python-redis 2.10.1-1 / usr / share / pyshared / redis-2.10.1.egg-info / PKG-INFO

Metadata-Version: 1.1
Name: redis
Version: 2.10.1
Summary: Python client for Redis key-value store
Home-page: http://github.com/andymccurdy/redis-py
Author: Andy McCurdy
Author-email: sedrik@gmail.com
License: MIT
Description: redis-py
        ========
        
        The Python interface to the Redis key-value store.
        
        .. image:: https://secure.travis-ci.org/andymccurdy/redis-py.png?branch=master
                :target: http://travis-ci.org/andymccurdy/redis-py
        
        Installation
        ------------
        
        redis-py requires a running Redis server. See `Redis's quickstart
        <http://redis.io/topics/quickstart>`_ for installation instructions.
        
        To install redis-py, simply:
        
        .. code-block:: bash
        
            $ sudo pip install redis
        
        or alternatively (you really should be using pip though):
        
        .. code-block:: bash
        
            $ sudo easy_install redis
        
        or from source:
        
        .. code-block:: bash
        
            $ sudo python setup.py install
        
        
        Getting Started
        ---------------
        
        .. code-block:: pycon
        
            >>> import redis
            >>> r = redis.StrictRedis(host='localhost', port=6379, db=0)
            >>> r.set('foo', 'bar')
            True
            >>> r.get('foo')
            'bar'
        
        API Reference
        -------------
        
        The `official Redis command documentation <http://redis.io/commands>`_ does a
        great job of explaining each command in detail. redis-py exposes two client
        classes that implement these commands. The StrictRedis class attempts to adhere
        to the official command syntax. There are a few exceptions:
        
        * **SELECT**: Not implemented. See the explanation in the Thread Safety section
          below.
        * **DEL**: 'del' is a reserved keyword in the Python syntax. Therefore redis-py
          uses 'delete' instead.
        * **CONFIG GET|SET**: These are implemented separately as config_get or config_set.
        * **MULTI/EXEC**: These are implemented as part of the Pipeline class. The
          pipeline is wrapped with the MULTI and EXEC statements by default when it
          is executed, which can be disabled by specifying transaction=False.
          See more about Pipelines below.
        * **SUBSCRIBE/LISTEN**: Similar to pipelines, PubSub is implemented as a separate
          class as it places the underlying connection in a state where it can't
          execute non-pubsub commands. Calling the pubsub method from the Redis client
          will return a PubSub instance where you can subscribe to channels and listen
          for messages. You can only call PUBLISH from the Redis client (see
          `this comment on issue #151
          <https://github.com/andymccurdy/redis-py/issues/151#issuecomment-1545015>`_
          for details).
        * **SCAN/SSCAN/HSCAN/ZSCAN**: The *SCAN commands are implemented as they
          exist in the Redis documentation. In addition, each command has an equivilant
          iterator method. These are purely for convenience so the user doesn't have
          to keep track of the cursor while iterating. Use the
          scan_iter/sscan_iter/hscan_iter/zscan_iter methods for this behavior.
        
        In addition to the changes above, the Redis class, a subclass of StrictRedis,
        overrides several other commands to provide backwards compatibility with older
        versions of redis-py:
        
        * **LREM**: Order of 'num' and 'value' arguments reversed such that 'num' can
          provide a default value of zero.
        * **ZADD**: Redis specifies the 'score' argument before 'value'. These were swapped
          accidentally when being implemented and not discovered until after people
          were already using it. The Redis class expects \*args in the form of:
          `name1, score1, name2, score2, ...`
        * **SETEX**: Order of 'time' and 'value' arguments reversed.
        
        
        More Detail
        -----------
        
        Connection Pools
        ^^^^^^^^^^^^^^^^
        
        Behind the scenes, redis-py uses a connection pool to manage connections to
        a Redis server. By default, each Redis instance you create will in turn create
        its own connection pool. You can override this behavior and use an existing
        connection pool by passing an already created connection pool instance to the
        connection_pool argument of the Redis class. You may choose to do this in order
        to implement client side sharding or have finer grain control of how
        connections are managed.
        
