What can Fortran learn from Node.js Standard Library

I’ve heard it said that “Software is eating the world.” If that is true, than Node.js is eating software.

The following link is to the Node.js Standard Library project that has an emphasis on numerical computation.

I’d be interested in any thoughts from the expert scientific programmers here on what is lacking. I think the statistics portion leaves a lot to be desired, but it is a decent start.

It is interesting that to build native numerical libraries, they still need gfortran.

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The provided link to the Node.js Standard Library did not work for me, but it’s also at GitHub. It looks like the JavaScript equivalent of NumPy and SciPy. People are working on having some of the functionality in FPM packages and stdlib.

Features

Demo showcasing special math functions

  • 35+ probability distributions, with support for evaluating probability density functions (PDFs), cumulative distribution functions (CDFs), quantiles, moments, and more.

Demo showcasing probability distributions

Demo showcasing PRNGs

  • 200+ general utilities for data transformation, functional programming, and asynchronous control flow.

Demo showcasing general utilities

Demo showcasing assertion utilities

Demo showcasing sample datasets

  • A plot API for data visualization and exploratory data analysis.

Demo showcasing plot API

  • Native add-ons for interfacing with BLAS libraries, with pure JavaScript fallbacks.

Demo showcasing BLAS APIs

Demo showcasing benchmark framework

  • REPL environment with integrated help and examples.
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Link should work now.

Thanks @R_cubed. What they have is my vision what stdlib should become.

CC @milancurcic, what do you think?

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Yes, same here.

Like Fortran, JavaScript doesn’t have a standard library, so the motivation is similar too.

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