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.
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Added June 8, 2026
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---
name: "Great Expectations Data Validation Pipeline"
slug: "great-expectations-data-validation-pipeline"
description: "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."
github_stars: 11321
verification: "security_reviewed"
source: "https://github.com/great-expectations/great_expectations"
category: "Code Quality & Review"
framework: "Claude Code"
tool_ecosystem:
github_repo: "great-expectations/great_expectations"
github_stars: 11321
---
# 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:
- [](https://pypi.python.org/pypi/great_expectations)
- 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](https://docs.greatexpectations.io/docs/core/introduction/).
- 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
## Source
- [Agent Skill Exchange](https://agentskillexchange.com/skills/great-expectations-data-validation-pipeline/)
