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[Moved from https://github.com/faster-cpython/ideas/discussions/395]
It's becoming obvious that:
- The pyperformance suite needs more benchmarks that are more similar to real-world workloads, and we should lean into optimizing for these and using these to report progress.
- Microbenchmarks of a particular feature are also useful and belong in the benchmark suite, but we shouldn't over-optimize for them or use them as a (misleading) indicator of overall progress.
It seems that one way to address this would be to lean into "tags" more in the pyperformance/pyperf ecosystem. pyperformance already allows for tags in each benchmark's pyproject.yaml
.
I propose we:
- Output the tags for each benchmark in the benchmark results in the
metadata
dictionary. pyperf
compare_to
would then calculate the geometric mean for each subset of benchmarks for each tag found in the results, as well as "all" benchmarks (existing behavior). This could be behind a flag if backward compatibility matters.
Alternatives:
We could instead use the nested benchmark heirarchy, rather than tags. Personally, I think tags is easier to understand and more flexible (a benchmark could be associated with multiple tags).
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