Why Fortran may be better than Python for teaching numerical linear algebra fundamentals to engineering students
By
Bostonian
Master baker tier. Every paragraph earns its place on the tray.
Summary
Dr. Jean-Christophe Loiseau argues that Fortran is a better teaching tool than Python for introducing engineering students to the basics of numerical linear algebra and scientific computing. While acknowledging Python's powerful ecosystem (NumPy/SciPy/matplotlib), the author contends that Fortran's simplicity, directness, and lack of abstraction layers help students with limited programming experience understand the fundamental mathematical operations behind linear algebra computations. The article focuses on pedagogical effectiveness rather than performance comparisons.
Key quotes
· 3 pulledThis is not a post about which language is the most elegant or which implementation is the fastest (we all know it's Fortran). It's about teaching the basics of scientific computing to engineering students with a limited programming experience.
Yes, the Numpy/Scipy/matplotlib stack is awesome. Yes, you can use numba or jax to speed up your code, or Cython, or even Mojo the latest kid in the block. Or you know what? Use Julia or Rust instead. But that's not the basics and it's beyond the point.
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