id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type 902031342,MDU6SXNzdWU5MDIwMzEzNDI=,5377,xr.tutorial.open_dataset should work even with locally preloaded cache.,198999,open,0,,,3,2021-05-26T08:51:02Z,2021-05-26T16:04:04Z,,NONE,,,,"**What happened**: When packaging for a Linux distribution (openSUSE in my case) there is no network access to the build machines for obvious reasons. Therefore we are very happy to preloaded cache and `xr.tutorial.open_dataset()` function. Unfortunately, with 0.18.2 (not sure about the previous versions) it doesn’t work, because `pooch.retrieve()` without `fname` parameter (even when `known_hash` is `None`) generates unique name for the data file, which is not available, therefore it fails. With the data directory expanded to `~/.cache/xarray_tutorial_data` call of `xr.tutorial.open_dataset('air_temperature')` should return the appropriate data even without the network access. This [patch](https://github.com/pydata/xarray/files/6545214/local_dataset.patch.txt) fixes that. When the datafile could be found in the local cache, `pooch.retrieve` is called with `fname` parameter. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5377/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 901856178,MDU6SXNzdWU5MDE4NTYxNzg=,5375,Tests TestDataset.test_resample_loffset and test_interpolate_1d[1-x-linear] fail on i586,198999,closed,0,,,5,2021-05-26T06:56:09Z,2021-05-26T13:46:34Z,2021-05-26T07:03:23Z,NONE,,,,"**What happened**: When running the test suite while packaging the package for openSUSE I’ve got these failed tests on i586: ``` [ 107s] ______________________ TestDataset.test_resample_loffset _______________________ [ 107s] [gw4] linux -- Python 3.9.5 /usr/bin/python3.9 [ 107s] [ 107s] self = [ 107s] [ 107s] def test_resample_loffset(self): [ 107s] times = pd.date_range(""2000-01-01"", freq=""6H"", periods=10) [ 107s] ds = Dataset( [ 107s] { [ 107s] ""foo"": ([""time"", ""x"", ""y""], np.random.randn(10, 5, 3)), [ 107s] ""bar"": (""time"", np.random.randn(10), {""meta"": ""data""}), [ 107s] ""time"": times, [ 107s] } [ 107s] ) [ 107s] ds.attrs[""dsmeta""] = ""dsdata"" [ 107s] [ 107s] # Our use of `loffset` may change if we align our API with pandas' changes. [ 107s] # ref https://github.com/pydata/xarray/pull/4537 [ 107s] actual = ds.resample(time=""24H"", loffset=""-12H"").mean().bar [ 107s] expected_ = ds.bar.to_series().resample(""24H"").mean() [ 107s] expected_.index += to_offset(""-12H"") [ 107s] expected = DataArray.from_series(expected_) [ 107s] > assert_identical(actual, expected) [ 107s] E AssertionError: Left and right DataArray objects are not identical [ 107s] E [ 107s] E Differing values: [ 107s] E L [ 107s] E array([ 0.018477, -0.178807, -0.792644]) [ 107s] E R [ 107s] E array([ 0.018477, -0.178807, -0.792644]) [ 107s] [ 107s] /home/abuild/rpmbuild/BUILD/xarray-0.18.2/xarray/tests/test_dataset.py:3991: AssertionError [ 107s] _______________________ test_interpolate_1d[1-x-linear] ________________________ [ 107s] [gw2] linux -- Python 3.9.5 /usr/bin/python3.9 [ 107s] [ 107s] method = 'linear', dim = 'x', case = 1 [ 107s] [ 107s] @pytest.mark.parametrize(""method"", [""linear"", ""cubic""]) [ 107s] @pytest.mark.parametrize(""dim"", [""x"", ""y""]) [ 107s] @pytest.mark.parametrize(""case"", [0, 1]) [ 107s] def test_interpolate_1d(method, dim, case): [ 107s] if not has_scipy: [ 107s] pytest.skip(""scipy is not installed."") [ 107s] [ 107s] if not has_dask and case in [1]: [ 107s] pytest.skip(""dask is not installed in the environment."") [ 107s] [ 107s] da = get_example_data(case) [ 107s] xdest = np.linspace(0.0, 0.9, 80) [ 107s] actual = da.interp(method=method, **{dim: xdest}) [ 107s] [ 107s] # scipy interpolation for the reference [ 107s] def func(obj, new_x): [ 107s] return scipy.interpolate.interp1d( [ 107s] da[dim], [ 107s] obj.data, [ 107s] axis=obj.get_axis_num(dim), [ 107s] bounds_error=False, [ 107s] fill_value=np.nan, [ 107s] kind=method, [ 107s] )(new_x) [ 107s] [ 107s] if dim == ""x"": [ 107s] > coords = {""x"": xdest, ""y"": da[""y""], ""x2"": (""x"", func(da[""x2""], xdest))} [ 107s] [ 107s] /home/abuild/rpmbuild/BUILD/xarray-0.18.2/xarray/tests/test_interp.py:89: [ 107s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ [ 107s] [ 107s] obj = [ 107s] dask.array [ 107s] new_x = array([0. , 0.01139241, 0.02278481, 0.03417722, 0.04556962, [ 107s] 0.05696203, 0.06835443, 0.07974684, 0.091139...35, 0.80886076, 0.82025316, 0.83164557, 0.84303797, [ 107s] 0.85443038, 0.86582278, 0.87721519, 0.88860759, 0.9 ]) [ 107s] [ 107s] def func(obj, new_x): [ 107s] > return scipy.interpolate.interp1d( [ 107s] da[dim], [ 107s] obj.data, [ 107s] axis=obj.get_axis_num(dim), [ 107s] bounds_error=False, [ 107s] fill_value=np.nan, [ 107s] kind=method, [ 107s] )(new_x) [ 107s] E AttributeError: module 'scipy' has no attribute 'interpolate' [ 107s] [ 107s] /home/abuild/rpmbuild/BUILD/xarray-0.18.2/xarray/tests/test_interp.py:79: AttributeError ``` This is the [build log](https://github.com/pydata/xarray/files/6541454/_log.txt) showing all used packages and steps leading to the failures. **Anything else we need to know?**: The first failure is easily fixed by [scipy-interpolate.patch](https://github.com/pydata/xarray/files/6544426/scipy-interpolate.patch.txt) **Environment**: see the above linked log","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5375/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue