StatGuardian
Python library for data quality and validation
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StatGuardian - Python library for data quality and validation

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Python library for data quality and validation — declarative contract DSL, schema checks, drift detection, anomaly detection. 13× faster than pandera. PyPI: statguardian - Mullassery/Statguardian

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Hunter
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After working with analytics and AI systems, I realized that successful pipelines don't always mean healthy data. StatGuardian was built to detect metric drift, anomalies, and unusual behavior automatically, so teams can trust their data and act faster.

love that the declarative DSL keeps schema checks and drift detection in the same mental model instead of splitting them across separate configs. the 13x speed claim against pandera is wild too, curious what tradeoff got you there.

the drift detection caught a real issue in my pipeline on the first run, which pandera never flagged. really clean DSL too, felt like writing tests more than writing validation code.

The declarative DSL feels really clean, way less boilerplate than pandera for the same checks. Drift detection out of the box is a nice touch I didn't expect.