test_lazy_corrcov[None-3-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-3-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-7-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-7-1] RuntimeError: Too many computes. Total: 1 > max: 0.

TestDataset.test_where AttributeError: 'bool' object has no attribute 'astype'

test_where_attrs AttributeError: 'bool' object has no attribute 'astype'

TestDataArray.test_where_string TypeError: Input should be a NumPy array or scalar. It is a <class 'list'> instead.

TestOps.test_where_type_promotion TypeError: Input should be a NumPy array or scalar. It is a <class 'list'> instead.

TestDataArray.test_curvefit[False] AttributeError: 'bool' object has no attribute 'astype'

TestDataArray.test_curvefit_helpers AttributeError: 'bool' object has no attribute 'astype'

test_weather_data_resample[True] TypeError: Input should be a NumPy array or scalar. It is a <class 'xarray.core.dataarray.DataArray'> instead.

test_weather_data_resample[False] TypeError: Input should be a NumPy array or scalar. It is a <class 'xarray.core.dataarray.DataArray'> instead.

test_multiple_groupers_string[True] TypeError: Input should be a NumPy array or scalar. It is a <class 'xarray.core.dataarray.DataArray'> instead.

test_multiple_groupers_string[False] TypeError: Input should be a NumPy array or scalar. It is a <class 'xarray.core.dataarray.DataArray'> instead.

test_coarsen_coords[1-numpy-True] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

test_coarsen_coords[1-numpy-False] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

test_coarsen_reduce[numpy-sum-1-1] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

test_coarsen_reduce[numpy-sum-1-2] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

test_coarsen_reduce[numpy-sum-2-1] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

test_coarsen_reduce[numpy-sum-2-2] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

test_roundtrip_timedelta64_nanosecond_precision_warning AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

test_coarsen_reduce[numpy-sum-3-1] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

test_roundtrip_float_times[GH-8271] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

test_coarsen_reduce[numpy-sum-3-2] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

test_lazy_corrcov[None-3-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-3-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-7-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-7-1] RuntimeError: Too many computes. Total: 1 > max: 0.

TestDataArrayAndDataset.test_where_dispatching AssertionError: assert False + where False = isinstance(array([nan, nan, nan, nan, 4., 5., 6., 7., 8., 9.]), <class 'dask.array.core.Array'>) + where array([nan, nan, nan, nan, 4., 5., 6., 7., 8., 9.]) = <xarray.DataArray (dim_0: 10)> Size: 80B\narray([nan, nan, nan, nan, 4., 5., 6., 7., 8., 9.])\nDimensions without coordinates: dim_0.data + and <class 'dask.array.core.Array'> = da.Array

test_lazy_corrcov[None-3-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-3-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_map_blocks_mixed_type_inputs[obj0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-3-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-3-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-7-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-7-1] RuntimeError: Too many computes. Total: 1 > max: 0.

TestDataArrayAndDataset.test_where_dispatching AssertionError: assert False + where False = isinstance(array([nan, nan, nan, nan, 4., 5., 6., 7., 8., 9.]), <class 'dask.array.core.Array'>) + where array([nan, nan, nan, nan, 4., 5., 6., 7., 8., 9.]) = <xarray.DataArray (dim_0: 10)> Size: 80B\narray([nan, nan, nan, nan, 4., 5., 6., 7., 8., 9.])\nDimensions without coordinates: dim_0.data + and <class 'dask.array.core.Array'> = da.Array

test_lazy_corrcov[None-3-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-3-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_map_blocks_mixed_type_inputs[obj0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_map_blocks_mixed_type_inputs[obj1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-3-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-3-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-7-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-7-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-3-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-3-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-4-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-5-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-6-1] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-7-0] RuntimeError: Too many computes. Total: 1 > max: 0.

test_lazy_corrcov[None-7-1] RuntimeError: Too many computes. Total: 1 > max: 0.