        .. code-block:: pycon
        
            >>> pool = redis.ConnectionPool(host='localhost', port=6379, db=0)
            >>> r = redis.Redis(connection_pool=pool)
        
        Connections
        ^^^^^^^^^^^
        
        ConnectionPools manage a set of Connection instances. redis-py ships with two
        types of Connections. The default, Connection, is a normal TCP socket based
        connection. The UnixDomainSocketConnection allows for clients running on the
        same device as the server to connect via a unix domain socket. To use a
        UnixDomainSocketConnection connection, simply pass the unix_socket_path
        argument, which is a string to the unix domain socket file. Additionally, make
        sure the unixsocket parameter is defined in your redis.conf file. It's
        commented out by default.
        
        .. code-block:: pycon
        
            >>> r = redis.Redis(unix_socket_path='/tmp/redis.sock')
        
        You can create your own Connection subclasses as well. This may be useful if
        you want to control the socket behavior within an async framework. To
        instantiate a client class using your own connection, you need to create
        a connection pool, passing your class to the connection_class argument.
        Other keyword parameters your pass to the pool will be passed to the class
        specified during initialization.
        
        .. code-block:: pycon
        
            >>> pool = redis.ConnectionPool(connection_class=YourConnectionClass,
                                            your_arg='...', ...)
        
        Parsers
        ^^^^^^^
        
        Parser classes provide a way to control how responses from the Redis server
        are parsed. redis-py ships with two parser classes, the PythonParser and the
        HiredisParser. By default, redis-py will attempt to use the HiredisParser if
        you have the hiredis module installed and will fallback to the PythonParser
        otherwise.
        
        Hiredis is a C library maintained by the core Redis team. Pieter Noordhuis was
        kind enough to create Python bindings. Using Hiredis can provide up to a
        10x speed improvement in parsing responses from the Redis server. The
        performance increase is most noticeable when retrieving many pieces of data,
        such as from LRANGE or SMEMBERS operations.
        
        Hiredis is available on PyPI, and can be installed via pip or easy_install
        just like redis-py.
        
        .. code-block:: bash
        
            $ pip install hiredis
        
        or
        
        .. code-block:: bash
        
            $ easy_install hiredis
        
        Response Callbacks
        ^^^^^^^^^^^^^^^^^^
        
        The client class uses a set of callbacks to cast Redis responses to the
        appropriate Python type. There are a number of these callbacks defined on
        the Redis client class in a dictionary called RESPONSE_CALLBACKS.
        
        Custom callbacks can be added on a per-instance basis using the
        set_response_callback method. This method accepts two arguments: a command
        name and the callback. Callbacks added in this manner are only valid on the
        instance the callback is added to. If you want to define or override a callback
        globally, you should make a subclass of the Redis client and add your callback
        to its REDIS_CALLBACKS class dictionary.
        
        Response callbacks take at least one parameter: the response from the Redis
        server. Keyword arguments may also be accepted in order to further control
        how to interpret the response. These keyword arguments are specified during the
        command's call to execute_command. The ZRANGE implementation demonstrates the
        use of response callback keyword arguments with its "withscores" argument.
        
        Thread Safety
        ^^^^^^^^^^^^^
        
        Redis client instances can safely be shared between threads. Internally,
        connection instances are only retrieved from the connection pool during
        command execution, and returned to the pool directly after. Command execution
        never modifies state on the client instance.
        
        However, there is one caveat: the Redis SELECT command. The SELECT command
        allows you to switch the database currently in use by the connection. That
        database remains selected until another is selected or until the connection is
        closed. This creates an issue in that connections could be returned to the pool
        that are connected to a different database.
        
        As a result, redis-py does not implement the SELECT command on client
        instances. If you use multiple Redis databases within the same application, you
        should create a separate client instance (and possibly a separate connection
        pool) for each database.
        
        It is not safe to pass PubSub or Pipeline objects between threads.
        
        Pipelines
        ^^^^^^^^^
        
        Pipelines are a subclass of the base Redis class that provide support for
        buffering multiple commands to the server in a single request. They can be used
        to dramatically increase the performance of groups of commands by reducing the
        number of back-and-forth TCP packets between the client and server.
        
