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Merged
dcherian merged 23 commits into from
Jun 9, 2025

Merge branch 'main' into jupyter-sphinx

dea0c23
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Merged

Switch docs to jupyter-execute sphinx extension for HTML reprs #10383

Merge branch 'main' into jupyter-sphinx
dea0c23
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GitHub Actions / Test Results failed Jun 9, 2025 in 0s

220 errors, 4 797 fail, 2 343 skipped, 15 743 pass in 1h 41m 11s

     13 files  ±  0       13 suites  ±0   1h 41m 11s ⏱️ + 20m 43s
 23 103 tests + 20   15 743 ✅  -  4 951   2 343 💤  - 42  4 797 ❌ +4 793  220 🔥 +220 
196 280 runs   - 170  159 912 ✅  - 10 219  26 336 💤 +21  9 586 ❌ +9 582  446 🔥 +446 

Results for commit dea0c23. ± Comparison against earlier commit 8ca7819.

Annotations

Check warning on line 0 in xarray.tests.test_backends.TestDask

See this annotation in the file changed.

@github-actions github-actions / Test Results

1 out of 11 runs failed: test_dask_roundtrip (xarray.tests.test_backends.TestDask) 

artifacts/Test results for Linux-3.13 flaky/pytest.xml [took 3m 0s]
Raw output 
Failed: Timeout (>180.0s) from pytest-timeout.
self = <xarray.tests.test_backends.TestDask object at 0x7fd354cf1db0>

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.flaky#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_dask_roundtrip#x1B[39;49;00m(#x1B[96mself#x1B[39;49;00m) -> #x1B[94mNone#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
        #x1B[94mwith#x1B[39;49;00m create_tmp_file() #x1B[94mas#x1B[39;49;00m tmp:#x1B[90m#x1B[39;49;00m
            data = create_test_data()#x1B[90m#x1B[39;49;00m
>           data.to_netcdf(tmp)#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:5275: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:2029: in to_netcdf
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m to_netcdf(  #x1B[90m# type: ignore[return-value]  # mypy cannot resolve the overloads:(#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/backends/api.py#x1B[0m:1928: in to_netcdf
    #x1B[0mdump_to_store(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/backends/api.py#x1B[0m:1975: in dump_to_store
    #x1B[0mstore.store(variables, attrs, check_encoding, writer, unlimited_dims=unlimited_dims)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/backends/common.py#x1B[0m:460: in store
    #x1B[0m#x1B[96mself#x1B[39;49;00m.set_variables(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/backends/common.py#x1B[0m:502: in set_variables
    #x1B[0mwriter.add(source, target)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/backends/common.py#x1B[0m:344: in add
    #x1B[0mtarget[...] = source#x1B[90m#x1B[39;49;00m
    ^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/backends/netCDF4_.py#x1B[0m:80: in __setitem__
    #x1B[0m#x1B[94mwith#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m.datastore.lock:#x1B[90m#x1B[39;49;00m
         ^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/backends/locks.py#x1B[0m:229: in __enter__
    #x1B[0mlock.#x1B[92m__enter__#x1B[39;49;00m()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <SerializableLock: adb02dd5-390a-4296-bced-f84bcd3b5012>

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m__enter__#x1B[39;49;00m(#x1B[96mself#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
>       #x1B[96mself#x1B[39;49;00m.lock.#x1B[92m__enter__#x1B[39;49;00m()#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE       Failed: Timeout (>180.0s) from pytest-timeout.#x1B[0m

#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/backends/locks.py#x1B[0m:64: Failed

Check warning on line 0 in xarray.tests.test_backends.TestPydap

See this annotation in the file changed.

@github-actions github-actions / Test Results

3 out of 10 runs failed: test_cmp_local_file (xarray.tests.test_backends.TestPydap) 

artifacts/Test results for Linux-3.13 all-but-numba/pytest.xml [took 0s]
artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
AssertionError: Left and right Dataset objects are not equal
Differing data variables:
L   bears    (i, j) |S3 18B b'ind' b'ist' b'ing' b'uis' b'hab' b'le'
R   bears    (i, j) <U4 96B 'ind' 'ist' 'ing' 'uis' 'hab' 'le'
self = <xarray.tests.test_backends.TestPydap object at 0x000001C9EBBA0050>

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_cmp_local_file#x1B[39;49;00m(#x1B[96mself#x1B[39;49;00m) -> #x1B[94mNone#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
        #x1B[94mwith#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m.create_datasets() #x1B[94mas#x1B[39;49;00m (actual, expected):#x1B[90m#x1B[39;49;00m
>           assert_equal(actual, expected)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           AssertionError: Left and right Dataset objects are not equal#x1B[0m
#x1B[1m#x1B[31mE           Differing data variables:#x1B[0m
#x1B[1m#x1B[31mE           L   bears    (i, j) |S3 18B b'ind' b'ist' b'ing' b'uis' b'hab' b'le'#x1B[0m
#x1B[1m#x1B[31mE           R   bears    (i, j) <U4 96B 'ind' 'ist' 'ing' 'uis' 'hab' 'le'#x1B[0m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_backends.py#x1B[0m:5396: AssertionError

Check warning on line 0 in xarray.tests.test_backends.TestPydap

See this annotation in the file changed.

