Comment by librasteve

First, let me say I am totally in favour of the sentiment here:

Python is by far the fastest to write, cleanest, more maintainable programming language I know, and that a bit of a runtime performance penalty is a small price to pay when I'm rewarded with significant productivity gains. I rarely feel Python slows me down, and on the other side I constantly marvel at how fast I code with it compared to other languages.

Personally I prefer Raku [https://raku.org] to do the same.

Here is the Python code from the article:

  import sys

  def fibo(n):
    if n <= 1:
        return n
    else:
        return fibo(n-1) + fibo(n-2)

  if __name__ == '__main__':
    for n in sys.argv[1:]:
        print(n, fibo(int(n)))

And here is my Raku code:

  sub MAIN(*@n) {
    say (0, 1, *+* ... *)[@n]
  }

So, even better on the "quick to code and easy to maintain" imo.

The performance comparison is interesting too...

CPython 9.72 - 22.10 secs

PyPy 1.65 secs

Node 1.76 secs

Rust 0.25 secs

Raku 0.12 secs

  > time ./fibo.raku 10 20 30 40
  (55 6765 832040 102334155)
  ./fibo.raku 10 20 30 40  0.12s user 0.02s system 114% cpu 0.124 total

Haha (admittedly I am on an M1 not an i5 so this is a bit Apples vs. Oranges ... but CPUs getting faster all the time and Raku has no GIL)