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Comment by enriquto | Hacker News Reader

> Python's entire value proposition is that it is "executable pseudocode" (...) so somebody like a scientist (...)

LOL'd hard at that.

What kind of scientist would write "import numpy as np" on their pseudocode? Or multiply matrices with the "@" operator? From the point of view of a scientist, Matlab/Octave, or even Fortran, is executable pseudocode. Numerical stuff in Python seems like an ugly kludge.

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As a scientist who had to use MATLAB up until about 2013 because that's what everyone else used, it was such a relief to move to Python. It's true that you can implement a linear algebra routine in a couple fewer characters in MATLAB, but unless that's literally all you're doing, Python is much nicer to work with. The data structures in MATLAB are just a nightmare for general purpose programming, which makes things like loading and parsing data -- things that scientists often need to do -- just terrible. The fact that the notion of the "matrix" (i.e. a 2D array rather than a general ND array) is so deeply baked into everything is a huge headache (a scalar is a 1x1 matrix in MATLAB!). I'm also surprised anyone is particularly bothered by the @ operator. The asterisk for matrix multiplication seems roughly equally unheard of in nicely typeset / handwritten math (you would just write e.g. Ab for a matrix-vector multiplication with no inset operator).

I shudder when I think of my Matlab days, but i’ve programmed long enough in enough other languages to know that we have better options than either Matlab or Numpy/Pandas with respect to API design. We can also have much better performance than Python with many other languages.

I don't know why you got downvoted, but I agree that matrix manipulation in numpy look quite foreign to to somebody new to python/numpy. I had heard this "complain" from several colleagues (mostly former matlab-users). Several colleagues have migrated to Julia, which does a quite good job in producing easy readable numerical code. For instance, the dot-product can be written with the Unicode dot symbol (typed as \dot<tab>)

> matrix manipulation in numpy look quite foreign to to somebody new to python/numpy

Not only to newcomers. I've been using python+numpy for more than 10 years, nearly every day, and it despairs me as much as the first day, if not more. I relish the few moments that I get to write numeric algorithms in any other language.

I think if you zoom out enough Python code looks a lot like pseudo code.

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