Did you know it takes about 17,000 CPU instructions to print(“Hello”) in Python? And that it takes ~2 billion of them to import a module?

  • @muntedcrocodile
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    2210 months ago

    If i needed speed i wouldnt be programming in python.

    • Eager Eagle
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      1010 months ago

      also, if I needed speed I wouldn’t be printing stuff every 100k instructions

    • @grue
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      710 months ago

      If I needed speed, I’d be programming in Python but then profiling the performance and re-writing the inner loops and such to call C or BLAS.

    • @[email protected]
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      410 months ago

      In fact, Python is still decent even if you do need speed. We compared Python and Rust for algorithm processing, and we got similar-ish numbers when using numba. Rust was certainly faster, but we would need to retrain a lot of our team, and numba was plenty fast.

      Python is fast enough, and if it’s not, there are libraries to get it there.

  • Eager Eagle
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    10 months ago

    so 200 to 800 microseconds on a modern cpu? Fast enough.

  • @eclecticprune
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    410 months ago

    While the processor I’m working on right now supports 14MIPS…

  • @[email protected]
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    310 months ago

    I doubt it’s useful for performance evaluation, however, if you are writing a paper and want to compare your algorithm to an existing one, this can be handy

    • @[email protected]
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      210 months ago

      Eh, maybe? It’s probably only useful for large jumps, and timing is also probably good enough for that as well. With small jumps, instruction execution order matters, so a bigger number could very well be faster if it improves pipelining.

      It’s certainly interesting and maybe useful sometimes, but it’s probably limited to people working on Python itself, not regular users.