Ouranosinc / xscen / 10799217685
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Added teststo `utils.py` and fixed bugs (#450)

<!-- Please ensure the PR fulfills the following requirements! -->
<!-- If this is your first PR, make sure to add your details to the
AUTHORS.rst! -->
### Pull Request Checklist:
- [x] This PR addresses an already opened issue (for bug fixes /
features)
    - This PR fixes #xyz
- [x] (If applicable) Documentation has been added / updated (for bug
fixes / features).
- [x] (If applicable) Tests have been added.
- [x] This PR does not seem to break the templates.
- [ ] CHANGELOG.rst has been updated (with summary of main changes).
- [ ] Link to issue (:issue:`number`) and pull request (:pull:`number`)
has been added.

### What kind of change does this PR introduce?

* Adds tests for all functions located in `utils.py`. With the exception
of a few lines impossible to test, everything should be covered.
* The `mask` argument in `stack_drop_nans` can now be a list of
dimensions. In that case, a `dropna(how='all')` operation will be used
to create the mask on-the-fly.
* `convert_calendar` in `xs.utils.clean_up` now uses `xarray` instead of
`xclim`.
* `attrs_to_remove` and `remove_all_attrs_except` in `xs.utils.clean_up`
now use real regex.
* Smaller changes:
  * `minimum_calendar` now accepts a list as input.
  * More calendars are recognized in `translate_time_chunk`
* Multiple entries can now be given for `change_attr_prefix` in
`xs.utils.clean_up`.
* `new_dim` in `unstack_dates` is now None by default and changes
depending on the frequency. It becomes `month` if the data is exactly
monthly, and keep the old default of `season` otherwise.
* Updated the list of libraries in `show_versions` to reflect our
current environment.

* Bug fixes:
  * `maybe_unstack` now works if the dimension name is not the default.
  * `xs.utils.clean_up` now does not also modify the original dataset.
* `unstack_dates` now works correctly for yearly datasets when
`winter_starts_year=True`.
... (continued)

25430 of 32836 relevant lines covered (77.45%)

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Jobs
ID Job ID Ran Files Coverage
1 run-Python3.9 - 10799217685.1 0
76.2
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2 run-Python3.10-conda - 10799217685.2 0
78.67
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3 run-Python3.11-conda - 10799217685.3 0
78.67
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4 run-Python3.9-conda - 10799217685.4 0
78.64
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5 run-Python3.10 - 10799217685.5 0
76.24
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6 run-Python3.11 - 10799217685.6 0
76.24
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7 run-Python3.12-conda - 10799217685.7 0
78.67
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8 run-Python3.12 - 10799217685.8 0
76.24
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