🚇 Speedup PR benchmark

[s-weigand]

Running benchmarks on PRs takes forever to get feedback (~1h e.g. here) since it benchmarks each commit in between.
The most important information are the benchmark of the last release and the current commit before merging.
Thus we can omit running the benchmarks for all steps in between.
If more insight is needed at which specific commit in a PR a performance regression occurred it can always be run locally.

Change summary

• Only run base compare commit (v0.4.0) and last HEAD commit on PR benchmark

Checklist

• ✔️ Passing the tests (mandatory for all PR's)

[github-actions]

👈 Launch a binder notebook on branch s-weigand/pyglotaran/speedup-PR-benchmark

[codecov]

Codecov Report

Merging #785 (7b3a571) into staging (b960a98) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           staging    #785   +/-   ##
=======================================
  Coverage     83.9%   83.9%           
=======================================
  Files           75      75           
  Lines         4185    4185           
  Branches       752     752           
=======================================
  Hits          3512    3512           
  Misses         538     538           
  Partials       135     135           

---

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[s-weigand]

The benchmarking time is down to ~3min 🎉

[sonarcloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells

No Coverage information
0.0% Duplication

[github-actions]

Benchmark is done. Checkout the benchmark result page.
Benchmark differences below 5% might be due to CI noise.

Benchmark diff

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [dc00e6da]       [7b3a5712]
     <v0.4.0>                   
-        62.4±2ms       43.9±0.6ms     0.70  BenchmarkOptimize.time_optimize(False, False, False)
-         363±3ms         57.7±1ms     0.16  BenchmarkOptimize.time_optimize(False, False, True)
-        91.5±2ms       74.0±0.7ms     0.81  BenchmarkOptimize.time_optimize(False, True, False)
         90.8±2ms        86.3±30ms     0.95  BenchmarkOptimize.time_optimize(False, True, True)
         63.7±1ms       59.0±0.5ms     0.93  BenchmarkOptimize.time_optimize(True, False, False)
-         362±6ms        66.7±30ms     0.18  BenchmarkOptimize.time_optimize(True, False, True)
         89.5±1ms         92.2±2ms     1.03  BenchmarkOptimize.time_optimize(True, True, False)
+        92.9±2ms         112±40ms     1.21  BenchmarkOptimize.time_optimize(True, True, True)
             182M             181M     0.99  IntegrationTwoDatasets.peakmem_create_result
             200M             199M     1.00  IntegrationTwoDatasets.peakmem_optimize
-         280±6ms          224±4ms     0.80  IntegrationTwoDatasets.time_create_result
-      5.85±0.02s       1.44±0.03s     0.25  IntegrationTwoDatasets.time_optimize

[jsnel]

👍 🕐++