this post was submitted on 28 Dec 2023
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Really makes you question your sanity when optimizing jumps in code without benchmarks.
For a long time I've been of the opinion that you should only ever optimize for the next ~~sucker~~ colleague who might need to read and edit your code. If you ever optimize for speed, it needs to be done with massive benchmarking / profiling support to ensure that the changes you make are worth it. This is especially true with modern compilers / interpreters that try to use clever techniques to optimize your code either on the fly, or before making the executable.
The first rule of optimization: Don’t do it
The second rule of optimization: Don’t do it yet (experts only)
I'm absolutely on-board ...in application code.
I do feel like it's good, though, when libraries optimize. Ideally, they don't have much else to do than one thing really well anyways.
And with how many libraries modern applications pull in, you do eventually notice whether you're in the Python ecosystem, where most libraries don't care, or in the Rust ecosystem, where many libraries definitely overdo it. Because well, they also kind of don't overdo it, since as a user of the library, you don't see any of it, except the culmulative performance benefits.
Libraries are also written and maintained by humans.
It's fine to optimize if you can truly justify it, but that's going to be even harder in libraries that are going to be used on multiple different architectures, etc.