pull_requests: 547053939

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id node_id number state locked title user body created_at updated_at closed_at merged_at merge_commit_sha assignee milestone draft head base author_association auto_merge repo url merged_by
547053939 MDExOlB1bGxSZXF1ZXN0NTQ3MDUzOTM5 4744 closed 0 Speed up Dataset._construct_dataarray 2448579 <!-- Feel free to remove check-list items aren't relevant to your change --> - [ ] Tests added - [x] Passes `isort . && black . && mypy . && flake8` - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` Significantly speeds up `_construct_dataarray` by iterating over `._coord_names` instead of `.coords`. This avoids unnecessarily constructing a `DatasetCoordinates` object and massively speeds up repr construction for datasets with large numbers of variables. Construct a 2000 variable dataset ```python import numpy as np import xarray as xr a = np.arange(0, 2000) b = np.core.defchararray.add("long_variable_name", a.astype(str)) coords = dict(time=np.array([0, 1])) data_vars = dict() for v in b: data_vars[v] = xr.DataArray( name=v, data=np.array([3, 4]), dims=["time"], coords=coords ) ds0 = xr.Dataset(data_vars) ``` Before: ``` %timeit ds0['long_variable_name1999'] %timeit ds0.__repr__() 1.33 ms ± 23 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) 2.66 s ± 52.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) ``` After: ``` %timeit ds0['long_variable_name1999'] %timeit ds0.__repr__() 10.5 µs ± 203 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) 84.2 ms ± 1.28 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) ``` 2020-12-30T19:03:05Z 2021-01-05T17:32:16Z 2021-01-05T17:32:13Z 2021-01-05T17:32:13Z 9fefefbb564ec7a90f4f99d89352463ab81125fb     0 fb48be973350c66c2bd1e48b3f8df8d9faad0524 bf0fe2caca1d2ebc4f1298f019758baa12f68b94 MEMBER   13221727 https://github.com/pydata/xarray/pull/4744  

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