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Decision brief
Great Expectations is a Python library that helps maintain data quality through unit testing mechanisms known as expectations.
Good fit when
- When you need detailed and automated documentation for each set of validation results to simplify your data quality processes while preserving institutional knowledge.
- If your team values a common language and intuitive way to express data quality tests, which fosters collaboration within the team.
Avoid when
- For environments that strictly require adherence to Python versions 3.9 or lower, since Great Expectations supports only 3.10 through 3.13 natively.
- If your data integration requirements are not compatible with those listed in the Great Expectations compatibility reference.
- Requirements:
- Supports Python versions 3.10 through 3.13, with experimental support for Python 3.14 and later via an environment variable.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- 51 low (51 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install great_expectationsSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
GX Core is a Python-based toolset for validating and testing data quality using expectations that serve as unit tests for data.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Aug 2, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 2, 2026)
GX Core supports Python `3.10` through `3.13`.Source link
Tags
README
About GX Core
GX Core combines the collective wisdom of thousands of community members with a proven track record in data quality deployments worldwide, wrapped into a super-simple package for data teams.
Its powerful technical tools start with Expectations: expressive and extensible unit tests for your data. Expectations foster collaboration by giving teams a common language to express data quality tests in an intuitive way. You can automatically generate documentation for each set of validation results, making it easy for everyone to stay on the same page. This not only simplifies your data quality processes, but helps preserve your organization’s institutional knowledge about its data.
Learn more about how data teams are using GX Core in our featured case studies.
Integration support policy
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.
For data sources and other integrations that GX supports, see the compatibility reference for additional information.
Get started
GX recommends deploying GX Core within a virtual environment. For more information about getting started with GX Core, see Introduction to GX Core.
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Run the following command in an empty base directory inside a Python virtual environment to install GX Core:
pip install great_expectations -
Run the following command to import the
great_expectations moduleand create a Data Context:import great_expectations as gx context = gx.get_context()
Get support from GX and the community
They are listed in the order in which GX is prioritizing the support issues:
- Issues and PRs in the GX GitHub repository
- Questions posted to the GX Core Discourse forum
- Questions posted to the GX Slack community channel
Contribute
We truly value the contributions of our community and always welcome pull requests. PRs are encouraged for both bug fixes and new features. For feature requests, we ask that you first open an issue for discussion to ensure the feature fits within the vision for GX Core and to align on the approach so that your time and effort are well spent. Thank you for being a crucial part of GX Core!
See CONTRIBUTING.md for details on how to propose a change, claim an issue, and submit a pull request.
Code of conduct
Everyone interacting in GX Core project codebases, Discourse forums, Slack channels, and email communications is expected to adhere to the GX Community Code of Conduct.
For agents
This page has a .md twin and JSON over the API.