1 dépôt
Awesome GitHub RepositoriesRuntime Constraint Validation
Validation of data values against logical rules and statistical boundaries during program execution.
Distinct from Static Type Checking: Distinct from static type checking as it verifies actual data values at runtime rather than code structure during compilation.
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Awesome Runtime Constraint Validation GitHub Repositories
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- unionai-oss/pandera
unionai-oss/pandera
4,382Voir sur GitHubPandera is a data pipeline validation framework and statistical type validation tool. It functions as a library for defining and enforcing schemas on datasets to ensure data quality and consistency, specifically providing validation capabilities for Pandas dataframes. The project includes a schema inference tool that automates setup by analyzing existing dataset samples to generate validation schemas. It also serves as a synthetic data generator, creating artificial datasets based on predefined schemas to verify data-producing functions. The framework covers data engineering quality assuranc
Implements runtime checks to verify that dataset values adhere to specific logical and statistical constraints.
Pythonassertionsdata-assertionsdata-check