        Pipelines are quite simple to use:
        
        .. code-block:: pycon
        
            >>> r = redis.Redis(...)
            >>> r.set('bing', 'baz')
            >>> # Use the pipeline() method to create a pipeline instance
            >>> pipe = r.pipeline()
            >>> # The following SET commands are buffered
            >>> pipe.set('foo', 'bar')
            >>> pipe.get('bing')
            >>> # the EXECUTE call sends all buffered commands to the server, returning
            >>> # a list of responses, one for each command.
            >>> pipe.execute()
            [True, 'baz']
        
        For ease of use, all commands being buffered into the pipeline return the
        pipeline object itself. Therefore calls can be chained like:
        
        .. code-block:: pycon
        
            >>> pipe.set('foo', 'bar').sadd('faz', 'baz').incr('auto_number').execute()
            [True, True, 6]
        
        In addition, pipelines can also ensure the buffered commands are executed
        atomically as a group. This happens by default. If you want to disable the
        atomic nature of a pipeline but still want to buffer commands, you can turn
        off transactions.
        
        .. code-block:: pycon
        
            >>> pipe = r.pipeline(transaction=False)
        
        A common issue occurs when requiring atomic transactions but needing to
        retrieve values in Redis prior for use within the transaction. For instance,
        let's assume that the INCR command didn't exist and we need to build an atomic
        version of INCR in Python.
        
        The completely naive implementation could GET the value, increment it in
        Python, and SET the new value back. However, this is not atomic because
        multiple clients could be doing this at the same time, each getting the same
        value from GET.
        
        Enter the WATCH command. WATCH provides the ability to monitor one or more keys
        prior to starting a transaction. If any of those keys change prior the
        execution of that transaction, the entire transaction will be canceled and a
        WatchError will be raised. To implement our own client-side INCR command, we
        could do something like this:
        
        .. code-block:: pycon
        
            >>> with r.pipeline() as pipe:
            ...     while 1:
            ...         try:
            ...             # put a WATCH on the key that holds our sequence value
            ...             pipe.watch('OUR-SEQUENCE-KEY')
            ...             # after WATCHing, the pipeline is put into immediate execution
            ...             # mode until we tell it to start buffering commands again.
            ...             # this allows us to get the current value of our sequence
            ...             current_value = pipe.get('OUR-SEQUENCE-KEY')
            ...             next_value = int(current_value) + 1
            ...             # now we can put the pipeline back into buffered mode with MULTI
            ...             pipe.multi()
            ...             pipe.set('OUR-SEQUENCE-KEY', next_value)
            ...             # and finally, execute the pipeline (the set command)
            ...             pipe.execute()
            ...             # if a WatchError wasn't raised during execution, everything
            ...             # we just did happened atomically.
            ...             break
            ...        except WatchError:
            ...             # another client must have changed 'OUR-SEQUENCE-KEY' between
            ...             # the time we started WATCHing it and the pipeline's execution.
            ...             # our best bet is to just retry.
            ...             continue
        
        Note that, because the Pipeline must bind to a single connection for the
        duration of a WATCH, care must be taken to ensure that the connection is
        returned to the connection pool by calling the reset() method. If the
        Pipeline is used as a context manager (as in the example above) reset()
        will be called automatically. Of course you can do this the manual way by
        explicity calling reset():
        
        .. code-block:: pycon
        
            >>> pipe = r.pipeline()
            >>> while 1:
            ...     try:
            ...         pipe.watch('OUR-SEQUENCE-KEY')
            ...         ...
            ...         pipe.execute()
            ...         break
            ...     except WatchError:
            ...         continue
            ...     finally:
            ...         pipe.reset()
        
        A convenience method named "transaction" exists for handling all the
        boilerplate of handling and retrying watch errors. It takes a callable that
        should expect a single parameter, a pipeline object, and any number of keys to
        be WATCHed. Our client-side INCR command above can be written like this,
        which is much easier to read:
        
        .. code-block:: pycon
        
            >>> def client_side_incr(pipe):
            ...     current_value = pipe.get('OUR-SEQUENCE-KEY')
            ...     next_value = int(current_value) + 1
            ...     pipe.multi()
            ...     pipe.set('OUR-SEQUENCE-KEY', next_value)
            >>>
            >>> r.transaction(client_side_incr, 'OUR-SEQUENCE-KEY')
            [True]
        
        Publish / Subscribe
        ^^^^^^^^^^^^^^^^^^^
        
        redis-py includes a `PubSub` object that subscribes to channels and listens
        for new messages. Creating a `PubSub` object is easy.
        
        .. code-block:: pycon
        
            >>> r = redis.StrictRedis(...)
            >>> p = r.pubsub()
        
        Once a `PubSub` instance is created, channels and patterns can be subscribed
        to.
        
        .. code-block:: pycon
        
            >>> p.subscribe('my-first-channel', 'my-second-channel', ...)
            >>> p.psubscribe('my-*', ...)
        
