[mariushn]

Thanks, it makes sense.

> focus on making the programming tools scientists use better, easier to use and GPL

That sounds the most natural path to take going forward. Besides looking at existing GPL software and how that can be improved, would you have a recommendation on where to find scientists/researchers open to discussing their needs that could be solved by software? I'll release the software under GPL, but need to know I'm building something useful.

[keldaris]

As a computational physicist (meaning I do science, but most of my time is spent programming), I agree with everything the parent said, but perhaps I can add some more specifics. The matplotlib example is a very good one in the sense that it's a piece of vital infrastructure almost everyone has used at some point. It works well enough for performance insensitive (meaning non-realtime and small-ish datasets) 2D visualization, has a lot of features and is easy to use. Other niches are less fortunate - for instance, for general purpose performant 3D visualization there's the bloated monstrosity that is VTK and little else, so I mostly just write OpenGL code by hand. That's annoying, but I haven't found anything that isn't outright terrible.

Other scientists, depending on their interests, will readily give you similar examples of obvious general purpose libraries that are lacking or non-existent, but there's a simple reason for this - it's hard, unrewarding work that's very hard to commercialize. Most of the large scale projects that exist have grown out of academic grants and often struggle for funding or are abandoned entirely. If you are really considering this as a career move that's eventually supposed to put food on the table, you need to have a pretty good idea of how your project is realistically going to earn money, because the correlation between funding and general usefulness is very weak in this space. Since academic funding isn't on the table for you, the common alternative involves things like biotech startups and venture capital.

[TallGuyShort]

>> Other scientists, depending on their interests, will readily give you similar examples of obvious general purpose libraries that are lacking or non-existent

I'd love to hear some of these, if folks on the thread can share more. Added 3d visualization to my list...

[badpun]

Symbolic computation libraries for Python are lacking - there's SymPy, but it can throw a "NotImplementedException" at you if you try processing some more hairy formulas... Would be great if SymPy was improved.

[peterhj]

Have you looked into SageMath? (Technically it's "Python-based" rather than "just" Python.) I'm also curious if you're specifically looking for something in Python, or if doing symbolic computation/computer algebra in other languages would work for you, barring license costs.

[badpun]

I needed a Python function which computes a (symbolic) derivative of a certain known formula. I could've just computed the derivative in say Mathematica, and then write the Python function manually based on the derived formula, but the derivative function had hundreds of terms and there was no way I'd transpile it manually without introducing errors.

In the end, I used a hacky Mathematica script which converts a resulting Mathematica formula into a Python code (which I then pasted into my program). But, if SymPy was better, I could do all this in just Python.

BTW, according to Wikipedia, SageMath is just using SymPy for calculus.