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README.md 2026-04-06 6.9 kB
Totals: 17 Items   1.5 GB 10

[19.0.0] - 2026-04-07 🔐 "The FAIR Answers Release" 📐

The Reproducibility Crisis in Scientific Research is one of the principal motivators for FAIR Principles in Data Management.

With AI increasingly used in data pipelines, the need for reproducibility and auditability has become even more critical as "hallucinations" and "non-deterministic outputs" are inherent challenges in Generative AI.

That's why in this release, we instrumented qsv with several features to help users track, audit, and reproduce their AI-assisted data wrangling workflows more effectively. As FAIR Principles do not only apply to data, we also want FAIR Answers - with the last R for "Reproducible":

  • Enhanced Logging: The qsv_log tool now supports structured logging with JSON output, making it easier to parse and analyze logs for reproducibility audits.
  • NEW blake3 Command: A new blake3 command computes BLAKE3 hashes of files or data streams, providing a fast and reliable way to verify data integrity and track file versions in workflows. Unlike the oft-used SHA-256 hash, BLAKE3 is up to 16 times faster without sacrificing security, making it ideal for large datasets and iterative processing.
  • Cowork Project Reproducibility Manifest: Building on the Cowork Project support released in 18.0.0, the qsv Cowork Plugin now creates a Project Reproducibility Manifest - a structured log of all prompts, commands, and outputs generated during a Cowork session. This manifest can be used for detailed audits of the data wrangling process, helping users understand how specific outputs were derived and enabling them to reproduce or modify the workflow with confidence.
  • Even Moarstats: The moarstats command gets even "moar" statistical tests and metrics (Trimean, Midhinge, Robust CV, Jarque-Bera, Theil Index, Mean Absolute Deviation and Simpson's Diversity Index), giving users deeper insights into their data distributions and relationships, which can be crucial for reproducibility in data analysis.
  • To Parquet Improvements: The to parquet command is re-added with a new implementation powered by Polars' LazyFrame API, providing faster and more reliable CSV-to-Parquet conversion with better schema inference and support for complex data types. New options like --infer-len and --try-parse-dates enhance the accuracy of type inference, further improving the fidelity of Parquet outputs for faster downstream analysis and reproducibility.

Detailed MCP Server and Cowork Plugin changes are documented in the MCP CHANGELOG.


Added

Changed

Fixed

  • docs: fix 27 stale claims found in documentation audit https://github.com/dathere/qsv/pull/3637
  • docs: correct 5 documentation inaccuracies found during audit
  • typo: | character not escaped, prematurely truncating content

Dependencies

Full Changelog: https://github.com/dathere/qsv/compare/18.0.0...19.0.0

Source: README.md, updated 2026-04-06