diff --git a/README.rst b/README.rst
index 70ba3e5008..e9bd339fe2 100644
--- a/README.rst
+++ b/README.rst
@@ -24,144 +24,10 @@ Hazelcast Python client is a way to communicate to Hazelcast clusters
 and access the cluster data. The client provides a Future-based
 asynchronous API suitable for wide ranges of use cases.
 
-Installation
-------------
-
-Hazelcast
-~~~~~~~~~
-
-Hazelcast Python client requires a working Hazelcast cluster to run.
-This cluster handles the storage and manipulation of the user data.
-
-A Hazelcast cluster consists of one or more cluster members. These
-members generally run on multiple virtual or physical machines and are
-connected to each other via the network. Any data put on the cluster is
-partitioned to multiple members transparent to the user. It is therefore
-very easy to scale the system by adding new members as the data grows.
-Hazelcast cluster also offers resilience. Should any hardware or
-software problem causes a crash to any member, the data on that member
-is recovered from backups and the cluster continues to operate without
-any downtime.
-
-The quickest way to start a single member cluster for development
-purposes is to use our `Docker
-images <https://hub.docker.com/r/hazelcast/hazelcast/>`__.
-
-.. code:: bash
-
-   docker run -p 5701:5701 hazelcast/hazelcast:5.3.0
-
-You can also use our ZIP or TAR
-`distributions <https://hazelcast.com/open-source-projects/downloads/>`__.
-Once you have downloaded, you can start the Hazelcast member using
-the ``bin/hz-start`` script.
-
-Client
-~~~~~~
-
-.. code:: bash
-
-   pip install hazelcast-python-client
-
-Overview
---------
-
-Usage
-~~~~~
-
-.. code:: python
-
-    import hazelcast
-
-    # Connect to Hazelcast cluster.
-    client = hazelcast.HazelcastClient()
-
-    # Get or create the "distributed-map" on the cluster.
-    distributed_map = client.get_map("distributed-map")
-
-    # Put "key", "value" pair into the "distributed-map" and wait for
-    # the request to complete.
-    distributed_map.set("key", "value").result()
-
-    # Try to get the value associated with the given key from the cluster
-    # and attach a callback to be executed once the response for the
-    # get request is received. Note that, the set request above was
-    # blocking since it calls ".result()" on the returned Future, whereas
-    # the get request below is non-blocking.
-    get_future = distributed_map.get("key")
-    get_future.add_done_callback(lambda future: print(future.result()))
-
-    # Do other operations. The operations below won't wait for
-    # the get request above to complete.
-
-    print("Map size:", distributed_map.size().result())
-
-    # Shutdown the client.
-    client.shutdown()
-
-
-If you are using Hazelcast and the Python client on the same machine,
-the default configuration should work out-of-the-box. However,
-you may need to configure the client to connect to cluster nodes that
-are running on different machines or to customize client properties.
-
-Configuration
-~~~~~~~~~~~~~
-
-.. code:: python
-
-    import hazelcast
-
-    client = hazelcast.HazelcastClient(
-        cluster_name="cluster-name",
-        cluster_members=[
-            "10.90.0.2:5701",
-            "10.90.0.3:5701",
-        ],
-        lifecycle_listeners=[
-            lambda state: print("Lifecycle event >>>", state),
-        ]
-    )
-
-    print("Connected to cluster")
-    client.shutdown()
-
-
-Refer to `the documentation <https://hazelcast.readthedocs.io>`__
-to learn more about supported configuration options.
-
-Features
---------
-
--  Distributed, partitioned and queryable in-memory key-value store
-   implementation, called **Map**
--  Eventually consistent cache implementation to store a subset of the
-   Map data locally in the memory of the client, called **Near Cache**
--  Additional data structures and simple messaging constructs such as
-   **Set**, **MultiMap**, **Queue**, **Topic**
--  Cluster-wide unique ID generator, called **FlakeIdGenerator**
--  Distributed, CRDT based counter, called **PNCounter**
--  Distributed concurrency primitives from CP Subsystem such as
-   **FencedLock**, **Semaphore**, **AtomicLong**
--  Similarity search using **VectorCollection** (Beta)
--  Integration with `Hazelcast Cloud <https://cloud.hazelcast.com/>`__
--  Support for serverless and traditional web service architectures with
-   **Unisocket** and **Smart** operation modes
--  Ability to listen to client lifecycle, cluster state, and distributed
-   data structure events
--  and `many
-   more <https://hazelcast.com/clients/python/#client-features>`__
-
-Getting Help
-------------
-
-You can use the following channels for your questions and
-development/usage issues:
+For a list of the features available, and for information about how 
+to install and get started with the client, see the 
+`Python client documentation <https://docs.hazelcast.com/hazelcast/latest/clients/python>`__.
 
--  `GitHub
-   repository <https://github.com/hazelcast/hazelcast-python-client/issues/new>`__
--  `Documentation <https://hazelcast.readthedocs.io>`__
--  `Slack <https://slack.hazelcast.com>`__
 
 Contributing
 ------------