WIP: Test lowest versions of all required and optional dependencies #3639
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,8 +1,8 @@ | ||
| # Test PyGMT with GMT legacy versions and old Python dependencies on Linux/macOS/Windows | ||
| # | ||
| # This workflow runs regular PyGMT tests with GMT legacy versions and old versions of | ||
| # all optional and required Python dependencies. Due to minor baseline image changes | ||
| # between GMT versions, the workflow runs the tests but doesn't do image comparisons. | ||
| # | ||
| # It is scheduled to run every Tuesday on the main branch. | ||
| # | ||
|
|
@@ -12,7 +12,7 @@ on: | |
| # push: | ||
| # branches: [ main ] | ||
| # Uncomment the 'pull_request' line below to trigger the workflow in PR | ||
| pull_request: | ||
| # types: [ready_for_review] | ||
| # paths: | ||
| # - 'pygmt/**' | ||
|
|
@@ -61,22 +61,6 @@ jobs: | |
| python=3.11 | ||
| gmt=${{ matrix.gmt_version }} | ||
| ghostscript<10 | ||
|
|
||
| # Download cached remote files (artifacts) from GitHub | ||
| - name: Download remote data from GitHub | ||
|
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@@ -93,10 +77,21 @@ jobs: | |
| env: | ||
| GH_TOKEN: ${{ github.token }} | ||
|
|
||
| # Install uv package manager | ||
| - name: Install uv | ||
| uses: astral-sh/[email protected] | ||
| with: | ||
| activate-environment: true | ||
| python-version: 3.11 | ||
|
|
||
| # Install the package that we want to test | ||
| - name: Install the package | ||
| run: | | ||
| uv run --with pip==23 --resolution lowest-direct --all-extras --dev make install | ||
| uv pip list | ||
|
|
||
| # Run the tests but skip images | ||
| - name: Run tests | ||
| run: uv run --with pytest==8,pytest-mpl==0.17,pytest-doctestplus==1.2 --resolution lowest-direct --all-extras --dev make test_no_images PYTEST_EXTRA="-r P" | ||
| env: | ||
| GMT_LIBRARY_PATH: $CONDA_PREFIX/lib | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -38,17 +38,17 @@ dependencies = [ | |
| "numpy>=1.26", | ||
| "pandas>=2.1", | ||
| "xarray>=2023.07", | ||
| "packaging>=22.0", | ||
| ] | ||
| dynamic = ["version"] | ||
|
|
||
| [project.optional-dependencies] | ||
| all = [ | ||
| "contextily>=1.5", | ||
| "geopandas>=1.0", | ||
| "IPython>=8", # 'ipython' is not the correct module name. | ||
| "pyarrow>=16", | ||
|
There was a problem hiding this comment. Pinning to ________ test_to_numpy_pyarrow_array_pyarrow_dtypes_string[string_view] ________
> ???
E KeyError: 'string_view'
pyarrow/types.pxi:5025: KeyError
During handling of the above exception, another exception occurred:
dtype = 'string_view'
@pytest.mark.skipif(not _HAS_PYARROW, reason="pyarrow is not installed")
@pytest.mark.parametrize(
"dtype",
[
None,
"string",
"utf8", # alias for string
"large_string",
"large_utf8", # alias for large_string
"string_view",
],
)
def test_to_numpy_pyarrow_array_pyarrow_dtypes_string(dtype):
"""
Test the _to_numpy function with PyArrow arrays of PyArrow string types.
"""
> array = pa.array(["abc", "defg", "12345"], type=dtype)
../pygmt/tests/test_clib_to_numpy.py:333:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
pyarrow/array.pxi:230: in pyarrow.lib.array
???
pyarrow/types.pxi:5040: in pyarrow.lib.ensure_type
???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> ???
E ValueError: No type alias for string_view
pyarrow/types.pxi:5027: ValueErrorCode was added in #3608: pygmt/pygmt/tests/test_clib_to_numpy.py Lines 326 to 336 in 97185e8 The There was a problem hiding this comment. PyArrow v16.0 was released in April, 2024. Instead of pinning pyarrow>=16.0, we can just skip There was a problem hiding this comment. Ok, I just tested older versions from pyarrow v12 to v15, and think we can pin to _________________________________________________________________ test_to_numpy_pyarrow_array_pyarrow_dtypes_date[date64[ms]] __________________________________________________________________
dtype = 'date64[ms]', expected_dtype = 'datetime64[ms]'
@pytest.mark.skipif(not _HAS_PYARROW, reason="pyarrow is not installed")
@pytest.mark.parametrize(
("dtype", "expected_dtype"),
[
pytest.param("date32[day]", "datetime64[D]", id="date32[day]"),
pytest.param("date64[ms]", "datetime64[ms]", id="date64[ms]"),
],
)
def test_to_numpy_pyarrow_array_pyarrow_dtypes_date(dtype, expected_dtype):
"""
Test the _to_numpy function with PyArrow arrays of PyArrow date types.
date32[day] and date64[ms] are stored as 32-bit and 64-bit integers, respectively,
representing the number of days and milliseconds since the UNIX epoch (1970-01-01).
Here we explicitly check the dtype and date unit of the result.
"""
data = [
date(2024, 1, 1),
datetime(2024, 1, 2),
datetime(2024, 1, 3),
]
array = pa.array(data, type=dtype)
result = _to_numpy(array)
_check_result(result, np.datetime64)
> assert result.dtype == expected_dtype # Explicitly check the date unit.
E AssertionError: assert dtype('<M8[D]') == 'datetime64[ms]'
E + where dtype('<M8[D]') = array(['2024-01-01', '2024-01-02', '2024-01-03'], dtype='datetime64[D]').dtype
../pygmt/tests/test_clib_to_numpy.py:364: AssertionErrorThe main change appears to be in apache/arrow#33321, when pyarrow supported preserving the datetime64 temporal resolution. Maybe we can keep the |
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| "rioxarray>=0.14", | ||
| ] | ||
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| [project.entry-points."xarray.backends"] | ||
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Using
--resolution lowest-directfor now, because--resolution lowestgrabs many other transitive dependencies that may be hard to install (e.g. missing wheels for newer Python versions, so requires compilation from source). We could switch to--resolution lowestonce the Python ecosystem does lower bound pins a bit more thoroughly (which may take years).