🚇👌 Run Doxygen workflow only on 'workflow_dispatch'

[s-weigand]

As requested by @jsnel this changes the Doxygen workflow to truly only run when requested.
The problem with the current implementation (#979 ) via github environment is that the UI never gets to the finished green checkmark state, but waits forever for the workflow to be approved.

This makes it hard to spot which PR is ready to be merged in the PR overview.

The new implementation allows specifying a repository to build the oxygen docs for (default glotaran/pyglotaran but could also be a fork) and a pr nr (default "" which uses the branch used to dispatch the workflow from).

Change summary

• 🚇👌 Reworked doxygen workflow to be 'workflow_dispatch' but work with PRs

Checklist

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

[github-actions]

👈 Launch a binder notebook on branch s-weigand/pyglotaran/doxygen

[sonarqubecloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells

No Coverage information
No Duplication information

[codecov]

Codecov Report

Merging #981 (e9b61f1) into main (2f00cd1) will not change coverage.
The diff coverage is n/a.

@@          Coverage Diff          @@
##            main    #981   +/-   ##
=====================================
  Coverage   85.6%   85.6%           
=====================================
  Files         90      90           
  Lines       4909    4909           
  Branches     927     927           
=====================================
  Hits        4207    4207           
  Misses       552     552           
  Partials     150     150           

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[github-actions]

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

Benchmark diff v0.5.1 vs. main

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [96b42630]       [e9b61f13]
     <v0.5.1>                   
         72.2±2ms         70.5±2ms     0.98  BenchmarkOptimize.time_optimize(False, False, False)
         140±20ms         115±20ms    ~0.82  BenchmarkOptimize.time_optimize(False, False, True)
         72.7±2ms         71.1±3ms     0.98  BenchmarkOptimize.time_optimize(False, True, False)
         151±10ms         168±20ms    ~1.12  BenchmarkOptimize.time_optimize(False, True, True)
         88.0±2ms          107±8ms    ~1.21  BenchmarkOptimize.time_optimize(True, False, False)
         112±40ms         114±20ms     1.02  BenchmarkOptimize.time_optimize(True, False, True)
         88.1±3ms         95.5±7ms     1.08  BenchmarkOptimize.time_optimize(True, True, False)
         101±40ms         113±40ms    ~1.12  BenchmarkOptimize.time_optimize(True, True, True)
             202M             203M     1.00  IntegrationTwoDatasets.peakmem_optimize
       2.21±0.07s       2.18±0.02s     0.99  IntegrationTwoDatasets.time_optimize

Benchmark diff main vs. PR

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [2f00cd1a]       [e9b61f13]
         71.4±2ms         70.5±2ms     0.99  BenchmarkOptimize.time_optimize(False, False, False)
          152±5ms         115±20ms    ~0.76  BenchmarkOptimize.time_optimize(False, False, True)
         70.6±1ms         71.1±3ms     1.01  BenchmarkOptimize.time_optimize(False, True, False)
         144±30ms         168±20ms    ~1.17  BenchmarkOptimize.time_optimize(False, True, True)
         90.7±3ms          107±8ms    ~1.17  BenchmarkOptimize.time_optimize(True, False, False)
         123±40ms         114±20ms     0.93  BenchmarkOptimize.time_optimize(True, False, True)
         89.7±3ms         95.5±7ms     1.07  BenchmarkOptimize.time_optimize(True, True, False)
         124±40ms         113±40ms     0.91  BenchmarkOptimize.time_optimize(True, True, True)
             200M             203M     1.01  IntegrationTwoDatasets.peakmem_optimize
       2.12±0.04s       2.18±0.02s     1.03  IntegrationTwoDatasets.time_optimize

[jsnel]

,👌