@github-actions github-actions / Test Results

3 out of 10 runs failed: test_dask (xarray.tests.test_backends.TestPydap) 

artifacts/Test results for Linux-3.13 all-but-numba/pytest.xml [took 0s]
artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
AssertionError: Left and right Dataset objects are not equal
Differing data variables:
L   bears    (i, j) |S3 18B b'ind' b'ist' b'ing' b'uis' b'hab' b'le'
R   bears    (i, j) <U4 96B 'ind' 'ist' 'ing' 'uis' 'hab' 'le'
self = <xarray.tests.test_backends.TestPydap object at 0x000001C9EBB94770>

    #x1B[0m#x1B[37m@requires_dask#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_dask#x1B[39;49;00m(#x1B[96mself#x1B[39;49;00m) -> #x1B[94mNone#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
        #x1B[94mwith#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m.create_datasets(chunks={#x1B[33m"#x1B[39;49;00m#x1B[33mj#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: #x1B[94m2#x1B[39;49;00m}) #x1B[94mas#x1B[39;49;00m (actual, expected):#x1B[90m#x1B[39;49;00m
>           assert_equal(actual, expected)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           AssertionError: Left and right Dataset objects are not equal#x1B[0m
#x1B[1m#x1B[31mE           Differing data variables:#x1B[0m
#x1B[1m#x1B[31mE           L   bears    (i, j) |S3 18B b'ind' b'ist' b'ing' b'uis' b'hab' b'le'#x1B[0m
#x1B[1m#x1B[31mE           R   bears    (i, j) <U4 96B 'ind' 'ist' 'ing' 'uis' 'hab' 'le'#x1B[0m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_backends.py#x1B[0m:5439: AssertionError

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_convert_calendar_360_days[date-standard-360_day-D] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = 'standard', target = '360_day', freq = 'D', align_on = 'date'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target,freq#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m4h#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[33m"#x1B[39;49;00m#x1B[33malign_on#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, [#x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33myear#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m])#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_convert_calendar_360_days#x1B[39;49;00m(source, target, freq, align_on):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-12-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=freq, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        conv = convert_calendar(da_src, target, align_on=align_on)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94massert#x1B[39;49;00m conv.time.dt.calendar == target#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m align_on == #x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
            np.testing.assert_array_equal(#x1B[90m#x1B[39;49;00m
>               conv.time.resample(time=#x1B[33m"#x1B[39;49;00m#x1B[33mME#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).last().dt.day,#x1B[90m#x1B[39;49;00m
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
                [#x1B[94m30#x1B[39;49;00m, #x1B[94m29#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m],#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:109: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1482: in last
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._first_or_last(#x1B[33m"#x1B[39;49;00m#x1B[33mlast#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, skipna, keep_attrs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\resample.py#x1B[0m:114: in _first_or_last
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m()._first_or_last(op=op, skipna=skipna, keep_attrs=keep_attrs)#x1B[90m#x1B[39;49;00m
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1423: in _first_or_last
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mxrdtypes#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_backends.TestNetCDF4ViaDaskData

See this annotation in the file changed.

@github-actions github-actions / Test Results

1 out of 11 runs failed: test_roundtrip_coordinates (xarray.tests.test_backends.TestNetCDF4ViaDaskData) 

artifacts/Test results for Linux-3.13 flaky/pytest.xml [took 3m 0s]
Raw output 
Failed: Timeout (>180.0s) from pytest-timeout.
self = <xarray.tests.test_backends.TestNetCDF4ViaDaskData object at 0x7fd355a54b00>

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.flaky#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_roundtrip_coordinates#x1B[39;49;00m(#x1B[96mself#x1B[39;49;00m) -> #x1B[94mNone#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
>       #x1B[96msuper#x1B[39;49;00m().test_roundtrip_coordinates()#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:2277: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:671: in test_roundtrip_coordinates
    #x1B[0m#x1B[94mwith#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m.roundtrip(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/micromamba/envs/xarray-tests/lib/python3.13/contextlib.py#x1B[0m:141: in __enter__
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mnext#x1B[39;49;00m(#x1B[96mself#x1B[39;49;00m.gen)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:2243: in roundtrip
    #x1B[0m#x1B[94mwith#x1B[39;49;00m TestNetCDF4Data.roundtrip(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/micromamba/envs/xarray-tests/lib/python3.13/contextlib.py#x1B[0m:141: in __enter__
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mnext#x1B[39;49;00m(#x1B[96mself#x1B[39;49;00m.gen)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:371: in roundtrip
    #x1B[0m#x1B[96mself#x1B[39;49;00m.save(data, path, **save_kwargs)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:392: in save
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m dataset.to_netcdf(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:2029: in to_netcdf
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m to_netcdf(  #x1B[90m# type: ignore[return-value]  # mypy cannot resolve the overloads:(#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/backends/api.py#x1B[0m:1937: in to_netcdf
    #x1B[0mwrites = writer.sync(compute=compute)#x1B[90m#x1B[39;49;00m
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/backends/common.py#x1B[0m:357: in sync
    #x1B[0mdelayed_store = chunkmanager.store(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/daskmanager.py#x1B[0m:247: in store
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m store(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/micromamba/envs/xarray-tests/lib/python3.13/site-packages/dask/array/core.py#x1B[0m:1227: in store
    #x1B[0mdask.compute(arrays, **kwargs)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/micromamba/envs/xarray-tests/lib/python3.13/site-packages/dask/base.py#x1B[0m:681: in compute
    #x1B[0mresults = schedule(expr, keys, **kwargs)#x1B[90m#x1B[39;49;00m
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31m/home/runner/micromamba/envs/xarray-tests/lib/python3.13/queue.py#x1B[0m:202: in get
    #x1B[0m#x1B[96mself#x1B[39;49;00m.not_empty.wait()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <Condition(<unlocked _thread.lock object at 0x7fd326d228d0>, 0)>
timeout = None

