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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 |
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2157624683 | I_kwDOAMm_X86Amr1r | 8788 | CI Failure in Xarray test suite post-Dask tokenization update | andersy005 13301940 | closed | 0 | crusaderky 6213168 | 1 | 2024-02-27T21:23:48Z | 2024-03-01T03:29:52Z | 2024-03-01T03:29:52Z | MEMBER | What is your issue?Recent changes in Dask's tokenization process (https://github.com/dask/dask/pull/10876) seem to have introduced unexpected behavior in Xarray's test suite. This has led to CI failures, specifically in tests related to tokenization. ```python ---------- coverage: platform linux, python 3.12.2-final-0 ----------- Coverage XML written to file coverage.xml =========================== short test summary info ============================ FAILED xarray/tests/test_dask.py::test_token_identical[obj0-<lambda>1] - AssertionError: assert 'bbd9679bdaf2...d3db65e29a72d' == '6352792990cf...e8004a9055314'
previously, the following code snippet would pass, verifying the consistency of tokenization in Xarray objects: ```python In [1]: import xarray as xr, numpy as np In [2]: def make_da(): ...: da = xr.DataArray( ...: np.ones((10, 20)), ...: dims=["x", "y"], ...: coords={"x": np.arange(10), "y": np.arange(100, 120)}, ...: name="a", ...: ).chunk({"x": 4, "y": 5}) ...: da.x.attrs["long_name"] = "x" ...: da.attrs["test"] = "test" ...: da.coords["c2"] = 0.5 ...: da.coords["ndcoord"] = da.x * 2 ...: da.coords["cxy"] = (da.x * da.y).chunk({"x": 4, "y": 5}) ...: ...: return da ...: In [3]: da = make_da() In [4]: import dask.base In [5]: assert dask.base.tokenize(da) == dask.base.tokenize(da.copy(deep=False)) In [6]: assert dask.base.tokenize(da) == dask.base.tokenize(da.copy(deep=True)) In [9]: dask.version Out[9]: '2023.3.0' ``` However, post-update in Dask version '2024.2.1', the same code fails: ```python In [55]: ...: def make_da(): ...: da = xr.DataArray( ...: np.ones((10, 20)), ...: dims=["x", "y"], ...: coords={"x": np.arange(10), "y": np.arange(100, 120)}, ...: name="a", ...: ).chunk({"x": 4, "y": 5}) ...: da.x.attrs["long_name"] = "x" ...: da.attrs["test"] = "test" ...: da.coords["c2"] = 0.5 ...: da.coords["ndcoord"] = da.x * 2 ...: da.coords["cxy"] = (da.x * da.y).chunk({"x": 4, "y": 5}) ...: ...: return da ...: In [56]: da = make_da() ``` ```python In [57]: assert dask.base.tokenize(da) == dask.base.tokenize(da.copy(deep=False)) AssertionError Traceback (most recent call last) Cell In[57], line 1 ----> 1 assert dask.base.tokenize(da) == dask.base.tokenize(da.copy(deep=False)) AssertionError: In [58]: dask.base.tokenize(da) Out[58]: 'bbd9679bdaf284c371cd3db65e29a72d' In [59]: dask.base.tokenize(da.copy(deep=False)) Out[59]: '6352792990cfe23adb7e8004a9055314' In [61]: dask.version Out[61]: '2024.2.1' ``` additionally, a deeper dive into
Cc @dcherian / @crusaderky for visibility |
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2106570846 | I_kwDOAMm_X859j7he | 8681 | CI Failures Associated with Pytest v8.0.0 Release | andersy005 13301940 | closed | 0 | 2 | 2024-01-29T22:45:26Z | 2024-01-31T16:53:46Z | 2024-01-31T16:53:46Z | MEMBER | What is your issue?A recent release of pytest (v8.0.0) appears to have broken our CI.
