v1.0.0

Desbordante CLI

Desbordante is a high-performance data profiler that is capable of discovering and validating many different patterns in data using various algorithms.

The Discovery task is designed to identify all instances of a specified pattern type of a given dataset.

The Validation task is different: it is designed to check whether a specified pattern instance is present in a given dataset. This task not only returns True or False, but it also explains why the instance does not hold (e.g. it can list table rows with conflicting values).

The currently supported data patterns are:

• Functional dependency variants:
  • Exact functional dependencies (discovery and validation)
  • Approximate functional dependencies, with g₁ metric (discovery and validation)
  • Probabilistic functional dependencies, with PerTuple and PerValue metrics (discovery)
• Graph functional dependencies (validation)
• Conditional functional dependencies (discovery)
• Inclusion dependencies (discovery)
• Order dependencies:
  • set-based axiomatization (discovery)
  • list-based axiomatization (discovery)
• Metric functional dependencies (validation)
• Fuzzy algebraic constraints (discovery)
• Unique column combinations:
  • Exact unique column combination (discovery and validation)
  • Approximate unique column combination, with g₁ metric (discovery and validation)
• Association rules (discovery)

For more information about the supported patterns check the main repo.

What's Changed

• Moved CLI to separated repository
• Add CLI for Split algorithm for discovery of Differential Dependencies by @MichaelS239 in #1

Full Changelog: https://github.com/Desbordante/desbordante-cli/commits/1.0.0