Python: Difference between revisions
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However, synthetic benchmarks are not | However, synthetic benchmarks are not necessarily reflective of real-world performance. In common real-world situations, the performance difference between optimized and non-optimized interpreters is minimal. For example, using <code>pylint</code> with a significant number of custom linters to scan a very large Python codebase (>6000 files) resulted in only a 5.5% difference. Other workflows that were not performance sensitive saw no impact to their run times. | ||
=== Possible Optimizations === | === Possible Optimizations === | ||
If you run code that heavily depends on Python performance | If you run code that heavily depends on Python performance, and you desire the most performant Python interpreter possible, here are some possible things you can do: | ||
* Enable the <code>enableOptimizations</code> flag for your Python derivation. [https://discourse.nixos.org/t/why-is-the-nix-compiled-python-slower/18717/10 Example] Do note that this will cause you to compile Python the first time that you run it | * '''Enable the <code>enableOptimizations</code> flag for your Python derivation'''. See [https://discourse.nixos.org/t/why-is-the-nix-compiled-python-slower/18717/10 Example]. Do note that this will cause you to compile Python the first time that you run it which will take a few minutes. | ||
* Switch to a newer version of Python. In the example above, going from 3.8 to 3.10 yielded an average 7.5% performance improvement | * '''Switch to a newer version of Python'''. In the example above, going from 3.8 to 3.10 yielded an average 7.5% performance improvement, but this is only a single benchmark. Switching versions most likely won't make all your code 7.5% faster. | ||
* Disable hardening | * '''Disable hardening'''. Beware this only yields a small performance boost and it has impacts beyond Python code. See [https://nixos.org/manual/nixpkgs/stable/#sec-hardening-in-nixpkgs Hardening in Nixpkgs]. | ||
'''Ultimately, it is up to your use case to determine if you need an optimized version of the Python interpreter. We encourage you to benchmark and test your code to determine if this is something that would benefit you.''' | '''Ultimately, it is up to your use case to determine if you need an optimized version of the Python interpreter. We encourage you to benchmark and test your code to determine if this is something that would benefit you.''' | ||