[06:22] schestowitz[06:22] schestowitzLet's assume that you are working on a code base and notice that it has some minor issue. For argument's sake we'll say that it has some self written functionality and that the language's standard library has added identical functionality recently. Let's further assume that that said implementation behaves exactly the same as the self written one. At this point you might decide to clean up the code base, [06:22] schestowitz make it use the stdlib implementation and delete the custom code. This seems like a nice cleanup so you then file merge request to get the thing changed.
[06:22] schestowitz
[06:31] schestowitz[06:31] schestowitzI was reading recently about some significant Python 3.11 performance improvements, and I was wondering whether Perl 5 still gets significant performance improvements on each version - even though it might be more mature, thus more optimized in the first place.
[06:31] -TechBytesBot/#techbytes-Perl performance evolution over the last decade | Dimitrios Kechagias [blogs.perl.org] [06:31] schestowitzI thought I'd compare the final releases of alternating versions starting with 5.12.5 released 10 years ago, using a benchmark I made for a cloud vm comparison. As is the case with any benchmark, it might not be representative of your own workloads - it benchmarks things that are relevant to me and also some things that I would avoid, but are used by many modules and are notoriously slow (mainly [06:31] schestowitz DateTime and Moose). However, it is more representative of "real-life", with results that are not lost in noise, than say, PerlBench (which has a different purpose of course).
[06:31] schestowitz