issues: 1410575877

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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
1410575877 PR_kwDOAMm_X85A4LHp 7172 Lazy import dask.distributed to reduce import time of xarray 90008 closed 0     9 2022-10-16T18:25:31Z 2022-10-18T17:41:50Z 2022-10-18T17:06:34Z CONTRIBUTOR   0 pydata/xarray/pulls/7172

I was auditing the import time of my software and found that distributed added a non insignificant amount of time to the import of xarray:

Using tuna, one can find that the following are sources of delay in import time for xarray:

To audit, one can use the the command python -X importtime -c "import numpy as np; import pandas as pd; import dask.array; import xarray as xr" 2>import.log && tuna import.lo The command as is, breaks out the import time of numpy, pandas, and dask.array to allow you to focus on "other" costs within xarray. Main branch:

Proposed:

One would be tempted to think that this is due to xarray.testing and xarray.tutorial but those just move the imports one level down in tuna graphs.

  • [x] ~~Closes~~
  • [x] ~~Tests added~~
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [x] ~~New functions/methods are listed in api.rst~~
 
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