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  • you should include a faster version of the fibonacci function with exponentiation by squaring

      def fibonacci(k):
    a,b=(0,1)
    for i in range(k.bit_length()-1,-1,-1):
      d=a**2
      c=2*a*b-d
      d+=b**2
      (a,b)=(d,c+d) if k>>i&1 else (c,d)
    return a
    see https://oeis.org/wiki/User:Natalia_L._Skirrow/linear_recurre... (warning: old and bad and in need of revision), https://github.com/sympy/sympy/pull/30452 and https://github.com/sympy/sympy/pull/30541 for details of how to make similarly fast programs for arbitrary linear-recurrent sequences.

    you can also encode polynomials into integers; see https://mathstodon.xyz/@peterluschny/116320199782572958 and the following prog from https://codegolf.stackexchange.com/a/279771

      lambda n:pow(p:=2<<n,n,p*p+~p)//p
    both of these would be more intensive on the arithmetic side rather than control flow

    also you could at least wrap the existing one in a `functools.cache`

    by DroneBetter
  • My pet peeve are numbers with too many decimals. If you only run a benchmark three times and take the arithmetic mean you don't have five or more significant digits. At best, you have two. And for benchmarking the geometric mean is a far superior mean.
    by bjourne
  • Answer: not fast at all.
    by dezsiszabi
  • This doesn't seem to test the GC, nor important operations such as dict lookup/iteration, set add/membership, list iteration and updating.

    Is really a recursive implementation of Fib an enlightening benchmark? I don't think so. And bubblesort is just messing around with two pointers.

    Why not, if you're first doing benchmarking, find out what the most time consuming popular operations/algorithms are, and then use them?

    Now it seems that you are just testing two obscure algorithms that are not really representative for Python coding in general.

    by JohnKemeny
  • So Claude can convert python code bases to rust or golang, and give you an easy 10x speed boost. Much better than waiting for Python performance to improve
    by brianwawok
  • only tangentially related, but naming PyPy when PyPI was already established was ridiculous
    by scosman
  • 35 years on since the first public Python release and there's still so much room for improvement in its performance. These tests by Miguel are a useful quick check on that progress in 3.15 even if as he admits it's impossible to get "an objective and universal measure of the performance of a programming language".
    by makaimc
  • So not much progress since 3.14 - but still progress! Personally, I think it's nice when my code automatically gets faster thanks to someone else's work, and I don't understand all the negative sentiment in this thread. Yes, of course Python is still a slow language. You hopefully knew that when you picked Python for your project.
    by jakobnissen

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