OMR Python Library Replaces Repetitive Data Audit Boilerplate with One Command

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A developer has released OMR (Omni Data Refinement), an open-source Python library designed to streamline dataset quality checks that typically require dozens of lines of boilerplate code. The library generates a 0–100 health score across five dimensions — completeness, uniqueness, consistency, validity, and conformity — with a single function call. OMR also supports auto-cleaning with a transformation log, schema validation, statistical analysis, and drift detection using methods like PSI and KS Test. It requires only pandas, numpy, and rich, with no cloud dependencies or large language models involved. The library is available via pip and its source code is publicly hosted on GitHub.

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