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mwait#x1B[39;49;00m(#x1B[96mself#x1B[39;49;00m, timeout=#x1B[94mNone#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""Wait until notified or until a timeout occurs.#x1B[39;49;00m
    #x1B[33m#x1B[39;49;00m
    #x1B[33m    If the calling thread has not acquired the lock when this method is#x1B[39;49;00m
    #x1B[33m    called, a RuntimeError is raised.#x1B[39;49;00m
    #x1B[33m#x1B[39;49;00m
    #x1B[33m    This method releases the underlying lock, and then blocks until it is#x1B[39;49;00m
    #x1B[33m    awakened by a notify() or notify_all() call for the same condition#x1B[39;49;00m
    #x1B[33m    variable in another thread, or until the optional timeout occurs. Once#x1B[39;49;00m
    #x1B[33m    awakened or timed out, it re-acquires the lock and returns.#x1B[39;49;00m
    #x1B[33m#x1B[39;49;00m
    #x1B[33m    When the timeout argument is present and not None, it should be a#x1B[39;49;00m
    #x1B[33m    floating-point number specifying a timeout for the operation in seconds#x1B[39;49;00m
    #x1B[33m    (or fractions thereof).#x1B[39;49;00m
    #x1B[33m#x1B[39;49;00m
    #x1B[33m    When the underlying lock is an RLock, it is not released using its#x1B[39;49;00m
    #x1B[33m    release() method, since this may not actually unlock the lock when it#x1B[39;49;00m
    #x1B[33m    was acquired multiple times recursively. Instead, an internal interface#x1B[39;49;00m
    #x1B[33m    of the RLock class is used, which really unlocks it even when it has#x1B[39;49;00m
    #x1B[33m    been recursively acquired several times. Another internal interface is#x1B[39;49;00m
    #x1B[33m    then used to restore the recursion level when the lock is reacquired.#x1B[39;49;00m
    #x1B[33m#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m #x1B[95mnot#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._is_owned():#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mRuntimeError#x1B[39;49;00m(#x1B[33m"#x1B[39;49;00m#x1B[33mcannot wait on un-acquired lock#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
        waiter = _allocate_lock()#x1B[90m#x1B[39;49;00m
        waiter.acquire()#x1B[90m#x1B[39;49;00m
        #x1B[96mself#x1B[39;49;00m._waiters.append(waiter)#x1B[90m#x1B[39;49;00m
        saved_state = #x1B[96mself#x1B[39;49;00m._release_save()#x1B[90m#x1B[39;49;00m
        gotit = #x1B[94mFalse#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[94mtry#x1B[39;49;00m:    #x1B[90m# restore state no matter what (e.g., KeyboardInterrupt)#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
            #x1B[94mif#x1B[39;49;00m timeout #x1B[95mis#x1B[39;49;00m #x1B[94mNone#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
>               waiter.acquire()#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE               Failed: Timeout (>180.0s) from pytest-timeout.#x1B[0m

#x1B[1m#x1B[31m/home/runner/micromamba/envs/xarray-tests/lib/python3.13/threading.py#x1B[0m:359: Failed

