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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
38719512 MDExOlB1bGxSZXF1ZXN0Mzg3MTk1MTI= 446 closed 0 Preprocess argument for open_mfdataset and threading lock shoyer 1217238 Fixes #443 Fixes #444 2015-06-28T03:33:19Z 2015-07-02T17:16:41Z 2015-06-29T18:06:54Z 2015-06-29T18:06:54Z cd861e1ba8d6a9c269bf946a232936199b90463b   0.5.2 1172685 0 0816424dcc65c4aa191478c22b9ac41a6eb2a1f3 fedd28b75ed83a73132c13d462a47b0afea76d06 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/446  
39042887 MDExOlB1bGxSZXF1ZXN0MzkwNDI4ODc= 450 closed 0 Add xray.save_mfdataset shoyer 1217238 This function allows for saving multiple datasets to disk simultaneously, which is useful when processing large datasets with dask.array. For example, to save a dataset too big to fit into memory to one file per year, we could write: ``` >>> years, datasets = zip(*ds.groupby('time.year')) >>> paths = ['%s.nc' % y for y in years] >>> xray.save_mfdataset(datasets, paths) ``` 2015-07-02T02:19:41Z 2015-07-06T18:41:27Z 2015-07-06T18:41:25Z 2015-07-06T18:41:25Z 2fe280c4214f5b93e233c2e6b0230e243cd02835   0.5.2 1172685 0 699ca84cdf0ebbc774b4f129994bea3684f0902d 613b285ea72023d8c2ce950ac4020f30e17b692b MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/450  
39227908 MDExOlB1bGxSZXF1ZXN0MzkyMjc5MDg= 454 closed 0 Fixed bug in serializing datetime scalars shoyer 1217238   2015-07-05T22:18:07Z 2015-07-06T04:56:53Z 2015-07-06T04:56:52Z 2015-07-06T04:56:52Z c3267eb690e3f0de8164fbf2a2880e1c3fb97cde   0.5.2 1172685 0 1876e7f7381c8d89bb6c5be5abd04c11c442dfe3 ffa8e692d72935579752903925936c8da00deab0 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/454  
39227912 MDExOlB1bGxSZXF1ZXN0MzkyMjc5MTI= 455 closed 0 Fix min/max for arrays with string or unicode types shoyer 1217238 Fixes #453 2015-07-05T22:18:31Z 2015-07-06T04:56:22Z 2015-07-06T04:56:20Z 2015-07-06T04:56:20Z e6b17b95ade26c461ec09f551e2ccfb6e6e75496   0.5.2 1172685 0 39c1f5e07d29ce70528e89db09a9a919631bd0c0 ffa8e692d72935579752903925936c8da00deab0 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/455  
39948630 MDExOlB1bGxSZXF1ZXN0Mzk5NDg2MzA= 472 closed 0 Add support for reading/writing complex numbers with h5netcdf shoyer 1217238   2015-07-14T18:48:03Z 2015-07-14T20:24:06Z 2015-07-14T20:24:04Z 2015-07-14T20:24:04Z 174dcef8876eae0b635a1e12e1a1d180ecd62e5d   0.5.2 1172685 0 05296c0a5a13b8c5e6e0eb7b127d1d6d78291ba6 470242120aab3fa51180e70c38fe5865a42c144e MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/472  
39983076 MDExOlB1bGxSZXF1ZXN0Mzk5ODMwNzY= 473 closed 0 Rewrite of xray.concat shoyer 1217238 Fixes #464 Fixes #438 The optional arguments `concat_over` and `mode` in `xray.concat` have been removed and replaced by `data_vars` and `coords`. The new arguments are both more easily understood and more robustly implemented. 2015-07-15T02:33:39Z 2015-07-15T21:47:14Z 2015-07-15T21:47:11Z 2015-07-15T21:47:11Z 2ef9cbe6e9c0c462142a6aa302ce44d0ce899f99   0.5.2 1172685 0 e6f6cbd756e57d251de8ffb90853b85f82c540f4 0e77e5a86ffa2355f986ef165b5b6970411d5ef6 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/473  
40078364 MDExOlB1bGxSZXF1ZXN0NDAwNzgzNjQ= 477 closed 0 Bytes attributes are decoded to strings with engine='h5netcdf' shoyer 1217238 Fixes #451 2015-07-15T22:49:03Z 2015-07-16T18:11:42Z 2015-07-16T18:11:42Z 2015-07-16T18:11:42Z e3ede44de51342e3678c000843a89eea508f10d1   0.5.2 1172685 0 71c30f71c7e8cedbbfa9a384130f3220b9bbe9ee 7c9a2fe27794a9761319daa4dc90a7e4e19c795e MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/477  
40177264 MDExOlB1bGxSZXF1ZXN0NDAxNzcyNjQ= 478 closed 0 Xray v0.5.2 updates shoyer 1217238 Fixes #444 2015-07-16T21:19:14Z 2015-07-16T21:40:23Z 2015-07-16T21:40:22Z 2015-07-16T21:40:22Z 5a5255e43c6c79827ead12abee2dc813bc956307   0.5.2 1172685 0 06941b00e763c773c112543d1d8b3fb4bbbd559f 222cff8a4e742cef1d9ff103c99e15855a1bc7c4 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/478  

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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]);