There are optimizable points that can be achieved by removing unnecessary tuple transformation and using vector calling convention.

+---------------+--------+----------------------+
| Benchmark     | base   | opt                  |
+===============+========+======================+
| bench pattern | 482 ns | 417 ns: 1.15x faster |
+---------------+--------+----------------------+

With Ken Jin's suggestion

+---------------+--------+----------------------+
| Benchmark     | base   | PR 28043           |
+===============+========+======================+
| bench pattern | 482 ns | 373 ns: 1.29x faster |
+---------------+--------+----------------------+

New changeset e6497fe698f6e87344501a68ffdea106eafcb257 by Dong-hee Na in branch 'main':
bpo-45045: Optimize mapping patterns of structural pattern matching (GH-28043)
https://github.com/python/cpython/commit/e6497fe698f6e87344501a68ffdea106eafcb257

For the record,

Final benchmark with optimization build + thin LTO option.

+---------------+---------------+----------------------+
| Benchmark     | thin_lto_base | thin_lto_opt         |
+===============+===============+======================+
| bench pattern | 357 ns        | 287 ns: 1.24x faster |
+---------------+---------------+----------------------+

Thanks, this is awesome.

FYI, there's probably more low-hanging fruit like this scattered about the pattern matching implementation. It's all very new code, mostly written by one person ;).

(I wouldn't worry too much about the pattern compiler, though... I'm currently finishing up a total rewrite of that!)

I'm also in the process of creating some pattern matching benchmarks. You might find them useful for benching optimizations like this in the future:

https://github.com/brandtbucher/patmaperformance

In particular, I'm curious to see the impact of this change on "patma_holdem". I bet it's quite good.

> https://github.com/brandtbucher/patmaperformance

Nice benchmark suite, I will take a look :)