issues: 776595030

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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
776595030 MDExOlB1bGxSZXF1ZXN0NTQ3MDUzOTM5 4744 Speed up Dataset._construct_dataarray 2448579 closed 0     1 2020-12-30T19:03:05Z 2021-01-05T17:32:16Z 2021-01-05T17:32:13Z MEMBER   0 pydata/xarray/pulls/4744
  • [ ] 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) ```

 
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