Eh, you make incorrect assumptions about me. I'm stating a fact why Python is used - the data science ecosystem in Python thrives because of well-written libraries _written in C_ under the hood AND an easy-to-use language that writes like pseudocode.
If it was too slow, we'd be doing all of this in Java, the C# or maybe doing it in C/Fortran. But because of some early design decisions (Guido being on the matrix-sig helped), the history behind Numeric/Numarray and finally NumPy and SciPy being based on those efforts allowed it to thrive.
> it's the only way a tragically slow language like Python can keep up.
Those were your words, not mine. I need not make any assumptions.
I just replied listing use cases where Python shine due to its strengths, performance being mostly irrelevant. I didn't even mention data science.
And although it's beyond the point, if I was to use Python, why should I care in which language a library was written? If the language allows libraries written in other languages, this is actually a nice feature.
If it was too slow, we'd be doing all of this in Java, the C# or maybe doing it in C/Fortran. But because of some early design decisions (Guido being on the matrix-sig helped), the history behind Numeric/Numarray and finally NumPy and SciPy being based on those efforts allowed it to thrive.