Strangely, the issue doesn't seem to occur when using previous versions (e.g.
i recreated the environment and successfully ran tests locally. the CI failures appear to be connected to the latest release of pytest. i haven't had a chance to do an in-depth exploration of the changes from pytest which could be influencing this disruption. so, i wanted to open an issue to track what is going on. in the meantime, i'm going to pin pytest to an earlier version. any insights, especially from those familiar with changes in the pytest v8.0.0 update, are warmly welcomed. |
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1035640211 | I_kwDOAMm_X849up2T | 5898 | Update docs for Dataset `reduce` methods to indicate that non-numeric data variables are dropped | andersy005 13301940 | closed | 0 | 2 | 2021-10-25T22:48:49Z | 2022-03-12T08:17:48Z | 2022-03-12T08:17:48Z | MEMBER |
```python In [47]: import xarray as xr In [48]: import numpy as np, pandas as pd In [50]: ds['foo'] = xr.DataArray(np.arange(6).reshape(2, 3), dims=['x', 'y']) In [53]: ds['bar'] = xr.DataArray(pd.date_range(start='2000', periods=6).values.reshape(2, 3), dims=['x', 'y']) In [54]: ds Out[54]: <xarray.Dataset> Dimensions: (x: 2, y: 3) Dimensions without coordinates: x, y Data variables: foo (x, y) int64 0 1 2 3 4 5 bar (x, y) datetime64[ns] 2000-01-01 2000-01-02 ... 2000-01-06 ``` ```python In [55]: ds.mean('x') Out[55]: <xarray.Dataset> Dimensions: (y: 3) Dimensions without coordinates: y Data variables: foo (y) float64 1.5 2.5 3.5 In [56]: ds.bar.mean('x') Out[56]: <xarray.DataArray 'bar' (y: 3)> array(['2000-01-02T12:00:00.000000000', '2000-01-03T12:00:00.000000000', '2000-01-04T12:00:00.000000000'], dtype='datetime64[ns]') Dimensions without coordinates: y ``` |
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731813879 | MDU6SXNzdWU3MzE4MTM4Nzk= | 4549 | [Proposal] Migrate general discussions from the xarray gitter room to GitHub Discussions | andersy005 13301940 | closed | 0 | 5 | 2020-10-28T21:48:29Z | 2020-11-25T22:28:41Z | 2020-11-25T22:28:41Z | MEMBER | Currently, xarray has a room on Gitter: https://gitter.im/pydata/xarray. This room works fine for discussions outside of the codebase. However, Gitter has a few disadvantages:
A few months ago, GitHub announced GitHub discussions which is meant to serve as a forum for discussions outside of the codebase. I am of the opinion that GitHub discussions is a better alternative to Gitter. I am wondering if xarray folks would be interested in enabling GitHub discussion on this repo, and migrating general discussions from Gitter to GitHub discussions? GitHub Discussions is still in beta, but projects can request early access here Here is a list of a few projects with beta access: |
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679445732 | MDU6SXNzdWU2Nzk0NDU3MzI= | 4341 | Computing averaged time produces wrong/incorrect time values | andersy005 13301940 | closed | 0 | 3 | 2020-08-14T23:15:01Z | 2020-08-15T20:05:23Z | 2020-08-15T20:05:23Z | MEMBER | What happened: While computing averaged time using time_bounds via What you expected to happen: Correct averaged time values Minimal Complete Verifiable Example: ```python In [1]: import xarray as xr In [2]: import numpy as np In [3]: dates = xr.cftime_range(start='0400-01', end='2101-01', freq='120Y', calendar='noleap') In [4]: bounds = xr.DataArray(np.vstack([dates[:-1], dates[1:]]).T, dims=['time', 'd2']) In [5]: bounds In [6]: bounds.mean('d2') ``` Anything else we need to know?: Environment: Output of <tt>xr.show_versions()</tt>```python INSTALLED VERSIONS ------------------ commit: None python: 3.7.8 | packaged by conda-forge | (default, Jul 23 2020, 03:54:19) [GCC 7.5.0] python-bits: 64 OS: Linux OS-release: 3.10.0-1127.13.1.el7.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: en_US.UTF-8 LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.16.0 pandas: 1.1.0 numpy: 1.19.1 scipy: 1.5.2 netCDF4: 1.5.4 pydap: None h5netcdf: None h5py: 2.10.0 Nio: None zarr: 2.4.0 cftime: 1.2.1 nc_time_axis: 1.2.0 PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: 2.22.0 distributed: 2.22.0 matplotlib: 3.3.0 cartopy: 0.18.0 seaborn: 0.10.1 numbagg: None pint: None setuptools: 49.2.1.post20200802 pip: 20.2.1 conda: None pytest: None IPython: 7.17.0 sphinx: None ``` |
