On Fri, 14 Aug 2020 at 05:37, Guido van Rossum <gu...@python.org> wrote:

> My own strawman would be to limit a Matrix to 2-dimensionality -- I believe 
> that even my college linear algebra introduction (for math majors!) didn't 
> touch upon higher dimensionality, and I doubt that what I learned in high 
> school about the topic went beyond 3x3 (it might not even have treated 
> non-square matrices).

Absolutely agree, dimensionality 2 is a must. For two reasons. First,
it's easy to understand and implement. Second it actively discourages
those who would like to use this matrix for real calculations. The
main point is basic and simple: teaching, geometry computation (e.g.
on point rotation/translation) etc. Things like that.
Anything else is beyond the scope of such a module and should be
implemented using numpy.

Calculations about determinant, element-wise operations, matrix
multiplication, inverse, etc are also basic operations that are likely
to come up during either a course or trivial computations for e.g.
geometry. I would not add things like QR or Cholesky factorization.


-- 
Kind regards,

Stefano Borini
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