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chernishev

26 karma · joined February 18, 2023

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chernishev··on Show HN: Desbordante 2.3.0 is out, now supports macOS
Desbordante, an open-source, high-performance data profiler that discovers and validates complex patterns in data, has released version 2.3.0. This update introduces two new patterns and adds support for macOS. Users can now install the Desbordante-core pip package on macOS via PyPi, compatible with CPython versions 3.8 through 3.13 and PyPy versions 3.7 through 3.10.

Release notes are here: https://github.com/Desbordante/desbordante-core/releases/tag...

chernishev··on Show HN: Desbordante 2.0 – A high-performance data profiler
That’s a great idea, but I think there are not enough interested people right now. We basically just started getting attention and to be honest I don't think the server will be very active at the moment. Instead, we have a google group for communication:

https://groups.google.com/g/desbordante

Feel free to ask questions!

chernishev··on Show HN: Desbordante 2.0 – A high-performance data profiler
Thank you for the suggestion. Adding a video is a very good idea, but unfortunately we do not have it now.

Instead, I can offer you a streamlit demo, showing what can be built with Desbordante: https://desbordante.streamlit.app/

And here are links to Python source code which runs inside it: 1) Typo miner: https://github.com/Desbordante/desbordante-core/blob/main/ex... 2) Deduplication: https://github.com/Desbordante/desbordante-core/blob/main/ex... 3) Anomaly detector: https://github.com/Desbordante/desbordante-core/blob/main/ex...

chernishev··on Show HN: Desbordante – an open-source data profiling tool
Desbordante is a high-performance data profiler oriented towards exploratory data analysis. Unlike many other profilers, our focus is on uncovering complex patterns hidden in data such as functional (both exact and approximate) dependencies, conditional dependencies, association rules and many others. Desbordante also offers data cleaning scenarios based on combinations of these formalisms. For now, we have implemented a typo detection pipeline using approximate and exact dependencies.

For interested readers we have also prepared an introductory article describing what is it all about: https://medium.com/@chernishev/exploratory-data-analysis-wit...

Desbordante is an open-source project, and we welcome contributions: https://github.com/Mstrutov/Desbordante/