        The `PubSub` instance is now subscribed to those channels/patterns. The
        subscription confirmations can be seen by reading messages from the `PubSub`
        instance.
        
        .. code-block:: pycon
        
            >>> p.get_message()
            {'pattern': None, 'type': 'subscribe', 'channel': 'my-second-channel', 'data': 1L}
            >>> p.get_message()
            {'pattern': None, 'type': 'subscribe', 'channel': 'my-first-channel', 'data': 2L}
            >>> p.get_message()
            {'pattern': None, 'type': 'psubscribe', 'channel': 'my-*', 'data': 3L}
        
        Every message read from a `PubSub` instance will be a dictionary with the
        following keys.
        
        * **type**: One of the following: 'subscribe', 'unsubscribe', 'psubscribe',
          'punsubscribe', 'message', 'pmessage'
        * **channel**: The channel [un]subscribed to or the channel a message was
          published to
        * **pattern**: The pattern that matched a published message's channel. Will be
          `None` in all cases except for 'pmessage' types.
        * **data**: The message data. With [un]subscribe messages, this value will be
          the number of channels and patterns the connection is currently subscribed
          to. With [p]message messages, this value will be the actual published
          message.
        
        Let's send a message now.
        
        .. code-block:: pycon
        
            # the publish method returns the number matching channel and pattern
            # subscriptions. 'my-first-channel' matches both the 'my-first-channel'
            # subscription and the 'my-*' pattern subscription, so this message will
            # be delivered to 2 channels/patterns
            >>> r.publish('my-first-channel', 'some data')
            2
            >>> p.get_message()
            {'channel': 'my-first-channel', 'data': 'some data', 'pattern': None, 'type': 'message'}
            >>> p.get_message()
            {'channel': 'my-first-channel', 'data': 'some data', 'pattern': 'my-*', 'type': 'pmessage'}
        
        Unsubscribing works just like subscribing. If no arguments are passed to
        [p]unsubscribe, all channels or patterns will be unsubscribed from.
        
        .. code-block:: pycon
        
            >>> p.unsubscribe()
            >>> p.punsubscribe('my-*')
            >>> p.get_message()
            {'channel': 'my-second-channel', 'data': 2L, 'pattern': None, 'type': 'unsubscribe'}
            >>> p.get_message()
            {'channel': 'my-first-channel', 'data': 1L, 'pattern': None, 'type': 'unsubscribe'}
            >>> p.get_message()
            {'channel': 'my-*', 'data': 0L, 'pattern': None, 'type': 'punsubscribe'}
        
        redis-py also allows you to register callback functions to handle published
        messages. Message handlers take a single argument, the message, which is a
        dictionary just like the examples above. To subscribe to a channel or pattern
        with a message handler, pass the channel or pattern name as a keyword argument
        with its value being the callback function.
        
        When a message is read on a channel or pattern with a message handler, the
        message dictionary is created and passed to the message handler. In this case,
        a `None` value is returned from get_message() since the message was already
        handled.
        
        .. code-block:: pycon
        
            >>> def my_handler(message):
            ...     print 'MY HANDLER: ', message['data']
            >>> p.subscribe(**{'my-channel': my_handler})
            # read the subscribe confirmation message
            >>> p.get_message()
            {'pattern': None, 'type': 'subscribe', 'channel': 'my-channel', 'data': 1L}
            >>> r.publish('my-channel', 'awesome data')
            1
            # for the message handler to work, we need tell the instance to read data.
            # this can be done in several ways (read more below). we'll just use
            # the familiar get_message() function for now
            >>> message = p.get_message()
            MY HANDLER:  awesome data
            # note here that the my_handler callback printed the string above.
            # `message` is None because the message was handled by our handler.
            >>> print message
            None
        
        If your application is not interested in the (sometimes noisy)
        subscribe/unsubscribe confirmation messages, you can ignore them by passing
        `ignore_subscribe_messages=True` to `r.pubsub()`. This will cause all
        subscribe/unsubscribe messages to be read, but they won't bubble up to your
        application.
        
        .. code-block:: pycon
        
            >>> p = r.pubsub(ignore_subscribe_messages=True)
            >>> p.subscribe('my-channel')
            >>> p.get_message()  # hides the subscribe message and returns None
            >>> r.publish('my-channel')
            1
            >>> p.get_message()
            {'channel': 'my-channel', data': 'my data', 'pattern': None, 'type': 'message'}
        
        There are three different strategies for reading messages.
        
