Metadata-Version: 1.1
Name: redis
Version: 2.8.0
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).
        
        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]
        
        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]
        
        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 :: 2.5
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