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510326302 | MDU6SXNzdWU1MTAzMjYzMDI= | 3426 | `.sel()` failures when using latest cftime release (v1.0.4) | andersy005 13301940 | closed | 0 | 3 | 2019-10-21T22:19:24Z | 2019-10-22T18:31:34Z | 2019-10-22T18:31:34Z | MEMBER | I just updated to the latest ```python In [1]: import xarray as xr In [2]: import cftime In [3]: ds = xr.tutorial.load_dataset('rasm') In [4]: ds In [5]: ds.sel(time=slice("1980", "1982"))ValueError Traceback (most recent call last) <ipython-input-5-2c26e36a673a> in <module> ----> 1 ds.sel(time=slice("1980", "1982")) ~/opt/miniconda3/envs/intake-esm-dev/lib/python3.7/site-packages/xarray/core/dataset.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs) 1998 indexers = either_dict_or_kwargs(indexers, indexers_kwargs, "sel") 1999 pos_indexers, new_indexes = remap_label_indexers( -> 2000 self, indexers=indexers, method=method, tolerance=tolerance 2001 ) 2002 result = self.isel(indexers=pos_indexers, drop=drop) ~/opt/miniconda3/envs/intake-esm-dev/lib/python3.7/site-packages/xarray/core/coordinates.py in remap_label_indexers(obj, indexers, method, tolerance, **indexers_kwargs) 390 391 pos_indexers, new_indexes = indexing.remap_label_indexers( --> 392 obj, v_indexers, method=method, tolerance=tolerance 393 ) 394 # attach indexer's coordinate to pos_indexers ~/opt/miniconda3/envs/intake-esm-dev/lib/python3.7/site-packages/xarray/core/indexing.py in remap_label_indexers(data_obj, indexers, method, tolerance) 259 coords_dtype = data_obj.coords[dim].dtype 260 label = maybe_cast_to_coords_dtype(label, coords_dtype) --> 261 idxr, new_idx = convert_label_indexer(index, label, dim, method, tolerance) 262 pos_indexers[dim] = idxr 263 if new_idx is not None: ~/opt/miniconda3/envs/intake-esm-dev/lib/python3.7/site-packages/xarray/core/indexing.py in convert_label_indexer(index, label, index_name, method, tolerance) 123 _sanitize_slice_element(label.start), 124 _sanitize_slice_element(label.stop), --> 125 _sanitize_slice_element(label.step), 126 ) 127 if not isinstance(indexer, slice): ~/opt/miniconda3/envs/intake-esm-dev/lib/python3.7/site-packages/pandas/core/indexes/base.py in slice_indexer(self, start, end, step, kind) 5032 slice(1, 3) 5033 """ -> 5034 start_slice, end_slice = self.slice_locs(start, end, step=step, kind=kind) 5035 5036 # return a slice ~/opt/miniconda3/envs/intake-esm-dev/lib/python3.7/site-packages/pandas/core/indexes/base.py in slice_locs(self, start, end, step, kind) 5246 start_slice = None 5247 if start is not None: -> 5248 start_slice = self.get_slice_bound(start, "left", kind) 5249 if start_slice is None: 5250 start_slice = 0 ~/opt/miniconda3/envs/intake-esm-dev/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_slice_bound(self, label, side, kind) 5158 # For datetime indices label may be a string that has to be converted 5159 # to datetime boundary according to its resolution. -> 5160 label = self._maybe_cast_slice_bound(label, side, kind) 5161 5162 # we need to look up the label ~/opt/miniconda3/envs/intake-esm-dev/lib/python3.7/site-packages/xarray/coding/cftimeindex.py in _maybe_cast_slice_bound(self, label, side, kind) 336 pandas.tseries.index.DatetimeIndex._maybe_cast_slice_bound""" 337 if isinstance(label, str): --> 338 parsed, resolution = _parse_iso8601_with_reso(self.date_type, label) 339 start, end = _parsed_string_to_bounds(self.date_type, resolution, parsed) 340 if self.is_monotonic_decreasing and len(self) > 1: ~/opt/miniconda3/envs/intake-esm-dev/lib/python3.7/site-packages/xarray/coding/cftimeindex.py in _parse_iso8601_with_reso(date_type, timestr) 114 # 1.0.3.4. 115 replace["dayofwk"] = -1 --> 116 return default.replace(**replace), resolution 117 118 cftime/_cftime.pyx in cftime._cftime.datetime.replace() ValueError: Replacing the dayofyr or dayofwk of a datetime is not supported. ``` Output of
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