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_convert_calendar_360_days[date-360_day-proleptic_gregorian-D] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = '360_day', target = 'proleptic_gregorian', freq = 'D'
align_on = 'date'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target,freq#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m4h#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[33m"#x1B[39;49;00m#x1B[33malign_on#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, [#x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33myear#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m])#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_convert_calendar_360_days#x1B[39;49;00m(source, target, freq, align_on):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-12-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=freq, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        conv = convert_calendar(da_src, target, align_on=align_on)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94massert#x1B[39;49;00m conv.time.dt.calendar == target#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m align_on == #x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
            np.testing.assert_array_equal(#x1B[90m#x1B[39;49;00m
>               conv.time.resample(time=#x1B[33m"#x1B[39;49;00m#x1B[33mME#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).last().dt.day,#x1B[90m#x1B[39;49;00m
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
                [#x1B[94m30#x1B[39;49;00m, #x1B[94m29#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m],#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:109: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1482: in last
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._first_or_last(#x1B[33m"#x1B[39;49;00m#x1B[33mlast#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, skipna, keep_attrs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\resample.py#x1B[0m:114: in _first_or_last
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m()._first_or_last(op=op, skipna=skipna, keep_attrs=keep_attrs)#x1B[90m#x1B[39;49;00m
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1423: in _first_or_last
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mxrdtypes#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_convert_calendar_360_days[date-proleptic_gregorian-360_day-4h] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = 'proleptic_gregorian', target = '360_day', freq = '4h'
align_on = 'date'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target,freq#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m4h#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[33m"#x1B[39;49;00m#x1B[33malign_on#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, [#x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33myear#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m])#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_convert_calendar_360_days#x1B[39;49;00m(source, target, freq, align_on):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-12-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=freq, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        conv = convert_calendar(da_src, target, align_on=align_on)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94massert#x1B[39;49;00m conv.time.dt.calendar == target#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m align_on == #x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
            np.testing.assert_array_equal(#x1B[90m#x1B[39;49;00m
>               conv.time.resample(time=#x1B[33m"#x1B[39;49;00m#x1B[33mME#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).last().dt.day,#x1B[90m#x1B[39;49;00m
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
                [#x1B[94m30#x1B[39;49;00m, #x1B[94m29#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m],#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:109: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1482: in last
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._first_or_last(#x1B[33m"#x1B[39;49;00m#x1B[33mlast#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, skipna, keep_attrs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\resample.py#x1B[0m:114: in _first_or_last
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m()._first_or_last(op=op, skipna=skipna, keep_attrs=keep_attrs)#x1B[90m#x1B[39;49;00m
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1423: in _first_or_last
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mxrdtypes#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_convert_calendar_360_days[year-standard-360_day-D] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = 'standard', target = '360_day', freq = 'D', align_on = 'year'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target,freq#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m4h#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[33m"#x1B[39;49;00m#x1B[33malign_on#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, [#x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33myear#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m])#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_convert_calendar_360_days#x1B[39;49;00m(source, target, freq, align_on):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-12-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=freq, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        conv = convert_calendar(da_src, target, align_on=align_on)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94massert#x1B[39;49;00m conv.time.dt.calendar == target#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m align_on == #x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
            np.testing.assert_array_equal(#x1B[90m#x1B[39;49;00m
                conv.time.resample(time=#x1B[33m"#x1B[39;49;00m#x1B[33mME#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).last().dt.day,#x1B[90m#x1B[39;49;00m
                [#x1B[94m30#x1B[39;49;00m, #x1B[94m29#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m],#x1B[90m#x1B[39;49;00m
            )#x1B[90m#x1B[39;49;00m
        #x1B[94melif#x1B[39;49;00m target == #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
            np.testing.assert_array_equal(#x1B[90m#x1B[39;49;00m
>               conv.time.resample(time=#x1B[33m"#x1B[39;49;00m#x1B[33mME#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).last().dt.day,#x1B[90m#x1B[39;49;00m
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
                [#x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m29#x1B[39;49;00m],#x1B[90m#x1B[39;49;00m
            )#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:114: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1482: in last
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._first_or_last(#x1B[33m"#x1B[39;49;00m#x1B[33mlast#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, skipna, keep_attrs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\resample.py#x1B[0m:114: in _first_or_last
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m()._first_or_last(op=op, skipna=skipna, keep_attrs=keep_attrs)#x1B[90m#x1B[39;49;00m
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1423: in _first_or_last
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mxrdtypes#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_convert_calendar_360_days[year-360_day-proleptic_gregorian-D] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = '360_day', target = 'proleptic_gregorian', freq = 'D'
align_on = 'year'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target,freq#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m4h#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[33m"#x1B[39;49;00m#x1B[33malign_on#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, [#x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33myear#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m])#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_convert_calendar_360_days#x1B[39;49;00m(source, target, freq, align_on):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-12-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=freq, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        conv = convert_calendar(da_src, target, align_on=align_on)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94massert#x1B[39;49;00m conv.time.dt.calendar == target#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m align_on == #x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
            np.testing.assert_array_equal(#x1B[90m#x1B[39;49;00m
                conv.time.resample(time=#x1B[33m"#x1B[39;49;00m#x1B[33mME#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).last().dt.day,#x1B[90m#x1B[39;49;00m
                [#x1B[94m30#x1B[39;49;00m, #x1B[94m29#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m],#x1B[90m#x1B[39;49;00m
            )#x1B[90m#x1B[39;49;00m
        #x1B[94melif#x1B[39;49;00m target == #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
            np.testing.assert_array_equal(#x1B[90m#x1B[39;49;00m
                conv.time.resample(time=#x1B[33m"#x1B[39;49;00m#x1B[33mME#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).last().dt.day,#x1B[90m#x1B[39;49;00m
                [#x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m29#x1B[39;49;00m],#x1B[90m#x1B[39;49;00m
            )#x1B[90m#x1B[39;49;00m
        #x1B[94melse#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
            np.testing.assert_array_equal(#x1B[90m#x1B[39;49;00m
>               conv.time.resample(time=#x1B[33m"#x1B[39;49;00m#x1B[33mME#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).last().dt.day,#x1B[90m#x1B[39;49;00m
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
                [#x1B[94m30#x1B[39;49;00m, #x1B[94m29#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m31#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m31#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m31#x1B[39;49;00m, #x1B[94m29#x1B[39;49;00m, #x1B[94m31#x1B[39;49;00m],#x1B[90m#x1B[39;49;00m
            )#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:119: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1482: in last
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._first_or_last(#x1B[33m"#x1B[39;49;00m#x1B[33mlast#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, skipna, keep_attrs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\resample.py#x1B[0m:114: in _first_or_last
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m()._first_or_last(op=op, skipna=skipna, keep_attrs=keep_attrs)#x1B[90m#x1B[39;49;00m
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1423: in _first_or_last
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mxrdtypes#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_convert_calendar_360_days[year-proleptic_gregorian-360_day-4h] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 2s]
artifacts/Test results for macOS-3.13/pytest.xml [took 1s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = 'proleptic_gregorian', target = '360_day', freq = '4h'
align_on = 'year'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target,freq#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m4h#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[33m"#x1B[39;49;00m#x1B[33malign_on#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, [#x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33myear#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m])#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_convert_calendar_360_days#x1B[39;49;00m(source, target, freq, align_on):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-12-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=freq, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        conv = convert_calendar(da_src, target, align_on=align_on)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94massert#x1B[39;49;00m conv.time.dt.calendar == target#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m align_on == #x1B[33m"#x1B[39;49;00m#x1B[33mdate#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
            np.testing.assert_array_equal(#x1B[90m#x1B[39;49;00m
                conv.time.resample(time=#x1B[33m"#x1B[39;49;00m#x1B[33mME#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).last().dt.day,#x1B[90m#x1B[39;49;00m
                [#x1B[94m30#x1B[39;49;00m, #x1B[94m29#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m],#x1B[90m#x1B[39;49;00m
            )#x1B[90m#x1B[39;49;00m
        #x1B[94melif#x1B[39;49;00m target == #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
            np.testing.assert_array_equal(#x1B[90m#x1B[39;49;00m
>               conv.time.resample(time=#x1B[33m"#x1B[39;49;00m#x1B[33mME#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).last().dt.day,#x1B[90m#x1B[39;49;00m
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
                [#x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m30#x1B[39;49;00m, #x1B[94m29#x1B[39;49;00m],#x1B[90m#x1B[39;49;00m
            )#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:114: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1482: in last
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._first_or_last(#x1B[33m"#x1B[39;49;00m#x1B[33mlast#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, skipna, keep_attrs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\resample.py#x1B[0m:114: in _first_or_last
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m()._first_or_last(op=op, skipna=skipna, keep_attrs=keep_attrs)#x1B[90m#x1B[39;49;00m
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1423: in _first_or_last
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mxrdtypes#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_cftimeindex

