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The speed or lack thereof of Python is not the problem. The problem is language (mis)features.

But interestingly, Go is a very simple, straightforward language. It's got many of the same goals that Python had, and it meets those goals quite well. And it is blazingly fast. And it compiles so fast that it might as well be interpreted. And it is statically typed, something that is all the rage again these days and which Python pretends to offer but is really just noise and decoration.

I would go so far as to claim that anything built in Python can be built better in one of many other languages, even if you use Numpy or some other Python-specific language. And the way I would meet that challenge would be to isolate the use of the Python library and provide a minimal interface to that, and then call that Python program from another better language. Then I get the utility of the Python library from a language that scales better conceptually and performance-wise.



Go is quite a bit cleaner than Python and its concurrency/parallelism primitives can be well suited to scientific workloads.

You may want to have a look at Gonum (https://www.gonum.org), and the Go HEP package developed by CERN (https://go-hep.org).

I was also surprised to see DSP and pretty sophisticated packages, although I never used them: https://awesome-go.com/science-and-data-analysis

And of course Go has Jupyter integration, it's almost like running a script thanks to its fast compilation time.




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