Install GX

GX Core is a Python library. Follow the instructions in this guide to install GX Core in your local Python environment, or as a notebook-scoped library in hosted environments such as EMR Spark clusters.

Prerequisites

• Python version 3.10 to 3.13
• Recommended. A Python virtual environment
• Internet access
• Permissions to download and install packages in your environment

Install the GX Python library

Local

GX Core is a Python library and as such can be used with a local Python installation to access the functionality of GX through Python scripts.

Installation and setup

1. Optional. Activate your virtual environment.

   If you created a virtual environment for your GX Python installation, browse to the folder that contains your virtual environment and run the following command to activate it:

   Terminal input

   source my_venv/bin/activate

2. Ensure you have the latest version of pip:

   Terminal input

   python -m ensurepip --upgrade

3. Install the GX Core library:

   Terminal input

   pip install great_expectations

4. Verify that GX installed successfully.

   In Python, run the following code:

   Python

   import great_expectations as gx
   
   print(gx.__version__)

   If GX was installed correctly, the version number of the installed GX library will be printed.

Hosted environment

Hosted environments such as EMR Spark do not provide a filesystem to install your GX Core instance. Instead, you must install GX Core in memory using the Python-style notebooks available on those platforms.

Use the information provided here to install GX on an EMR Spark cluster and instantiate a Data Context without a full configuration directory.

Additional prerequisites

• An EMR Spark cluster.
• Access to the EMR Spark notebook.

Installation and setup

1. To install GX on your EMR Spark cluster copy this code snippet into a cell in your EMR Spark notebook and then run it:

   Python

   sc.install_pypi_package("great_expectations")

2. Create an in-code Data Context. See Instantiate an Ephemeral Data Context.

3. Copy the Python code at the end of How to instantiate an Ephemeral Data Context into a cell in your EMR Spark notebook, or use the other examples to customize your configuration. The code instantiates and configures a Data Context for an EMR Spark cluster.

4. Execute the cell with your Data Context initialization and configuration.

5. Run the following command to verify that GX was installed and your in-memory Data Context was instantiated successfully:

   Python

      context.list_datasources()