Record coverage for fast tests and analyze with deepsource and codecov

[tovrstra]

See #313 for the overview.

• This splits up the tests in slow (29) and the rest (not slow, 462 tests). Only the fast ones are used for coverage analysis, because coverage would slow down the slow tests to the point it becomes impractical (and expensive).
• Coverage is only recorded on Linux, for performance/cost and compatibility with upload scripts.
• Some slow unit tests were split up into separate, faster ones, using pytest.mark.paramettrize.
• The contributing guide is also updated to show how to run the fast tests first, which makes development a little easier.
• The coverage is analyzed by codecov and deepsource, which is an experiment. I don't know how well deepsource will work, but I'd like to find something better than codecov.
• For security reasons, coverage reports cannot be uploaded in pull requests from forks, like this one. (I've tested on my repo that it works.)
• Secrets configured in repository settings: CODECOV_TOKEN and DEEPSOURCE_DSN.

Summary by Sourcery

This pull request optimizes test coverage analysis by splitting tests into 'slow' and 'fast' categories, using DeepSource for coverage analysis of fast tests, and updating the CI workflow to handle these changes. Additionally, it refactors some slow tests into faster, parameterized tests and updates the contributing guide.

• New Features:
  • Introduced the use of DeepSource for coverage analysis of fast tests.
• Enhancements:
  • Split tests into 'slow' and 'fast' categories to optimize coverage analysis and performance.
  • Updated the contributing guide to include instructions on running fast tests first.
  • Refactored some slow unit tests into faster, parameterized tests using pytest.mark.parametrize.
• CI:
  • Modified CI workflow to run tests on different operating systems and Python versions.
  • Added steps to run pytest with and without coverage for fast tests, and without coverage for slow tests.
  • Configured DeepSource to upload coverage reports only on Linux.
• Documentation:
  • Updated the contributing guide to show how to run fast tests first.
• Tests:
  • Refactored multiple test functions to use pytest.mark.parametrize for better organization and performance.
  • Marked certain tests as 'slow' using pytest.mark.slow to differentiate them from fast tests.

[sourcery-ai[bot]]

Reviewer's Guide by Sourcery

This pull request optimizes the test suite by categorizing tests into fast and slow groups, refactoring some slow tests into smaller, parameterized ones, and updating the CI workflow to handle these changes. Additionally, the contributing guide has been updated to reflect the new testing strategy.

File-Level Changes

Files	Changes
iodata/test/test_fchk.py iodata/test/test_wfx.py iodata/test/test_wfn.py iodata/test/test_molekel.py	Refactored multiple individual test functions into parameterized tests using pytest.mark.parametrize and marked specific tests as slow using pytest.mark.slow.
.github/workflows/pytest.yaml .deepsource.toml	Updated CI workflow to run fast tests with coverage analysis on Linux and upload the coverage report to Deepsource. Enabled test-coverage analyzer in Deepsource configuration.

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[deepsource-io[bot]]

Here's the code health analysis summary for commits 286d95f..ac34301. View details on DeepSource ↗.

Analysis Summary

Analyzer	Status	Summary	Link
Test coverage	⚠️ Artifact not reported	Timed out: Artifact was never reported	View Check ↗
Shell	✅ Success		View Check ↗
Python	✅ Success		View Check ↗

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[tovrstra]

Thanks for checking. Going in...