Straightforward data validation since the Jurassic.
This is a work in progress, use it at your own risk!
- Intuitive and simple to use - the opposite of Great Expectations
- Consistently structured - e.g., don't make type checks and value checks behave differently (looking at you Pandera)
- Focused on doing one thing well - loading, partitioning, reporting, etc. belong to others
- 100% coverage of Great Expectations core
- Foundational interfaces:
ExpectationandRunner - Initial Pandas support:
PandasRunner, 22% coverage of core expectations - Initial Polars support
- Initial PySpark support
- Compatability package that allows users to define expectations exactly how they're defined in Great Expectations
- 100% coverage of single-column expectations from Great Expectations
- 100% coverage of multi-column expectations from Great Expectations