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GridGain Quick Start Guide for Python

This chapter explains system requirements for running GridGain and how to install GridGain, start a cluster, and run a simple Hello World example using a thin client for Python.

Thin Client is a lightweight GridGain connection mode. It does not participate in the cluster, never holds any data, or performs computations. All it does is establish a socket connection to an individual GridGain node and perform all operations through that node.

Since GridGain is built on top of Apache Ignite, GridGain reuses Ignite’s system properties, environment properties, startup scripts, etc. wherever possible.


GridGain was officially tested on:


Oracle JDK 8, 11 or 17, Open JDK 8, 11 or 17, IBM JDK 8, 11 or 17


Linux (any flavor), Mac OSX (10.6 and up), Windows (XP and up), Windows Server (2008 and up), Oracle Solaris, z/OS


x86, x64, SPARC, PowerPC


No restrictions (10G recommended)



Version 3.4 or above

Installing GridGain

GridGain is available in three editions: Community Edition (CE), Enterprise Edition (EE) and Ultimate Edition (UE). For this example, we’ll use the GridGain CE, which is distributed as binary, docker, and cloud images, and via RPM/DEB. This chapter explains how to install the GridGain CE binary distribution.

To get started with the GridGain CE binary distribution:

  1. Download the GridGain binary as a zip archive.

  2. Unzip the zip archive into the installation folder in your system.

  3. Move the ignite-rest-http folder from {gridgain}/libs/optional to {gridgain}/libs to enable the Ignite REST library for the cluster. The library is used by GridGain Nebula for cluster management and monitoring needs.

  4. (Optional) Enable required modules.

  5. (Optional) Set the IGNITE_HOME environment variable or Windows PATH to point to the installation folder and make sure there is no trailing / (or \ for Windows) in the path.

Once that’s done, execute the following command to install the Python Thin Client package. This thin client is abbreviated as pygridgain:

pip3 install pygridgain
pip install pygridgain

Starting a GridGain Node

Before connecting to GridGain via the Python thin client, you must start at least one GridGain cluster node.

You can start a GridGain node from the command line using the default configuration or by passing a custom configuration file. You can start as many nodes as you like and they will all automatically discover each other.

Navigate into the bin folder of GridGain installation directory from the command shell. Your command might look like this:

cd {gridgain}/bin/
cd {gridgain}\bin\

Start a node with a custom configuration file that is passed as a parameter to|bat like this:

./ ../examples/config/example-ignite.xml
ignite.bat ..\examples\config\example-ignite.xml

You will see output similar to this:

[08:53:45] Ignite node started OK (id=7b30bc8e)
[08:53:45] Topology snapshot [ver=1, locNode=7b30bc8e, servers=1, clients=0, state=ACTIVE, CPUs=4, offheap=1.6GB, heap=2.0GB]

Open another tab from your command shell and run the same command again:

./ ../examples/config/example-ignite.xml
ignite.bat ..\examples\config\example-ignite.xml

Check the Topology snapshot line in the output. Now you have a cluster of two server nodes with more CPUs and RAM available cluster-wide:

[08:54:34] Ignite node started OK (id=3a30b7a4)
[08:54:34] Topology snapshot [ver=2, locNode=3a30b7a4, servers=2, clients=0, state=ACTIVE, CPUs=4, offheap=3.2GB, heap=4.0GB]

Running Your First GridGain Application

Once the cluster is started, you can use the GridGain Python thin client to perform cache operations.

Assuming that the server node is running locally, here is a HelloWorld example that puts and gets values from the cache:

from pygridgain import Client

client = Client()
client.connect('', 10800)

#Create cache
my_cache = client.create_cache('my cache')

#Put value in cache
my_cache.put(1, 'Hello World')

#Get value from cache
result = my_cache.get(1)

To run this, you can save the example as a text file ( for example) and run it from the command line:


Or you can enter the example into your Python interpreter/shell (IDLE on Windows, for example) and modify/execute it there.