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 10 runs failed: test_groupby[365_day] (xarray.tests.test_cftimeindex) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
da = <xarray.DataArray (time: 4)> Size: 32B
array([1, 2, 3, 4])
Coordinates:
  * time     (time) object 32B 0001-01-01 00:00:00 ... 0002-02-01 00:00:00

    #x1B[0m#x1B[37m@requires_cftime#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_groupby#x1B[39;49;00m(da):#x1B[90m#x1B[39;49;00m
>       result = da.groupby(#x1B[33m"#x1B[39;49;00m#x1B[33mtime.month#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).sum(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_cftimeindex.py#x1B[0m:528: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:7475: in sum
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._flox_reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1035: in _flox_reduce
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_cftimeindex

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 10 runs failed: test_groupby[360_day] (xarray.tests.test_cftimeindex) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
da = <xarray.DataArray (time: 4)> Size: 32B
array([1, 2, 3, 4])
Coordinates:
  * time     (time) object 32B 0001-01-01 00:00:00 ... 0002-02-01 00:00:00

    #x1B[0m#x1B[37m@requires_cftime#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_groupby#x1B[39;49;00m(da):#x1B[90m#x1B[39;49;00m
>       result = da.groupby(#x1B[33m"#x1B[39;49;00m#x1B[33mtime.month#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).sum(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_cftimeindex.py#x1B[0m:528: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:7475: in sum
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._flox_reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1035: in _flox_reduce
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_cftimeindex

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 10 runs failed: test_groupby[julian] (xarray.tests.test_cftimeindex) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
da = <xarray.DataArray (time: 4)> Size: 32B
array([1, 2, 3, 4])
Coordinates:
  * time     (time) object 32B 0001-01-01 00:00:00 ... 0002-02-01 00:00:00

    #x1B[0m#x1B[37m@requires_cftime#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_groupby#x1B[39;49;00m(da):#x1B[90m#x1B[39;49;00m
>       result = da.groupby(#x1B[33m"#x1B[39;49;00m#x1B[33mtime.month#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).sum(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_cftimeindex.py#x1B[0m:528: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:7475: in sum
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._flox_reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1035: in _flox_reduce
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_cftimeindex

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 10 runs failed: test_groupby[all_leap] (xarray.tests.test_cftimeindex) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
da = <xarray.DataArray (time: 4)> Size: 32B
array([1, 2, 3, 4])
Coordinates:
  * time     (time) object 32B 0001-01-01 00:00:00 ... 0002-02-01 00:00:00

    #x1B[0m#x1B[37m@requires_cftime#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_groupby#x1B[39;49;00m(da):#x1B[90m#x1B[39;49;00m
>       result = da.groupby(#x1B[33m"#x1B[39;49;00m#x1B[33mtime.month#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).sum(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_cftimeindex.py#x1B[0m:528: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:7475: in sum
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._flox_reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1035: in _flox_reduce
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_cftimeindex

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 10 runs failed: test_groupby[366_day] (xarray.tests.test_cftimeindex) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
da = <xarray.DataArray (time: 4)> Size: 32B
array([1, 2, 3, 4])
Coordinates:
  * time     (time) object 32B 0001-01-01 00:00:00 ... 0002-02-01 00:00:00

    #x1B[0m#x1B[37m@requires_cftime#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_groupby#x1B[39;49;00m(da):#x1B[90m#x1B[39;49;00m
>       result = da.groupby(#x1B[33m"#x1B[39;49;00m#x1B[33mtime.month#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).sum(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_cftimeindex.py#x1B[0m:528: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:7475: in sum
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._flox_reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1035: in _flox_reduce
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_cftimeindex

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 10 runs failed: test_groupby[gregorian] (xarray.tests.test_cftimeindex) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
da = <xarray.DataArray (time: 4)> Size: 32B
array([1, 2, 3, 4])
Coordinates:
  * time     (time) object 32B 0001-01-01 00:00:00 ... 0002-02-01 00:00:00

    #x1B[0m#x1B[37m@requires_cftime#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_groupby#x1B[39;49;00m(da):#x1B[90m#x1B[39;49;00m
>       result = da.groupby(#x1B[33m"#x1B[39;49;00m#x1B[33mtime.month#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).sum(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_cftimeindex.py#x1B[0m:528: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:7475: in sum
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._flox_reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1035: in _flox_reduce
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_cftimeindex

