Python Programming and Numerical Methods: A Guide for Engineers and Scientists

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • WolframLanguageForJupyter

    Wolfram Language kernel for Jupyter notebooks

  • magicl

    Matrix Algebra proGrams In Common Lisp.

  • I guess my number one piece of advice is to estimate time accordingly. Most things can be solved using pre-existing solutions with a bit of work, if you’re patient and you can afford to put in the time to do it.

    Secondary to that:

    - Learn to use FFI very well try hard to find libraries written in C.

    - Familiarize yourself with the structure of LAPACK and what it offers.

    - Learn to use a profiler and debugger (if using Lisp: SB-SPROF, TIME, SLIME, and SLDB).

    - (if using Lisp) Contribute useful things back to existing libraries, like MAGICL [0].

    Maybe it’s not the best analogy, but scientific programming in Lisp is currently like woodworking (compared to building IKEA with Python).

    [0] https://github.com/rigetti/magicl

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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