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Your "just in case the software is exposed to the web" should be "exposed to untrusted data." The very old Python hash could be DoS'ed reading a data file. The original randomized version required some feedback to figure out the hash, so generally required some sort of interaction.
I find that hard to believe that's a performance bottleneck. String hashes are all cached, and names like "print" are interned.
For a 2x overall gain I would expect to see the hash function pop up easily in my profiling, but I haven't seen it in my own profiling which was looking for simple things like that.
When siphash was evaluated, quoting https://peps.python.org/pep-0456/#performance , "In general the PEP 456 code with SipHash24 is about as fast as the old code with FNV" and "The summarized total runtime of the benchmark is within 1% of the runtime of an unmodified Python 3.4 binary".
Since then they switched from siphash24 to the faster siphash13. https://github.com/python/cpython/pull/28752
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CodeRabbit
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rustc-hash
Custom hash algorithm used by rustc (plus hashmap/set aliases): fast, deterministic, not secure
Which is why the Rust compiler itself uses a non-cryptographic hash, which takes just 3 x86 instructions and can work on 8 bytes at a time: <https://github.com/rust-lang/rustc-hash/blob/master/src/lib....>
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I have a real life example in this commit: https://github.com/hpc4cmb/toast/pull/380/commits/a38d1d6dbc...
Replacing 2 lines of python code (with tens of glue code in Numba) with hundreds lines of C++ with glue code.
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If you have no knowledge you can still make use of element picker in the context menu. In this case though the problematic element will have a generated class name like `frontend-components-SubscribePrompt-`, so I resorted to the CSS syntax (`##`). There are a lot, a freaking lot of them [1] but the CSS syntax alone can achieve a lot.
[1] https://github.com/gorhill/uBlock/wiki/Static-filter-syntax
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Recent CPython development has been towards optimizations and addressing use cases that benefit from optimizations, some coming from the faster CPython initiative. You might just get your JIT[1].
[1] https://github.com/faster-cpython/ideas/wiki/Workflow-for-3....
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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A template repo can be found here https://github.com/JacksonKearl/cpython, but it does not implement an ideal malloc as I am not sure if it is still being used as an assignment.
The repo states that even this dummy implementation:
> has a 60% faster startup as compared to base CPython, and in some test cases has marginally better runtime performance as well.
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