        The examples above have been using `pubsub.get_message()`. Behind the scenes,
        `get_message()` uses the system's 'select' module to quickly poll the
        connection's socket. If there's data available to be read, `get_message()` will
        read it, format the message and return it or pass it to a message handler. If
        there's no data to be read, `get_message()` will immediately return None. This
        makes it trivial to integrate into an existing event loop inside your
        application.
        
        .. code-block:: pycon
        
            >>> while True:
            >>>     message = p.get_message()
            >>>     if message:
            >>>         # do something with the message
            >>>     time.sleep(0.001)  # be nice to the system :)
        
        Older versions of redis-py only read messages with `pubsub.listen()`. listen()
        is a generator that blocks until a message is available. If your application
        doesn't need to do anything else but receive and act on messages received from
        redis, listen() is an easy way to get up an running.
        
        .. code-block:: pycon
        
            >>> for message in p.listen():
            ...     # do something with the message
        
        The third option runs an event loop in a separate thread.
        `pubsub.run_in_thread()` creates a new thread and starts the event loop. The
        thread object is returned to the caller of `run_in_thread()`. The caller can
        use the `thread.stop()` method to shut down the event loop and thread. Behind
        the scenes, this is simply a wrapper around `get_message()` that runs in a
        separate thread, essentially creating a tiny non-blocking event loop for you.
        `run_in_thread()` takes an optional `sleep_time` argument. If specified, the
        event loop will call `time.sleep()` with the value in each iteration of the
        loop.
        
        Note: Since we're running in a separate thread, there's no way to handle
        messages that aren't automatically handled with registered message handlers.
        Therefore, redis-py prevents you from calling `run_in_thread()` if you're
        subscribed to patterns or channels that don't have message handlers attached.
        
        .. code-block:: pycon
        
            >>> p.subscribe(**{'my-channel': my_handler})
            >>> thread = p.run_in_thread(sleep_time=0.001)
            # the event loop is now running in the background processing messages
            # when it's time to shut it down...
            >>> thread.stop()
        
        A PubSub object adheres to the same encoding semantics as the client instance
        it was created from. Any channel or pattern that's unicode will be encoded
        using the `charset` specified on the client before being sent to Redis. If the
        client's `decode_responses` flag is set the False (the default), the
        'channel', 'pattern' and 'data' values in message dictionaries will be byte
        strings (str on Python 2, bytes on Python 3). If the client's
        `decode_responses` is True, then the 'channel', 'pattern' and 'data' values
        will be automatically decoded to unicode strings using the client's `charset`.
        
        PubSub objects remember what channels and patterns they are subscribed to. In
        the event of a disconnection such as a network error or timeout, the
        PubSub object will re-subscribe to all prior channels and patterns when
        reconnecting. Messages that were published while the client was disconnected
        cannot be delivered. When you're finished with a PubSub object, call its
        `.close()` method to shutdown the connection.
        
        .. code-block:: pycon
        
            >>> p = r.pubsub()
            >>> ...
            >>> p.close()
        
        LUA Scripting
        ^^^^^^^^^^^^^
        
        redis-py supports the EVAL, EVALSHA, and SCRIPT commands. However, there are
        a number of edge cases that make these commands tedious to use in real world
        scenarios. Therefore, redis-py exposes a Script object that makes scripting
        much easier to use.
        
        To create a Script instance, use the `register_script` function on a client
        instance passing the LUA code as the first argument. `register_script` returns
        a Script instance that you can use throughout your code.
        
        The following trivial LUA script accepts two parameters: the name of a key and
        a multiplier value. The script fetches the value stored in the key, multiplies
        it with the multiplier value and returns the result.
        
        .. code-block:: pycon
        
            >>> r = redis.StrictRedis()
            >>> lua = """
            ... local value = redis.call('GET', KEYS[1])
            ... value = tonumber(value)
            ... return value * ARGV[1]"""
            >>> multiply = r.register_script(lua)
        
        `multiply` is now a Script instance that is invoked by calling it like a
        function. Script instances accept the following optional arguments:
        
        * **keys**: A list of key names that the script will access. This becomes the
          KEYS list in LUA.
        * **args**: A list of argument values. This becomes the ARGV list in LUA.
        * **client**: A redis-py Client or Pipeline instance that will invoke the
          script. If client isn't specified, the client that intiially
          created the Script instance (the one that `register_script` was
          invoked from) will be used.
        
