issues: 252547273
This data as json
| 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 252547273 | MDU6SXNzdWUyNTI1NDcyNzM= | 1523 | Pass arguments to dask.compute() | 6213168 | closed | 0 | 5 | 2017-08-24T09:48:14Z | 2017-09-05T19:55:46Z | 2017-09-05T19:55:46Z | MEMBER | I work with a very large dask-based algorithm in xarray, and I do my optimization by hand before hitting compute(). In other cases, I need using multiple dask schedulers at once (e.g. a multithreaded one for numpy-based work and a multiprocessing one for pure python work). This change proposal (which I'm happy to do) is about accepting *args, **kwds parameters in all .compute(), .load(), and .persist() xarray methods and pass them verbatim to the underlying dask compute() and persist() functions. |
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completed | 13221727 | issue |