Allow calculating geometric mean of groups of benchmarks based on tags

[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:

1. Output the tags for each benchmark in the benchmark results in the metadata dictionary.
2. 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).

まず、pyperformance's pyproject.yaml のベンチマークタグがベンチマーク結果とメタデータでどのように表現されているかを追跡し、次に pyperf の compare_to フローを調査します。タグがメタデータに公開され、各タグサブセットおよびすべてのベンチマークについて幾何平均が計算され、後方互換性の動作が解決されていれば完了です。