Internally,\nconnection instances are only retrieved from the connection pool during\ncommand execution, and returned to the pool directly after. Command execution\nnever modifies state on the client instance.\n\nHowever, there is one caveat: the Redis SELECT command. The SELECT command\nallows you to switch the database currently in use by the connection. That\ndatabase remains selected until another is selected or until the connection is\nclosed. This creates an issue in that connections could be returned to the pool\nthat are connected to a different database.\n\nAs a result, redis-py does not implement the SELECT command on client\ninstances. If you use multiple Redis databases within the same application, you\nshould create a separate client instance (and possibly a separate connection\npool) for each database.\n\nIt is not safe to pass PubSub or Pipeline objects between threads.\n\nPipelines\n^^^^^^^^^\n\nPipelines are a subclass of the base Redis class that provide support for\nbuffering multiple commands to the server in a single request. They can be used\nto dramatically increase the performance of groups of commands by reducing the\nnumber of back-and-forth TCP packets between the client and server.\n\nPipelines are quite simple to use:\n\n.. code-block:: pycon\n\n    >>> r = redis.Redis(...)\n    >>> r.set('bing', 'baz')\n    >>> # Use the pipeline() method to create a pipeline instance\n    >>> pipe = r.pipeline()\n    >>> # The following SET commands are buffered\n    >>> pipe.set('foo', 'bar')\n    >>> pipe.get('bing')\n    >>> # the EXECUTE call sends all buffered commands to the server, returning\n    >>> # a list of responses, one for each command.\n    >>> pipe.execute()\n    [True, 'baz']\n\nFor ease of use, all commands being buffered into the pipeline return the\npipeline object itself. Therefore calls can be chained like:\n\n.. code-block:: pycon\n\n    >>> pipe.set('foo', 'bar').sadd('faz', 'baz').incr('auto_number').execute()\n    [True, True, 6]\n\nIn addition, pipelines can also ensure the buffered commands are executed\natomically as a group. This happens by default. If you want to disable the\natomic nature of a pipeline but still want to buffer commands, you can turn\noff transactions.\n\n.. code-block:: pycon\n\n    >>> pipe = r.pipeline(transaction=False)\n\nA common issue occurs when requiring atomic transactions but needing to\nretrieve values in Redis prior for use within the transaction. For instance,\nlet's assume that the INCR command didn't exist and we need to build an atomic\nversion of INCR in Python.\n\nThe completely naive implementation could GET the value, increment it in\nPython, and SET the new value back. However, this is not atomic because\nmultiple clients could be doing this at the same time, each getting the same\nvalue from GET.\n\nEnter the WATCH command. WATCH provides the ability to monitor one or more keys\nprior to starting a transaction. If any of those keys change prior the\nexecution of that transaction, the entire transaction will be canceled and a\nWatchError will be raised. To implement our own client-side INCR command, we\ncould do something like this:\n\n.. code-block:: pycon\n\n    >>> with r.pipeline() as pipe:\n    ...     while True:\n    ...         try:\n    ...             # put a WATCH on the key that holds our sequence value\n    ...             pipe.watch('OUR-SEQUENCE-KEY')\n    ...             # after WATCHing, the pipeline is put into immediate execution\n    ...             # mode until we tell it to start buffering commands again.\n    ...             # this allows us to get the current value of our sequence\n    ...             current_value = pipe.get('OUR-SEQUENCE-KEY')\n    ...             next_value = int(current_value) + 1\n    ...             # now we can put the pipeline back into buffered mode with MULTI\n    ...             pipe.multi()\n    ...             pipe.set('OUR-SEQUENCE-KEY', next_value)\n    ...             # and finally, execute the pipeline (the set command)\n    ...             pipe.execute()\n    ...             # if a WatchError wasn't raised during execution, everything\n    ...             # we just did happened atomically.