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 10 runs failed: test_groupby[proleptic_gregorian] (xarray.tests.test_cftimeindex) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
da = <xarray.DataArray (time: 4)> Size: 32B
array([1, 2, 3, 4])
Coordinates:
  * time     (time) object 32B 0001-01-01 00:00:00 ... 0002-02-01 00:00:00

    #x1B[0m#x1B[37m@requires_cftime#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_groupby#x1B[39;49;00m(da):#x1B[90m#x1B[39;49;00m
>       result = da.groupby(#x1B[33m"#x1B[39;49;00m#x1B[33mtime.month#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m).sum(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_cftimeindex.py#x1B[0m:528: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:7475: in sum
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._flox_reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1035: in _flox_reduce
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_interp_calendar[standard-noleap] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = 'standard', target = 'noleap'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mall_leap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_interp_calendar#x1B[39;49;00m(source, target):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        tgt = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=target),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        conv = interp_calendar(da_src, tgt)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        assert_identical(tgt.time, conv.time)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
>       np.testing.assert_almost_equal(conv.max(), #x1B[94m1#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                                       ^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:281: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:2820: in max
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m.reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\dataarray.py#x1B[0m:3857: in reduce
    #x1B[0mvar = #x1B[96mself#x1B[39;49;00m.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\variable.py#x1B[0m:1667: in reduce
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m().reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\namedarray\core.py#x1B[0m:922: in reduce
    #x1B[0mdata = func(#x1B[96mself#x1B[39;49;00m.data, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\duck_array_ops.py#x1B[0m:533: in f
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m func(values, axis=axis, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\computation\nanops.py#x1B[0m:78: in nanmax
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m nputils.nanmax(a, axis=axis)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\nputils.py#x1B[0m:211: in f
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumbagg#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_interp_calendar[noleap-proleptic_gregorian] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = 'noleap', target = 'proleptic_gregorian'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mall_leap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_interp_calendar#x1B[39;49;00m(source, target):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        tgt = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=target),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        conv = interp_calendar(da_src, tgt)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        assert_identical(tgt.time, conv.time)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
>       np.testing.assert_almost_equal(conv.max(), #x1B[94m1#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                                       ^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:281: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:2820: in max
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m.reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\dataarray.py#x1B[0m:3857: in reduce
    #x1B[0mvar = #x1B[96mself#x1B[39;49;00m.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\variable.py#x1B[0m:1667: in reduce
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m().reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\namedarray\core.py#x1B[0m:922: in reduce
    #x1B[0mdata = func(#x1B[96mself#x1B[39;49;00m.data, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\duck_array_ops.py#x1B[0m:533: in f
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m func(values, axis=axis, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\computation\nanops.py#x1B[0m:78: in nanmax
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m nputils.nanmax(a, axis=axis)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\nputils.py#x1B[0m:211: in f
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumbagg#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_interp_calendar[standard-360_day] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = 'standard', target = '360_day'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mall_leap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_interp_calendar#x1B[39;49;00m(source, target):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        tgt = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=target),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        conv = interp_calendar(da_src, tgt)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        assert_identical(tgt.time, conv.time)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
>       np.testing.assert_almost_equal(conv.max(), #x1B[94m1#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                                       ^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:281: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:2820: in max
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m.reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\dataarray.py#x1B[0m:3857: in reduce
    #x1B[0mvar = #x1B[96mself#x1B[39;49;00m.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\variable.py#x1B[0m:1667: in reduce
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m().reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\namedarray\core.py#x1B[0m:922: in reduce
    #x1B[0mdata = func(#x1B[96mself#x1B[39;49;00m.data, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\duck_array_ops.py#x1B[0m:533: in f
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m func(values, axis=axis, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\computation\nanops.py#x1B[0m:78: in nanmax
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m nputils.nanmax(a, axis=axis)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\nputils.py#x1B[0m:211: in f
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumbagg#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_interp_calendar[360_day-proleptic_gregorian] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = '360_day', target = 'proleptic_gregorian'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mall_leap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_interp_calendar#x1B[39;49;00m(source, target):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        tgt = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=target),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        conv = interp_calendar(da_src, tgt)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        assert_identical(tgt.time, conv.time)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
>       np.testing.assert_almost_equal(conv.max(), #x1B[94m1#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                                       ^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:281: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:2820: in max
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m.reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\dataarray.py#x1B[0m:3857: in reduce
    #x1B[0mvar = #x1B[96mself#x1B[39;49;00m.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\variable.py#x1B[0m:1667: in reduce
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m().reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\namedarray\core.py#x1B[0m:922: in reduce
    #x1B[0mdata = func(#x1B[96mself#x1B[39;49;00m.data, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\duck_array_ops.py#x1B[0m:533: in f
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m func(values, axis=axis, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\computation\nanops.py#x1B[0m:78: in nanmax
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m nputils.nanmax(a, axis=axis)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\nputils.py#x1B[0m:211: in f
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumbagg#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_interp_calendar[noleap-all_leap] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = 'noleap', target = 'all_leap'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mall_leap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_interp_calendar#x1B[39;49;00m(source, target):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        tgt = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=target),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        conv = interp_calendar(da_src, tgt)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        assert_identical(tgt.time, conv.time)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
>       np.testing.assert_almost_equal(conv.max(), #x1B[94m1#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                                       ^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:281: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:2820: in max
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m.reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\dataarray.py#x1B[0m:3857: in reduce
    #x1B[0mvar = #x1B[96mself#x1B[39;49;00m.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\variable.py#x1B[0m:1667: in reduce
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m().reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\namedarray\core.py#x1B[0m:922: in reduce
    #x1B[0mdata = func(#x1B[96mself#x1B[39;49;00m.data, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\duck_array_ops.py#x1B[0m:533: in f
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m func(values, axis=axis, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\computation\nanops.py#x1B[0m:78: in nanmax
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m nputils.nanmax(a, axis=axis)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\nputils.py#x1B[0m:211: in f
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumbagg#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_calendar_ops