TestDatetimeAccessor.test_days_in_year[standard-366] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

TestScipyInMemoryData.test_roundtrip_bytes_with_fill_value AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

TestDatetimeAccessor.test_days_in_year[noleap-365] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

TestDatetimeAccessor.test_days_in_year[all_leap-366] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

TestScipyInMemoryData.test_roundtrip_string_with_fill_value_nchar AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

TestScipyInMemoryData.test_roundtrip_mask_and_scale[dtype0-create_unsigned_masked_scaled_data-create_encoded_unsigned_masked_scaled_data] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

TestScipyInMemoryData.test_roundtrip_mask_and_scale[dtype0-create_signed_masked_scaled_data-create_encoded_signed_masked_scaled_data] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

TestScipyInMemoryData.test_roundtrip_mask_and_scale[dtype0-create_masked_and_scaled_data-create_encoded_masked_and_scaled_data] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

TestScipyInMemoryData.test_roundtrip_mask_and_scale[dtype1-create_unsigned_masked_scaled_data-create_encoded_unsigned_masked_scaled_data] AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

test_aggregation AttributeError: module 'numpy' has no attribute 'astype'. Did you mean: 'dtype'?

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deallocating CachingFileManager(<class 'netCDF4._netCDF4.Dataset'>, '/tmp/pytest-of-runner/pytest-0/popen-gw3/test_download_from_github0/xarray_tutorial_data/4c5c606840191d085ac934c9665f7387-tiny.nc', mode='r', kwargs={'clobber': True, 'diskless': False, 'persist': False, 'format': 'NETCDF4'}, manager_id='a2597f90-6695-4a14-957e-2f4e60837d94'), but file is not already closed. This may indicate a bug.

deallocating CachingFileManager(<class 'netCDF4._netCDF4.Dataset'>, '/tmp/pytest-of-runner/pytest-0/popen-gw3/test_download_from_github0/xarray_tutorial_data/4c5c606840191d085ac934c9665f7387-tiny.nc', mode='r', kwargs={'clobber': True, 'diskless': False, 'persist': False, 'format': 'NETCDF4'}, manager_id='a2597f90-6695-4a14-957e-2f4e60837d94'), but file is not already closed. This may indicate a bug.

deallocating CachingFileManager(<class 'netCDF4._netCDF4.Dataset'>, '/tmp/pytest-of-runner/pytest-0/popen-gw3/test_download_from_github_load0/xarray_tutorial_data/4c5c606840191d085ac934c9665f7387-tiny.nc', mode='r', kwargs={'clobber': True, 'diskless': False, 'persist': False, 'format': 'NETCDF4'}, manager_id='fb2af90e-3d9c-467f-87ec-712c93b57207'), but file is not already closed. This may indicate a bug.

deallocating CachingFileManager(<class 'netCDF4._netCDF4.Dataset'>, '/tmp/pytest-of-runner/pytest-0/popen-gw3/test_download_from_github_load0/xarray_tutorial_data/4c5c606840191d085ac934c9665f7387-tiny.nc', mode='r', kwargs={'clobber': True, 'diskless': False, 'persist': False, 'format': 'NETCDF4'}, manager_id='33f1951c-3f91-4969-8beb-7637eee034a2'), but file is not already closed. This may indicate a bug.

deallocating CachingFileManager(<class 'netCDF4._netCDF4.Dataset'>, '/tmp/pytest-of-runner/pytest-0/popen-gw3/test_download_from_github_load0/xarray_tutorial_data/4c5c606840191d085ac934c9665f7387-tiny.nc', mode='r', kwargs={'clobber': True, 'diskless': False, 'persist': False, 'format': 'NETCDF4'}, manager_id='fb2af90e-3d9c-467f-87ec-712c93b57207'), but file is not already closed. This may indicate a bug.

deallocating CachingFileManager(<class 'netCDF4._netCDF4.Dataset'>, '/tmp/pytest-of-runner/pytest-0/popen-gw3/test_download_from_github_load0/xarray_tutorial_data/4c5c606840191d085ac934c9665f7387-tiny.nc', mode='r', kwargs={'clobber': True, 'diskless': False, 'persist': False, 'format': 'NETCDF4'}, manager_id='33f1951c-3f91-4969-8beb-7637eee034a2'), but file is not already closed. This may indicate a bug.

