python-pandera provides a flexible and expressive API for performing data validation on dataframe-like objects to make data processing pipelines more readable and robust. Dataframes contain information that python-pandera explicitly validates at runtime. This is useful in production-critical data pipelines or reproducible research settings. With python-pandera, you can:
Define a schema once and use it to validate different dataframe types.
Check the types and properties of columns.
Perform more complex statistical validation like hypothesis testing.
Seamlessly integrate with existing data pipelines via function decorators.
Define dataframe models with the class-based API with pydantic-style syntax.
Synthesize data from schema objects for property-based testing.
Lazily validate dataframes so that all validation rules are executed.
Integrate with a rich ecosystem of tools like
python-pydantic,python-fastapiandpython-mypy.