        Continuing the example from above:
        
        .. code-block:: pycon
        
            >>> r.set('foo', 2)
            >>> multiply(keys=['foo'], args=[5])
            10
        
        The value of key 'foo' is set to 2. When multiply is invoked, the 'foo' key is
        passed to the script along with the multiplier value of 5. LUA executes the
        script and returns the result, 10.
        
        Script instances can be executed using a different client instance, even one
        that points to a completely different Redis server.
        
        .. code-block:: pycon
        
            >>> r2 = redis.StrictRedis('redis2.example.com')
            >>> r2.set('foo', 3)
            >>> multiply(keys=['foo'], args=[5], client=r2)
            15
        
        The Script object ensures that the LUA script is loaded into Redis's script
        cache. In the event of a NOSCRIPT error, it will load the script and retry
        executing it.
        
        Script objects can also be used in pipelines. The pipeline instance should be
        passed as the client argument when calling the script. Care is taken to ensure
        that the script is registered in Redis's script cache just prior to pipeline
        execution.
        
        .. code-block:: pycon
        
            >>> pipe = r.pipeline()
            >>> pipe.set('foo', 5)
            >>> multiply(keys=['foo'], args=[5], client=pipe)
            >>> pipe.execute()
            [True, 25]
        
        Sentinel support
        ^^^^^^^^^^^^^^^^
        
        redis-py can be used together with `Redis Sentinel <http://redis.io/topics/sentinel>`_
        to discover Redis nodes. You need to have at least one Sentinel daemon running
        in order to use redis-py's Sentinel support.
        
        Connecting redis-py to the Sentinel instance(s) is easy. You can use a
        Sentinel connection to discover the master and slaves network addresses:
        
        .. code-block:: pycon
        
            >>> from redis.sentinel import Sentinel
            >>> sentinel = Sentinel([('localhost', 26379)], socket_timeout=0.1)
            >>> sentinel.discover_master('mymaster')
            ('127.0.0.1', 6379)
            >>> sentinel.discover_slaves('mymaster')
            [('127.0.0.1', 6380)]
        
        You can also create Redis client connections from a Sentinel instnace. You can
        connect to either the master (for write operations) or a slave (for read-only
        operations).
        
        .. code-block:: pycon
        
            >>> master = sentinel.master_for('mymaster', socket_timeout=0.1)
            >>> slave = sentinel.slave_for('mymaster', socket_timeout=0.1)
            >>> master.set('foo', 'bar')
            >>> slave.get('foo')
            'bar'
        
        The master and slave objects are normal StrictRedis instances with their
        connection pool bound to the Sentinel instance. When a Sentinel backed client
        attempts to establish a connection, it first queries the Sentinel servers to
        determine an appropriate host to connect to. If no server is found,
        a MasterNotFoundError or SlaveNotFoundError is raised. Both exceptions are
        subclasses of ConnectionError.
        
        When trying to connect to a slave client, the Sentinel connection pool will
        iterate over the list of slaves until it finds one that can be connected to.
        If no slaves can be connected to, a connection will be established with the
        master.
        
        See `Guidelines for Redis clients with support for Redis Sentinel
        <http://redis.io/topics/sentinel-clients>`_ to learn more about Redis Sentinel.
        
        Scan Iterators
        ^^^^^^^^^^^^^^
        
        The *SCAN commands introduced in Redis 2.8 can be cumbersome to use. While
        these commands are fully supported, redis-py also exposes the following methods
        that return Python iterators for convenience: `scan_iter`, `hscan_iter`,
        `sscan_iter` and `zscan_iter`.
        
        .. code-block:: pycon
        
            >>> for key, value in (('A', '1'), ('B', '2'), ('C', '3')):
            ...     r.set(key, value)
            >>> for key in r.scan_iter():
            ...     print key, r.get(key)
            A 1
            B 2
            C 3
        
        Author
        ^^^^^^
        
        redis-py is developed and maintained by Andy McCurdy (sedrik@gmail.com).
        It can be found here: http://github.com/andymccurdy/redis-py
        
        Special thanks to:
        
        * Ludovico Magnocavallo, author of the original Python Redis client, from
          which some of the socket code is still used.
        * Alexander Solovyov for ideas on the generic response callback system.
        * Paul Hubbard for initial packaging support.
        
        
Keywords: Redis,key-value store
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4