PyDAP was unable to determine the DAP protocol defaulting to DAP2 which is consider legacy and may result in slower responses. For more, see go to https://www.opendap.org/faq-page.

PyDAP was unable to determine the DAP protocol defaulting to DAP2 which is consider legacy and may result in slower responses. For more, see go to https://www.opendap.org/faq-page.

Call to deprecated method findAll. (Replaced by find_all) -- Deprecated since version 4.0.0.

Call to deprecated method findAll. (Replaced by find_all) -- Deprecated since version 4.0.0.

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Cache not found for keys: Linux-X64-py3.13-2025-03-02-d88b469f63f878053725f10a66978c2ee81a9b1cd6d183569791389f18c43440-linux-64-xarray-tests-args-a3edb49-root-dcc80ee-bin-[object Promise]-file-33c9cc5a88c76e78b0fabe92743e9cb3e46dd8e3d40dab6d83e242e8d39519b8

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Cache not found for keys: Linux-X64-py3.13-2025-03-02-d88b469f63f878053725f10a66978c2ee81a9b1cd6d183569791389f18c43440-linux-64-xarray-tests-args-a3edb49-root-dcc80ee-bin-[object Promise]-file-33c9cc5a88c76e78b0fabe92743e9cb3e46dd8e3d40dab6d83e242e8d39519b8

Failed to save: Failed to CreateCacheEntry: Received non-retryable error: Failed request: (409) Conflict: cache entry with the same key, version, and scope already exists

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Cache not found for keys: Linux-X64-py3.10-2025-03-02-d88b469f63f878053725f10a66978c2ee81a9b1cd6d183569791389f18c43440-linux-64-xarray-tests-args-e0a578e-root-dcc80ee-bin-[object Promise]-file-33c9cc5a88c76e78b0fabe92743e9cb3e46dd8e3d40dab6d83e242e8d39519b8

Failed to save: Failed to CreateCacheEntry: Received non-retryable error: Failed request: (409) Conflict: cache entry with the same key, version, and scope already exists

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Cache not found for keys: macOS-ARM64-py3.10-2025-03-02-d88b469f63f878053725f10a66978c2ee81a9b1cd6d183569791389f18c43440-osx-arm64-xarray-tests-args-e0a578e-root-873f6fe-bin-[object Promise]-file-33c9cc5a88c76e78b0fabe92743e9cb3e46dd8e3d40dab6d83e242e8d39519b8

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

The experimental Zarr V3 implementation in this version of Zarr-Python is not in alignment with the final V3 specification. This version will be removed in Zarr-Python 3 in favor of a spec compliant version.

The experimental Zarr V3 implementation in this version of Zarr-Python is not in alignment with the final V3 specification. This version will be removed in Zarr-Python 3 in favor of a spec compliant version.

Duplicate dimension names present: dimensions {'x'} appear more than once in dims=('x', 'x'). We do not yet support duplicate dimension names, but we do allow initial construction of the object. We recommend you rename the dims immediately to become distinct, as most xarray functionality is likely to fail silently if you do not. To rename the dimensions you will need to set the ``.dims`` attribute of each variable, ``e.g. var.dims=('x0', 'x1')``.

Duplicate dimension names present: dimensions {'x'} appear more than once in dims=('x', 'x'). We do not yet support duplicate dimension names, but we do allow initial construction of the object. We recommend you rename the dims immediately to become distinct, as most xarray functionality is likely to fail silently if you do not. To rename the dimensions you will need to set the ``.dims`` attribute of each variable, ``e.g. var.dims=('x0', 'x1')``.

The `numpy.astype` function is not implemented by Dask array. You may want to use the da.map_blocks function or something similar to silence this warning. Your code may stop working in a future release.

The `numpy.astype` function is not implemented by Dask array. You may want to use the da.map_blocks function or something similar to silence this warning. Your code may stop working in a future release.