\n    ...             break\n    ...        except WatchError:\n    ...             # another client must have changed 'OUR-SEQUENCE-KEY' between\n    ...             # the time we started WATCHing it and the pipeline's execution.\n    ...             # our best bet is to just retry.\n    ...             continue\n\nNote that, because the Pipeline must bind to a single connection for the\nduration of a WATCH, care must be taken to ensure that the connection is\nreturned to the connection pool by calling the reset() method. If the\nPipeline is used as a context manager (as in the example above) reset()\nwill be called automatically. Of course you can do this the manual way by\nexplicitly calling reset():\n\n.. code-block:: pycon\n\n    >>> pipe = r.pipeline()\n    >>> while True:\n    ...     try:\n    ...         pipe.watch('OUR-SEQUENCE-KEY')\n    ...         ...\n    ...         pipe.execute()\n    ...         break\n    ...     except WatchError:\n    ...         continue\n    ...     finally:\n    ...         pipe.reset()\n\nA convenience method named \"transaction\" exists for handling all the\nboilerplate of handling and retrying watch errors. It takes a callable that\nshould expect a single parameter, a pipeline object, and any number of keys to\nbe WATCHed. Our client-side INCR command above can be written like this,\nwhich is much easier to read:\n\n.. code-block:: pycon\n\n    >>> def client_side_incr(pipe):\n    ...     current_value = pipe.get('OUR-SEQUENCE-KEY')\n    ...     next_value = int(current_value) + 1\n    ...     pipe.multi()\n    ...     pipe.set('OUR-SEQUENCE-KEY', next_value)\n    >>>\n    >>> r.transaction(client_side_incr, 'OUR-SEQUENCE-KEY')\n    [True]\n\nPublish / Subscribe\n^^^^^^^^^^^^^^^^^^^\n\nredis-py includes a `PubSub` object that subscribes to channels and listens\nfor new messages. Creating a `PubSub` object is easy.\n\n.. code-block:: pycon\n\n    >>> r = redis.Redis(...)\n    >>> p = r.pubsub()\n\nOnce a `PubSub` instance is created, channels and patterns can be subscribed\nto.\n\n.. code-block:: pycon\n\n    >>> p.subscribe('my-first-channel', 'my-second-channel', ...)\n    >>> p.psubscribe('my-*', ...)\n\nThe `PubSub` instance is now subscribed to those channels/patterns. The\nsubscription confirmations can be seen by reading messages from the `PubSub`\ninstance.\n\n.. code-block:: pycon\n\n    >>> p.get_message()\n    {'pattern': None, 'type': 'subscribe', 'channel': 'my-second-channel', 'data': 1L}\n    >>> p.get_message()\n    {'pattern': None, 'type': 'subscribe', 'channel': 'my-first-channel', 'data': 2L}\n    >>> p.get_message()\n    {'pattern': None, 'type': 'psubscribe', 'channel': 'my-*', 'data': 3L}\n\nEvery message read from a `PubSub` instance will be a dictionary with the\nfollowing keys.\n\n* **type**: One of the following: 'subscribe', 'unsubscribe', 'psubscribe',\n  'punsubscribe', 'message', 'pmessage'\n* **channel**: The channel [un]subscribed to or the channel a message was\n  published to\n* **pattern**: The pattern that matched a published message's channel. Will be\n  `None` in all cases except for 'pmessage' types.\n* **data**: The message data. With [un]subscribe messages, this value will be\n  the number of channels and patterns the connection is currently subscribed\n  to. With [p]message messages, this value will be the actual published\n  message.\n\nLet's send a message now.\n\n.. code-block:: pycon\n\n    # the publish method returns the number matching channel and pattern\n    # subscriptions. 'my-first-channel' matches both the 'my-first-channel'\n    # subscription and the 'my-*' pattern subscription, so this message will\n    # be delivered to 2 channels/patterns\n    >>> r.publish('my-first-channel', 'some data')\n    2\n    >>> p.get_message()\n    {'channel': 'my-first-channel', 'data': 'some data', 'pattern': None, 'type': 'message'}\n    >>> p.get_message()\n    {'channel': 'my-first-channel', 'data': 'some data', 'pattern': 'my-*', 'type': 'pmessage'}\n\nUnsubscribing works just like subscribing. If no arguments are passed to\n[p]unsubscribe, all channels or patterns will be unsubscribed from.