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_interp_calendar[360_day-noleap] (xarray.tests.test_calendar_ops) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
source = '360_day', target = 'noleap'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33msource,target#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        [#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mstandard#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mproleptic_gregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mall_leap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
            (#x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m),#x1B[90m#x1B[39;49;00m
        ],#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_interp_calendar#x1B[39;49;00m(source, target):#x1B[90m#x1B[39;49;00m
        src = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=source),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        tgt = DataArray(#x1B[90m#x1B[39;49;00m
            date_range(#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m2004-07-30#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33mD#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, calendar=target),#x1B[90m#x1B[39;49;00m
            dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,),#x1B[90m#x1B[39;49;00m
            name=#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        da_src = DataArray(#x1B[90m#x1B[39;49;00m
            np.linspace(#x1B[94m0#x1B[39;49;00m, #x1B[94m1#x1B[39;49;00m, src.size), dims=(#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,), coords={#x1B[33m"#x1B[39;49;00m#x1B[33mtime#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m: src}#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        conv = interp_calendar(da_src, tgt)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        assert_identical(tgt.time, conv.time)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
>       np.testing.assert_almost_equal(conv.max(), #x1B[94m1#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                                       ^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_calendar_ops.py#x1B[0m:281: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:2820: in max
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m.reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\dataarray.py#x1B[0m:3857: in reduce
    #x1B[0mvar = #x1B[96mself#x1B[39;49;00m.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\variable.py#x1B[0m:1667: in reduce
    #x1B[0mresult = #x1B[96msuper#x1B[39;49;00m().reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\namedarray\core.py#x1B[0m:922: in reduce
    #x1B[0mdata = func(#x1B[96mself#x1B[39;49;00m.data, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\duck_array_ops.py#x1B[0m:533: in f
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m func(values, axis=axis, **kwargs)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\computation\nanops.py#x1B[0m:78: in nanmax
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m nputils.nanmax(a, axis=axis)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\nputils.py#x1B[0m:211: in f
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumbagg#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_cftimeindex_resample

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_calendars[gregorian] (xarray.tests.test_cftimeindex_resample) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
calendar = 'gregorian'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.filterwarnings(#x1B[33m"#x1B[39;49;00m#x1B[33mignore:Converting a CFTimeIndex#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
    #x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33mcalendar#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, [#x1B[33m"#x1B[39;49;00m#x1B[33mgregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mall_leap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mjulian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_calendars#x1B[39;49;00m(calendar: #x1B[96mstr#x1B[39;49;00m) -> #x1B[94mNone#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
        #x1B[90m# Limited testing for non-standard calendars#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        freq, closed, label = #x1B[33m"#x1B[39;49;00m#x1B[33m8001min#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[94mNone#x1B[39;49;00m, #x1B[94mNone#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        xr_index = xr.date_range(#x1B[90m#x1B[39;49;00m
            start=#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01T12:07:01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
            periods=#x1B[94m7#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
            freq=#x1B[33m"#x1B[39;49;00m#x1B[33m3D#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
            calendar=calendar,#x1B[90m#x1B[39;49;00m
            use_cftime=#x1B[94mTrue#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        pd_index = pd.date_range(start=#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01T12:07:01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, periods=#x1B[94m7#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33m3D#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>       da_cftime = da(xr_index).resample(time=freq, closed=closed, label=label).mean()#x1B[90m#x1B[39;49;00m
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_cftimeindex_resample.py#x1B[0m:187: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:8619: in mean
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._flox_reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\resample.py#x1B[0m:59: in _flox_reduce
    #x1B[0m#x1B[96msuper#x1B[39;49;00m()#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1035: in _flox_reduce
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError

Check warning on line 0 in xarray.tests.test_cftimeindex_resample

See this annotation in the file changed.

@github-actions github-actions / Test Results

2 out of 9 runs failed: test_calendars[noleap] (xarray.tests.test_cftimeindex_resample) 

artifacts/Test results for Windows-3.13/pytest.xml [took 0s]
artifacts/Test results for macOS-3.13/pytest.xml [took 0s]
Raw output 
ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.
calendar = 'noleap'

    #x1B[0m#x1B[37m@pytest#x1B[39;49;00m.mark.filterwarnings(#x1B[33m"#x1B[39;49;00m#x1B[33mignore:Converting a CFTimeIndex#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
    #x1B[37m@pytest#x1B[39;49;00m.mark.parametrize(#x1B[90m#x1B[39;49;00m
        #x1B[33m"#x1B[39;49;00m#x1B[33mcalendar#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, [#x1B[33m"#x1B[39;49;00m#x1B[33mgregorian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mnoleap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mall_leap#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33m360_day#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[33m"#x1B[39;49;00m#x1B[33mjulian#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    )#x1B[90m#x1B[39;49;00m
    #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_calendars#x1B[39;49;00m(calendar: #x1B[96mstr#x1B[39;49;00m) -> #x1B[94mNone#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
        #x1B[90m# Limited testing for non-standard calendars#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        freq, closed, label = #x1B[33m"#x1B[39;49;00m#x1B[33m8001min#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, #x1B[94mNone#x1B[39;49;00m, #x1B[94mNone#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        xr_index = xr.date_range(#x1B[90m#x1B[39;49;00m
            start=#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01T12:07:01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
            periods=#x1B[94m7#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
            freq=#x1B[33m"#x1B[39;49;00m#x1B[33m3D#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
            calendar=calendar,#x1B[90m#x1B[39;49;00m
            use_cftime=#x1B[94mTrue#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        )#x1B[90m#x1B[39;49;00m
        pd_index = pd.date_range(start=#x1B[33m"#x1B[39;49;00m#x1B[33m2004-01-01T12:07:01#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, periods=#x1B[94m7#x1B[39;49;00m, freq=#x1B[33m"#x1B[39;49;00m#x1B[33m3D#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>       da_cftime = da(xr_index).resample(time=freq, closed=closed, label=label).mean()#x1B[90m#x1B[39;49;00m
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m