Consolidated metadata is currently not part in the Zarr format 3 specification. It may not be supported by other zarr implementations and may change in the future.

Consolidated metadata is currently not part in the Zarr format 3 specification. It may not be supported by other zarr implementations and may change in the future.

Consolidated metadata is currently not part in the Zarr format 3 specification. It may not be supported by other zarr implementations and may change in the future.

Consolidated metadata is currently not part in the Zarr format 3 specification. It may not be supported by other zarr implementations and may change in the future.

Consolidated metadata is currently not part in the Zarr format 3 specification. It may not be supported by other zarr implementations and may change in the future.

Consolidated metadata is currently not part in the Zarr format 3 specification. It may not be supported by other zarr implementations and may change in the future.

Consolidated metadata is currently not part in the Zarr format 3 specification. It may not be supported by other zarr implementations and may change in the future.

Consolidated metadata is currently not part in the Zarr format 3 specification. It may not be supported by other zarr implementations and may change in the future.

Consolidated metadata is currently not part in the Zarr format 3 specification. It may not be supported by other zarr implementations and may change in the future.

Consolidated metadata is currently not part in the Zarr format 3 specification. It may not be supported by other zarr implementations and may change in the future.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Cache not found for keys: Linux-X64-py3.12-2025-03-02-15ab7227e4e5c4c709e63785e07b9f9d621b9f7022ba8176de939ddc4ec63673-linux-64-xarray-tests-args-e92b363-root-dcc80ee-bin-[object Promise]-file-a1e896c24894be3d4dac7f0101eb96f13d4c16f8435131d64512d5c4fc356e92

Duplicate dimension names present: dimensions {'x'} appear more than once in dims=('x', 'x'). We do not yet support duplicate dimension names, but we do allow initial construction of the object. We recommend you rename the dims immediately to become distinct, as most xarray functionality is likely to fail silently if you do not. To rename the dimensions you will need to set the ``.dims`` attribute of each variable, ``e.g. var.dims=('x0', 'x1')``.

Duplicate dimension names present: dimensions {'x'} appear more than once in dims=('x', 'x'). We do not yet support duplicate dimension names, but we do allow initial construction of the object. We recommend you rename the dims immediately to become distinct, as most xarray functionality is likely to fail silently if you do not. To rename the dimensions you will need to set the ``.dims`` attribute of each variable, ``e.g. var.dims=('x0', 'x1')``.

invalid value encountered in cast

invalid value encountered in cast

Setuptools is replacing distutils. Support for replacing an already imported distutils is deprecated. In the future, this condition will fail. Register concerns at https://github.com/pypa/setuptools/issues/new?template=distutils-deprecation.yml

Setuptools is replacing distutils. Support for replacing an already imported distutils is deprecated. In the future, this condition will fail. Register concerns at https://github.com/pypa/setuptools/issues/new?template=distutils-deprecation.yml

the `pandas.MultiIndex` object(s) passed as 'x' coordinate(s) or data variable(s) will no longer be implicitly promoted and wrapped into multiple indexed coordinates in the future (i.e., one coordinate for each multi-index level + one dimension coordinate). If you want to keep this behavior, you need to first wrap it explicitly using `mindex_coords = xarray.Coordinates.from_pandas_multiindex(mindex_obj, 'dim')` and pass it as coordinates, e.g., `xarray.Dataset(coords=mindex_coords)`, `dataset.assign_coords(mindex_coords)` or `dataarray.assign_coords(mindex_coords)`.