\n\n.. code-block:: pycon\n\n    >>> p.unsubscribe()\n    >>> p.punsubscribe('my-*')\n    >>> p.get_message()\n    {'channel': 'my-second-channel', 'data': 2L, 'pattern': None, 'type': 'unsubscribe'}\n    >>> p.get_message()\n    {'channel': 'my-first-channel', 'data': 1L, 'pattern': None, 'type': 'unsubscribe'}\n    >>> p.get_message()\n    {'channel': 'my-*', 'data': 0L, 'pattern': None, 'type': 'punsubscribe'}\n\nredis-py also allows you to register callback functions to handle published\nmessages. Message handlers take a single argument, the message, which is a\ndictionary just like the examples above. To subscribe to a channel or pattern\nwith a message handler, pass the channel or pattern name as a keyword argument\nwith its value being the callback function.\n\nWhen a message is read on a channel or pattern with a message handler, the\nmessage dictionary is created and passed to the message handler. In this case,\na `None` value is returned from get_message() since the message was already\nhandled.\n\n.. code-block:: pycon\n\n    >>> def my_handler(message):\n    ...     print 'MY HANDLER: ', message['data']\n    >>> p.subscribe(**{'my-channel': my_handler})\n    # read the subscribe confirmation message\n    >>> p.get_message()\n    {'pattern': None, 'type': 'subscribe', 'channel': 'my-channel', 'data': 1L}\n    >>> r.publish('my-channel', 'awesome data')\n    1\n    # for the message handler to work, we need tell the instance to read data.\n    # this can be done in several ways (read more below). we'll just use\n    # the familiar get_message() function for now\n    >>> message = p.get_message()\n    MY HANDLER:  awesome data\n    # note here that the my_handler callback printed the string above.\n    # `message` is None because the message was handled by our handler.\n    >>> print message\n    None\n\nIf your application is not interested in the (sometimes noisy)\nsubscribe/unsubscribe confirmation messages, you can ignore them by passing\n`ignore_subscribe_messages=True` to `r.pubsub()`. This will cause all\nsubscribe/unsubscribe messages to be read, but they won't bubble up to your\napplication.\n\n.. code-block:: pycon\n\n    >>> p = r.pubsub(ignore_subscribe_messages=True)\n    >>> p.subscribe('my-channel')\n    >>> p.get_message()  # hides the subscribe message and returns None\n    >>> r.publish('my-channel', 'my data')\n    1\n    >>> p.get_message()\n    {'channel': 'my-channel', 'data': 'my data', 'pattern': None, 'type': 'message'}\n\nThere are three different strategies for reading messages.\n\nThe examples above have been using `pubsub.get_message()`. Behind the scenes,\n`get_message()` uses the system's 'select' module to quickly poll the\nconnection's socket. If there's data available to be read, `get_message()` will\nread it, format the message and return it or pass it to a message handler. If\nthere's no data to be read, `get_message()` will immediately return None. This\nmakes it trivial to integrate into an existing event loop inside your\napplication.\n\n.. code-block:: pycon\n\n    >>> while True:\n    >>>     message = p.get_message()\n    >>>     if message:\n    >>>         # do something with the message\n    >>>     time.sleep(0.001)  # be nice to the system :)\n\nOlder versions of redis-py only read messages with `pubsub.listen()`. listen()\nis a generator that blocks until a message is available. If your application\ndoesn't need to do anything else but receive and act on messages received from\nredis, listen() is an easy way to get up an running.\n\n.. code-block:: pycon\n\n    >>> for message in p.listen():\n    ...     # do something with the message\n\nThe third option runs an event loop in a separate thread.\n`pubsub.run_in_thread()` creates a new thread and starts the event loop. The\nthread object is returned to the caller of `run_in_thread()`. The caller can\nuse the `thread.stop()` method to shut down the event loop and thread. Behind\nthe scenes, this is simply a wrapper around `get_message()` that runs in a\nseparate thread, essentially creating a tiny non-blocking event loop for you.\n`run_in_thread()` takes an optional `sleep_time` argument. 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