I'm struggling to comprehend your comment here, python needs to work native on windows or is it something else, why is WSL such a barrier given it's generally available on a few billion devices worldwide?
Python is now bigger than what even its most keen friends ever imagined might happen. This is not automatically solving the issues, nor make it more likeable to those who dislike it, but it does incentivise serious plumbing work.
The developers of SciPY are really good, maybe their brains could be focused on developing tools for a different language that doesn't cause articles to be written about how crazy it is to integrate with it.
At some point, move on, Python started as a toy, and grew into a behemoth.
For some in the scientific community, Julia is seen as a a nice alternative to python. It has some great libraries, and installing them is easy, perhaps because the system was well-designed from the start, and recently enough to build on experience with other systems.
Julia is really handy for reproducible work, because you can specify which versions of which libraries you're using, and share that information with others easily so they can retrace your steps. That's a big factor in scientific work.
The other thing (returning to the main topic) is that Julia does not have to rely on fortran or C/C++ for low-level work. Julia is very fast all by itself. Indeed, most of the Julia libraries are written in Julia itself, providing users with a tutorial for intensive work.
In addition to these things, I have to admit that I love how Julia lets me program in unicode symbols, so my equations in code can look like my equations on paper.
There are some downsides to Julia that I ought to point out.
1. The error messages can be very cryptic.
2. The documentation is poor (no worse than Python, I think, but a lot worse than R).
3. The development community is a bit ivory-tower-ish. The usual answer to "could you improve the documentation" is "please submit a PR".
4. There is a learning curve to get used to Julia. It's easier if you are already familiar with Fortran and Matlab. Then again, most scientists I know are familiar with both those languages (and Python, and R, and ...) so learning a new language is not a challenge. Scientists like to learn stuff -- that's the whole point of being in science, for most of us.
Maybe instead the solution should be moving away from Windows. Almost all the issues described in the article (and I would argue with most language packaging systems) is due Windows being such a pain to develop on. I'd argue it's going to be easier to convert all scientific users to Linux than rewrite all scientific code in a different language. (no I'm not seriously suggesting all Windows users abandon it, I'm just replying to someone who suggests to ditch the language which has the largest scientific codebase by likely several orders of magnitude)
I assume it would be working on WSL also? Which seems like a simple solution to the mess that is developing on Windows, especially in Python.