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vowl

vowl (vee-owl 🦉): a validation engine for Open Data Contract Standard (ODCS) data contracts. Define your validation rules once in a declarative YAML contract and get rich, actionable reports on your data's quality.

Key Features

  • Extensible Check Engine: Ships with a SQL check engine out of the box, with the architecture designed to support custom check types beyond SQL.
  • Auto-Generated Rules: Checks are automatically derived from contract metadata (logicalType, logicalTypeOptions, required, unique, primaryKey) and library metrics (nullValues, missingValues, invalidValues, duplicateValues, rowCount).
  • Any DataFrame, Any Backend: Load any Narwhals-compatible DataFrame type (pandas, Polars, PySpark, etc.) or connect to 20+ backends via Ibis. SQL dialect translation is handled by SQLGlot.
  • Server-Side Execution: SQL checks run server-side through Ibis without materialising tables on the client.
  • Multi-Source Validation: Validate across tables in different source systems with cross-database joins.
  • Declarative ODCS Contracts: Define validation rules in YAML following the Open Data Contract Standard.
  • Flexible Filtering: Filter conditions with wildcard pattern matching, ideal for incremental validation of new data.
  • Rich Reporting: Detailed summaries, row-level failure analysis, saveable reports, and a chainable ValidationResult API.
  • No Silent Gaps: Unimplemented or unrecognised checks surface as ERROR, not quietly skipped, so nothing slips through the cracks.

Quick Start

pip install vowl

import pandas as pd
from vowl import validate_data

df = pd.read_csv("data.csv")
result = validate_data("contract.yaml", df=df)
result.display_full_report()

Optional extras: vowl[spark], vowl[all].

License

This project is licensed under the MIT License.