the `pandas.MultiIndex` object(s) passed as 'x' coordinate(s) or data variable(s) will no longer be implicitly promoted and wrapped into multiple indexed coordinates in the future (i.e., one coordinate for each multi-index level + one dimension coordinate). If you want to keep this behavior, you need to first wrap it explicitly using `mindex_coords = xarray.Coordinates.from_pandas_multiindex(mindex_obj, 'dim')` and pass it as coordinates, e.g., `xarray.Dataset(coords=mindex_coords)`, `dataset.assign_coords(mindex_coords)` or `dataarray.assign_coords(mindex_coords)`.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Cache not found for keys: Linux-X64-py3.10-2025-03-02-d0b85fa4ec1d09fdcd5ac5333c6f51273aea95f41e3e23447c6064bf3bf0fc9f-linux-64-xarray-tests-args-e0a578e-root-dcc80ee-bin-[object Promise]-file-a5ee9cc42c678faaaba3f2d0130dbfc562349aaaacf8949b9af9cab3ef1cd070

Cache not found for keys: macOS-ARM64-py3.13-2025-03-02-d88b469f63f878053725f10a66978c2ee81a9b1cd6d183569791389f18c43440-osx-arm64-xarray-tests-args-a3edb49-root-873f6fe-bin-[object Promise]-file-33c9cc5a88c76e78b0fabe92743e9cb3e46dd8e3d40dab6d83e242e8d39519b8

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

The experimental Zarr V3 implementation in this version of Zarr-Python is not in alignment with the final V3 specification. This version will be removed in Zarr-Python 3 in favor of a spec compliant version.

The experimental Zarr V3 implementation in this version of Zarr-Python is not in alignment with the final V3 specification. This version will be removed in Zarr-Python 3 in favor of a spec compliant version.

Duplicate dimension names present: dimensions {'x'} appear more than once in dims=('x', 'x'). We do not yet support duplicate dimension names, but we do allow initial construction of the object. We recommend you rename the dims immediately to become distinct, as most xarray functionality is likely to fail silently if you do not. To rename the dimensions you will need to set the ``.dims`` attribute of each variable, ``e.g. var.dims=('x0', 'x1')``.

Duplicate dimension names present: dimensions {'x'} appear more than once in dims=('x', 'x'). We do not yet support duplicate dimension names, but we do allow initial construction of the object. We recommend you rename the dims immediately to become distinct, as most xarray functionality is likely to fail silently if you do not. To rename the dimensions you will need to set the ``.dims`` attribute of each variable, ``e.g. var.dims=('x0', 'x1')``.

The `numpy.astype` function is not implemented by Dask array. You may want to use the da.map_blocks function or something similar to silence this warning. Your code may stop working in a future release.

The `numpy.astype` function is not implemented by Dask array. You may want to use the da.map_blocks function or something similar to silence this warning. Your code may stop working in a future release.

deallocating CachingFileManager(<class 'h5netcdf.core.File'>, <fsspec.implementations.local.LocalFileOpener object at 0x7fbfa725dd20>, mode='r', kwargs={'invalid_netcdf': None, 'decode_vlen_strings': True, 'driver': None, 'phony_dims': 'access'}, manager_id='fa77f924-94c8-43d1-afe2-af48248c479d'), but file is not already closed. This may indicate a bug.

deallocating CachingFileManager(<class 'h5netcdf.core.File'>, <fsspec.implementations.local.LocalFileOpener object at 0x7fbfb057eda0>, mode='r', kwargs={'invalid_netcdf': None, 'decode_vlen_strings': True, 'driver': None, 'phony_dims': 'access'}, manager_id='31e0b505-3470-4d04-9045-be5613be05d5'), but file is not already closed. This may indicate a bug.

deallocating CachingFileManager(<class 'h5netcdf.core.File'>, <fsspec.implementations.local.LocalFileOpener object at 0x7fbfa725dd20>, mode='r', kwargs={'invalid_netcdf': None, 'decode_vlen_strings': True, 'driver': None, 'phony_dims': 'access'}, manager_id='fa77f924-94c8-43d1-afe2-af48248c479d'), but file is not already closed. This may indicate a bug.

deallocating CachingFileManager(<class 'h5netcdf.core.File'>, <fsspec.implementations.local.LocalFileOpener object at 0x7fbfb057eda0>, mode='r', kwargs={'invalid_netcdf': None, 'decode_vlen_strings': True, 'driver': None, 'phony_dims': 'access'}, manager_id='31e0b505-3470-4d04-9045-be5613be05d5'), but file is not already closed. This may indicate a bug.