#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\tests\test_cftimeindex_resample.py#x1B[0m:187: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\_aggregations.py#x1B[0m:8619: in mean
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m #x1B[96mself#x1B[39;49;00m._flox_reduce(#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\resample.py#x1B[0m:59: in _flox_reduce
    #x1B[0m#x1B[96msuper#x1B[39;49;00m()#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\a\xarray\xarray\xarray\core\groupby.py#x1B[0m:1035: in _flox_reduce
    #x1B[0m#x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mflox#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\__init__.py#x1B[0m:7: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mcore#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\core.py#x1B[0m:70: in <module>
    #x1B[0mHAS_NUMBAGG = module_available(#x1B[33m"#x1B[39;49;00m#x1B[33mnumbagg#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m, minversion=#x1B[33m"#x1B[39;49;00m#x1B[33m0.3.0#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\flox\xrutils.py#x1B[0m:31: in module_available
    #x1B[0mmod = importlib.import_module(module)#x1B[90m#x1B[39;49;00m
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\importlib\__init__.py#x1B[0m:88: in import_module
    #x1B[0m#x1B[94mreturn#x1B[39;49;00m _bootstrap._gcd_import(name[level:], package, level)#x1B[90m#x1B[39;49;00m
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\__init__.py#x1B[0m:3: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96m.#x1B[39;49;00m#x1B[04m#x1B[96mfuncs#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m (#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numbagg\funcs.py#x1B[0m:4: in <module>
    #x1B[0m#x1B[94mfrom#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumba#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mimport#x1B[39;49;00m bool_, float32, float64, int32, int64#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:59: in <module>
    #x1B[0m_ensure_critical_deps()#x1B[90m#x1B[39;49;00m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92m_ensure_critical_deps#x1B[39;49;00m():#x1B[90m#x1B[39;49;00m
    #x1B[90m    #x1B[39;49;00m#x1B[33m"""#x1B[39;49;00m
    #x1B[33m    Make sure the Python, NumPy and SciPy present are supported versions.#x1B[39;49;00m
    #x1B[33m    This has to be done _before_ importing anything from Numba such that#x1B[39;49;00m
    #x1B[33m    incompatible versions can be reported to the user. If this occurs _after_#x1B[39;49;00m
    #x1B[33m    importing things from Numba and there's an issue in e.g. a Numba c-ext, a#x1B[39;49;00m
    #x1B[33m    SystemError might have occurred which prevents reporting the likely cause of#x1B[39;49;00m
    #x1B[33m    the problem (incompatible versions of critical dependencies).#x1B[39;49;00m
    #x1B[33m    """#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m#NOTE THIS CODE SHOULD NOT IMPORT ANYTHING FROM NUMBA!#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mextract_version#x1B[39;49;00m(mod):#x1B[90m#x1B[39;49;00m
            #x1B[94mreturn#x1B[39;49;00m #x1B[96mtuple#x1B[39;49;00m(#x1B[96mmap#x1B[39;49;00m(#x1B[96mint#x1B[39;49;00m, mod.__version__.split(#x1B[33m'#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m'#x1B[39;49;00m)[:#x1B[94m2#x1B[39;49;00m]))#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        PYVERSION = sys.version_info[:#x1B[94m2#x1B[39;49;00m]#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m PYVERSION < (#x1B[94m3#x1B[39;49;00m, #x1B[94m10#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs Python 3.10 or greater. Got Python #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mPYVERSION[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mimport#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnumpy#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[94mas#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[04m#x1B[96mnp#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        numpy_version = extract_version(np)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version < (#x1B[94m1#x1B[39;49;00m, #x1B[94m24#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 1.24 or greater. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
            #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m numpy_version > (#x1B[94m2#x1B[39;49;00m, #x1B[94m2#x1B[39;49;00m):#x1B[90m#x1B[39;49;00m
            msg = (#x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33mNumba needs NumPy 2.2 or less. Got NumPy #x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
                   #x1B[33mf#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m0#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m{#x1B[39;49;00mnumpy_version[#x1B[94m1#x1B[39;49;00m]#x1B[33m}#x1B[39;49;00m#x1B[33m.#x1B[39;49;00m#x1B[33m"#x1B[39;49;00m)#x1B[90m#x1B[39;49;00m
>           #x1B[94mraise#x1B[39;49;00m #x1B[96mImportError#x1B[39;49;00m(msg)#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           ImportError: Numba needs NumPy 2.2 or less. Got NumPy 2.3.#x1B[0m

#x1B[1m#x1B[31mC:\Users\runneradmin\micromamba\envs\xarray-tests\Lib\site-packages\numba\__init__.py#x1B[0m:45: ImportError
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