As a data point, running a Python program I've been working on lately, which is near enough entirely Python code, with a bit of I/O: (a prototype for some code I'll ultimately be writing in a lower-level language)

(macOS Ventura, x64)

- System python 3.9.6: 26.80s user 0.27s system 99% cpu 27.285 total

- MacPorts python 3.9.25: 23.83s user 0.32s system 98% cpu 24.396 total

- MacPorts python 3.13.11: 15.17s user 0.28s system 98% cpu 15.675 total

- MacPorts python 3.14.2: 15.31s user 0.32s system 98% cpu 15.893 total

Wish I'd thought to try this test sooner now. (I generally haven't bothered with Python upgrades much, on the basis that the best version will be the one that's easiest to install, or, better yet, is there already. I'm quite used to the language and stdlib as the are, and I've just assumed the performance will still be as limited as it always has been...!)

I have a benchmark program I use, a solution to day 5 of the 2017 advent of code, which is all python and negligible I/O. It still runs 8.8x faster on pypy than on python 3.14:

    $ hyperfine "mise exec python@pypy3.11 -- python e.py" "mise exec python@3.9 -- python e.py" "mise exec python@3.11 -- python e.py" "mise exec python@3.14 -- python e.py"
    Benchmark 1: mise exec python@pypy3.11 -- python e.py
      Time (mean ± σ):     148.1 ms ±   1.8 ms    [User: 132.3 ms, System: 17.5 ms]
      Range (min … max):   146.7 ms … 154.7 ms    19 runs

    Benchmark 2: mise exec python@3.9 -- python e.py
      Time (mean ± σ):      1.933 s ±  0.007 s    [User: 1.913 s, System: 0.023 s]
      Range (min … max):    1.925 s …  1.948 s    10 runs
     
    Benchmark 3: mise exec python@3.11 -- python e.py
      Time (mean ± σ):      1.375 s ±  0.011 s    [User: 1.356 s, System: 0.022 s]
      Range (min … max):    1.366 s …  1.403 s    10 runs
     
    Benchmark 4: mise exec python@3.14 -- python e.py
      Time (mean ± σ):      1.302 s ±  0.003 s    [User: 1.284 s, System: 0.022 s]
      Range (min … max):    1.298 s …  1.307 s    10 runs
     
    Summary
      mise exec python@pypy3.11 -- python e.py ran
        8.79 ± 0.11 times faster than mise exec python@3.14 -- python e.py
        9.28 ± 0.13 times faster than mise exec python@3.11 -- python e.py
       13.05 ± 0.16 times faster than mise exec python@3.9 -- python e.py

https://gist.github.com/llimllib/0eda0b96f345932dc0abc2432ab...

> [...] and I've just assumed the performance will still be as limited as it always has been...!)

Historically CPython performance has been so bad, that massive speedups were quite possible, once someone seriously got into it.

And indeed that has proven the case. But my assumption was that Python had been so obviously designed with performance so very much not in mind, that it had ended up in some local minimum from which meaningful escape would be impossible. But I didn't overthink this opinion, and I've always liked Python well enough for small programs anyway, so I don't mind having it proven wrong.