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

The experimental Zarr V3 implementation in this version of Zarr-Python is not in alignment with the final V3 specification. This version will be removed in Zarr-Python 3 in favor of a spec compliant version.

The experimental Zarr V3 implementation in this version of Zarr-Python is not in alignment with the final V3 specification. This version will be removed in Zarr-Python 3 in favor of a spec compliant version.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Cache not found for keys: Linux-X64-py3.13-2025-03-02-c221d1a8acfc2436e37af6dc4a51ce46b7cd0d49c3905abb2b157ec14f7b956b-linux-64-xarray-tests-args-a3edb49-root-dcc80ee-bin-[object Promise]-file-ae1c30cc20ee9016e1f67897a09749a8e5b907d49d448d422645b591dc225b63

Cache not found for keys: Linux-X64-py3.10-2025-03-02-d88b469f63f878053725f10a66978c2ee81a9b1cd6d183569791389f18c43440-linux-64-xarray-tests-args-e0a578e-root-dcc80ee-bin-[object Promise]-file-33c9cc5a88c76e78b0fabe92743e9cb3e46dd8e3d40dab6d83e242e8d39519b8

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

The experimental Zarr V3 implementation in this version of Zarr-Python is not in alignment with the final V3 specification. This version will be removed in Zarr-Python 3 in favor of a spec compliant version.

The experimental Zarr V3 implementation in this version of Zarr-Python is not in alignment with the final V3 specification. This version will be removed in Zarr-Python 3 in favor of a spec compliant version.

Duplicate dimension names present: dimensions {'x'} appear more than once in dims=('x', 'x'). We do not yet support duplicate dimension names, but we do allow initial construction of the object. We recommend you rename the dims immediately to become distinct, as most xarray functionality is likely to fail silently if you do not. To rename the dimensions you will need to set the ``.dims`` attribute of each variable, ``e.g. var.dims=('x0', 'x1')``.

Duplicate dimension names present: dimensions {'x'} appear more than once in dims=('x', 'x'). We do not yet support duplicate dimension names, but we do allow initial construction of the object. We recommend you rename the dims immediately to become distinct, as most xarray functionality is likely to fail silently if you do not. To rename the dimensions you will need to set the ``.dims`` attribute of each variable, ``e.g. var.dims=('x0', 'x1')``.

The `numpy.astype` function is not implemented by Dask array. You may want to use the da.map_blocks function or something similar to silence this warning. Your code may stop working in a future release.

The `numpy.astype` function is not implemented by Dask array. You may want to use the da.map_blocks function or something similar to silence this warning. Your code may stop working in a future release.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Cache not found for keys: Linux-X64-py3.13-2025-03-02-d88b469f63f878053725f10a66978c2ee81a9b1cd6d183569791389f18c43440-linux-64-xarray-tests-args-a3edb49-root-dcc80ee-bin-[object Promise]-file-33c9cc5a88c76e78b0fabe92743e9cb3e46dd8e3d40dab6d83e242e8d39519b8

Failed to save: Failed to CreateCacheEntry: Received non-retryable error: Failed request: (409) Conflict: cache entry with the same key, version, and scope already exists

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

The experimental Zarr V3 implementation in this version of Zarr-Python is not in alignment with the final V3 specification. This version will be removed in Zarr-Python 3 in favor of a spec compliant version.

The experimental Zarr V3 implementation in this version of Zarr-Python is not in alignment with the final V3 specification. This version will be removed in Zarr-Python 3 in favor of a spec compliant version.

invalid value encountered in cast

invalid value encountered in cast

The `numpy.astype` function is not implemented by Dask array. You may want to use the da.map_blocks function or something similar to silence this warning. Your code may stop working in a future release.

The `numpy.astype` function is not implemented by Dask array. You may want to use the da.map_blocks function or something similar to silence this warning. Your code may stop working in a future release.

