agentskillexchange Great Expectations Data Validation Pipeline
Validate data quality using the Great Expectations Python library. Define expectations as unit tests for your data, run validation suites, and generate human-readable data quality reports.
Installation
Use the upstream install or setup path that matches your environment:
- pip install great_expectations
Requirements and caveats from upstream:
- GX Core supports Python 3.10 through 3.13.
- Experimental support for Python 3.14 and later can be enabled by setting a GX_PYTHON_EXPERIMENTAL environment variable when installing great_expectations.
Basic usage or getting-started notes:
GX recommends deploying GX Core within a virtual environment. For more information about getting started with GX Core, see Introduction to GX Core.
Run the following command to import the great_expectations module and create a Data Context:
Source: https://github.com/great-expectations/great_expectations
Extracted from upstream docs: https://raw.githubusercontent.com/great-expectations/great_expectations/HEAD/README.md