✨🚇 Add official python 3.11 support

[s-weigand]

Since python 3.11 came out some time ago we should also see we can already support it (mostly dependency issue).

Change summary

• ✨🚇 Added python 3.11 CI tests

Checklist

• ✔️ Passing the tests (mandatory for all PR's)
• 🚧 Added changes to changelog (mandatory for all PR's)
• 🧪 Adds new tests for the feature (mandatory for ✨ feature and 🩹 bug fix PR's)

[github-actions]

👈 Launch a binder notebook on branch s-weigand/pyglotaran/add-py311-support

[github-actions]

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

Benchmark diff v0.7.0 vs. main

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [9adf4a49]       [7e0285a7]
     <v0.7.0>                   
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, False, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, False, True)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, True, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, True, True)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, False, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, False, True)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, True, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, True, True)
             218M             219M     1.00  IntegrationTwoDatasets.peakmem_optimize
       1.01±0.02s         972±40ms     0.96  IntegrationTwoDatasets.time_optimize

Benchmark diff main vs. PR

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [7e0285a7]       [e4f50434]
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, False, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, False, True)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, True, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, True, True)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, False, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, False, True)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, True, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, True, True)
             219M             217M     0.99  IntegrationTwoDatasets.peakmem_optimize
         972±40ms         972±40ms     1.00  IntegrationTwoDatasets.time_optimize

[s-weigand]

Ok looks like numba does not support py311 officially yet

[sonarcloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells

No Coverage information
0.0% Duplication

[codecov]

Codecov Report

Patch and project coverage have no change.

Comparison is base (7e0285a) 88.3% compared to head (e4f5043) 88.3%.

Additional details and impacted files

@@          Coverage Diff           @@
##            main   #1161    +/-   ##
======================================
  Coverage   88.3%   88.3%            
======================================
  Files        107     107            
  Lines       5122    5122            
  Branches     847     960   +113     
======================================
  Hits        4525    4525            
  Misses       479     479            
  Partials     118     118            

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[s-weigand]

In #1276 it was tested that we get the same results with python 3.11 and numba 0.57.0

[sonarcloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells

No Coverage information
0.0% Duplication

[jsnel]

Finally! 😄