Cache not found for keys: Windows-X64-py3.10-2025-03-02-e8c295d54ec7b33e028c4ef3f5de6c8bc064026f845f027aaa789c9f1a176051-win-64-xarray-tests-args-e0a578e-root-74fbf63-bin-[object Promise]-file-8a847870d9eabe6a5889e8cc4751f87f1f26356326da5ac29cd93c8b170ed715

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.

The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.

The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.

The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.

The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.

The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

Duplicate dimension names present: dimensions {'x'} appear more than once in dims=('x', 'x'). We do not yet support duplicate dimension names, but we do allow initial construction of the object. We recommend you rename the dims immediately to become distinct, as most xarray functionality is likely to fail silently if you do not. To rename the dimensions you will need to set the ``.dims`` attribute of each variable, ``e.g. var.dims=('x0', 'x1')``.

Duplicate dimension names present: dimensions {'x'} appear more than once in dims=('x', 'x'). We do not yet support duplicate dimension names, but we do allow initial construction of the object. We recommend you rename the dims immediately to become distinct, as most xarray functionality is likely to fail silently if you do not. To rename the dimensions you will need to set the ``.dims`` attribute of each variable, ``e.g. var.dims=('x0', 'x1')``.

The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.

The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.

The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.

The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.

Cache not found for keys: Windows-X64-py3.13-2025-03-02-e8c295d54ec7b33e028c4ef3f5de6c8bc064026f845f027aaa789c9f1a176051-win-64-xarray-tests-args-a3edb49-root-74fbf63-bin-[object Promise]-file-8a847870d9eabe6a5889e8cc4751f87f1f26356326da5ac29cd93c8b170ed715

Cache not found for keys: Linux-X64-py3.10-2025-03-02-c909689293cb6019c4cc2757fa3a775c553017216200ee20ff6e244192ec7041-linux-64-xarray-tests-args-e0a578e-root-dcc80ee-bin-[object Promise]-file-f4bf6040f0c0b5d4a664d923d807676a5362efe13a9c39507a9fa06a933345ec

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

NumPy will stop allowing conversion of out-of-bound Python integers to integer arrays. The conversion of 255 to int8 will fail in the future. For the old behavior, usually: np.array(value).astype(dtype)` will give the desired result (the cast overflows).

NumPy will stop allowing conversion of out-of-bound Python integers to integer arrays. The conversion of 255 to int8 will fail in the future. For the old behavior, usually: np.array(value).astype(dtype)` will give the desired result (the cast overflows).

NumPy will stop allowing conversion of out-of-bound Python integers to integer arrays. The conversion of 255 to int8 will fail in the future. For the old behavior, usually: np.array(value).astype(dtype)` will give the desired result (the cast overflows).

NumPy will stop allowing conversion of out-of-bound Python integers to integer arrays. The conversion of 255 to int8 will fail in the future. For the old behavior, usually: np.array(value).astype(dtype)` will give the desired result (the cast overflows).

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

invalid value encountered in cast

NumPy will stop allowing conversion of out-of-bound Python integers to integer arrays. The conversion of 255 to int8 will fail in the future. For the old behavior, usually: np.array(value).astype(dtype)` will give the desired result (the cast overflows).

NumPy will stop allowing conversion of out-of-bound Python integers to integer arrays. The conversion of 255 to int8 will fail in the future. For the old behavior, usually: np.array(value).astype(dtype)` will give the desired result (the cast overflows).

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artifacts/Test results for Linux-3.10 min-all-deps/pytest.xml [took 0s] artifacts/Test results for Linux-3.10/pytest.xml [took 0s] artifacts/Test results for Linux-3.13 all-but-numba/pytest.xml [took 0s] artifacts/Test results for Linux-3.13/pytest.xml [took 0s] artifacts/Test results for Windows-3.10/pytest.xml [took 0s] artifacts/Test results for Windows-3.13/pytest.xml [took 0s] artifacts/Test results for macOS-3.10/pytest.xml [took 0s] artifacts/Test results for macOS-3.13/pytest.xml [took 0s]

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