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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
34089909 MDExOlB1bGxSZXF1ZXN0MzQwODk5MDk= 401 closed 0 Handle bool in NetCDF4 conversion khaeru 1634164 I am working on some code that creates `xray.Datasets` with a 'bool' dtype. Trying to call `Dataset.to_netcdf()` on this code causes `_nc4_values_and_dtype()` to raise a `ValueError`, so I added these few lines to force the storage of these variables as 1-byte integers. Perhaps it should be 'u1' instead; I can change that if need be. 2015-04-24T21:59:08Z 2016-05-26T18:51:06Z 2016-05-23T04:54:40Z   cc75c65217f679729f2af01bacc16d56beb00061     0 60c43e076d06ab2eb0ceea44b20bd11488c8e9f2 eed58d5cb4274f262e77277bc8fcf394a9fae77c FIRST_TIME_CONTRIBUTOR   xarray 13221727 https://github.com/pydata/xarray/pull/401  
408964137 MDExOlB1bGxSZXF1ZXN0NDA4OTY0MTM3 4007 open 0 Allow DataArray.to_series() without invoking sparse.COO.todense() khaeru 1634164 This adds some code (from iiasa/ixmp#317) that allows DataArray.to_series() to be called without invoking sparse.COO.todense() when that is the backing data type. I'm aware this needs some improvement to meet the standard of the existing codebase, so I hope I could ask for some guidance on how to address the following points (including whom to ask about them): - [ ] Make the same improvement in {DataArray,Dataset}.to_dataframe(). - [ ] Possibly move the code out of dataarray.py to a more appropriate location (where?). - [ ] Possibly check for sparse.COO explicitly instead of xarray.core.pycompat.sparse_array_type. Other SparseArray subclasses, e.g. DOK, may not have the same attributes. Standard items: - [ ] Tests added. - [x] Passes `isort -rc . && black . && mypy . && flake8` (Sort of: these wanted to modify 7 files beyond the one I touched; didn't commit these changes.) - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API. 2020-04-25T20:15:16Z 2022-06-09T14:50:17Z     97367f000d06c906a778dfd2868cda39d937e87d     0 b5581fcd49264992acf53e05ea17957f7f2be61b d1e4164f3961d7bbb3eb79037e96cae14f7182f8 FIRST_TIME_CONTRIBUTOR   xarray 13221727 https://github.com/pydata/xarray/pull/4007  

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CREATE TABLE [pull_requests] (
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [state] TEXT,
   [locked] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [body] TEXT,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [merged_at] TEXT,
   [merge_commit_sha] TEXT,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [draft] INTEGER,
   [head] TEXT,
   [base] TEXT,
   [author_association] TEXT,
   [auto_merge] TEXT,
   [repo] INTEGER REFERENCES [repos]([id]),
   [url] TEXT,
   [merged_by] INTEGER REFERENCES [users]([id])
);
CREATE INDEX [idx_pull_requests_merged_by]
    ON [pull_requests] ([merged_by]);
CREATE INDEX [idx_pull_requests_repo]
    ON [pull_requests] ([repo]);
CREATE INDEX [idx_pull_requests_milestone]
    ON [pull_requests] ([milestone]);
CREATE INDEX [idx_pull_requests_assignee]
    ON [pull_requests] ([assignee]);
CREATE INDEX [idx_pull_requests_user]
    ON [pull_requests] ([user]);