✨Add Python 3.10 support

[s-weigand]

Numba 0.55.0 added support for python 3.10 which means so can we

Change summary

• 🚇🧪 Add tests for python 3.10
• ⬆️ Raised max supported python version to <3.11
• ⬆️ Unpin setuptools

Using an old version of setuptools caused a lot of import errors in python 3.10
Pinning the version of setuptools goes back to the time when we still had c-extensions, so it is safe to unpin it

Checklist

• ✔️ Passing the tests (mandatory for all PR's)
• 🚧 Added changes to changelog (mandatory for all PR's)

[github-actions]

👈 Launch a binder notebook on branch s-weigand/pyglotaran/add-py310-support

[codecov]

Codecov Report

Merging #977 (1d5cc33) into main (5bd49b6) will increase coverage by 0.0%.
The diff coverage is n/a.

@@          Coverage Diff          @@
##            main    #977   +/-   ##
=====================================
  Coverage   85.6%   85.6%           
=====================================
  Files         90      90           
  Lines       4883    4909   +26     
  Branches     916     927   +11     
=====================================
+ Hits        4181    4207   +26     
  Misses       552     552           
  Partials     150     150           

Impacted Files	Coverage Δ
glotaran/model/dataset_group.py	100.0% <0.0%> (ø)
glotaran/parameter/parameter.py	95.5% <0.0%> (+<0.1%)	⬆️
glotaran/plugin_system/data_io_registration.py	97.2% <0.0%> (+<0.1%)	⬆️
...n/analysis/optimization_group_calculator_linked.py	95.8% <0.0%> (+<0.1%)	⬆️
glotaran/project/result.py	90.1% <0.0%> (+1.7%)	⬆️

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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]       [1d5cc339]
     <v0.5.1>                   
         71.1±1ms         73.2±2ms     1.03  BenchmarkOptimize.time_optimize(False, False, False)
         146±40ms         118±20ms    ~0.81  BenchmarkOptimize.time_optimize(False, False, True)
         71.0±1ms         70.5±1ms     0.99  BenchmarkOptimize.time_optimize(False, True, False)
         168±20ms         131±40ms    ~0.78  BenchmarkOptimize.time_optimize(False, True, True)
       89.8±0.5ms         89.8±2ms     1.00  BenchmarkOptimize.time_optimize(True, False, False)
         100±30ms         95.0±2ms     0.95  BenchmarkOptimize.time_optimize(True, False, True)
         89.6±1ms         90.4±3ms     1.01  BenchmarkOptimize.time_optimize(True, True, False)
         96.9±2ms         102±30ms     1.05  BenchmarkOptimize.time_optimize(True, True, True)
             205M             201M     0.98  IntegrationTwoDatasets.peakmem_optimize
       2.23±0.03s       2.16±0.06s     0.97  IntegrationTwoDatasets.time_optimize

Benchmark diff main vs. PR

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [5bd49b63]       [1d5cc339]
         72.0±1ms         73.2±2ms     1.02  BenchmarkOptimize.time_optimize(False, False, False)
         124±30ms         118±20ms     0.95  BenchmarkOptimize.time_optimize(False, False, True)
       72.9±0.5ms         70.5±1ms     0.97  BenchmarkOptimize.time_optimize(False, True, False)
         139±30ms         131±40ms     0.94  BenchmarkOptimize.time_optimize(False, True, True)
         90.5±1ms         89.8±2ms     0.99  BenchmarkOptimize.time_optimize(True, False, False)
        97.9±10ms         95.0±2ms     0.97  BenchmarkOptimize.time_optimize(True, False, True)
         90.0±2ms         90.4±3ms     1.00  BenchmarkOptimize.time_optimize(True, True, False)
         96.4±2ms         102±30ms     1.06  BenchmarkOptimize.time_optimize(True, True, True)
             201M             201M     1.00  IntegrationTwoDatasets.peakmem_optimize
       2.25±0.02s       2.16±0.06s     0.96  IntegrationTwoDatasets.time_optimize

[sonarqubecloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells

No Coverage information
No Duplication information

[jsnel]

LGTM.

It's about time. 😅