issue_comments

Table actions

3 rows where issue = 482543307 and user = 3019665 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: reactions, created_at (date), updated_at (date)

user 1

  • jakirkham · 3 ✖

issue 1

  • Use pytorch as backend for xarrays · 3 ✖

author_association 1

id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1190589331 https://github.com/pydata/xarray/issues/3232#issuecomment-1190589331 https://api.github.com/repos/pydata/xarray/issues/3232 IC_kwDOAMm_X85G9vOT jakirkham 3019665 2022-07-20T18:01:56Z 2022-07-20T18:01:56Z NONE

While it is true to use PyTorch Tensors directly, one would need the Array API implemented in PyTorch. One could use them indirectly by converting them zero-copy to CuPy arrays, which do have Array API support

 
{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Use pytorch as backend for xarrays 482543307
606354369 https://github.com/pydata/xarray/issues/3232#issuecomment-606354369 https://api.github.com/repos/pydata/xarray/issues/3232 MDEyOklzc3VlQ29tbWVudDYwNjM1NDM2OQ== jakirkham 3019665 2020-03-31T02:07:47Z 2020-03-31T02:07:47Z NONE

Well here's a blogpost on using Dask + CuPy. Maybe start there and build up to using Xarray.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Use pytorch as backend for xarrays 482543307
606262540 https://github.com/pydata/xarray/issues/3232#issuecomment-606262540 https://api.github.com/repos/pydata/xarray/issues/3232 MDEyOklzc3VlQ29tbWVudDYwNjI2MjU0MA== jakirkham 3019665 2020-03-30T21:31:18Z 2020-03-30T21:31:18Z NONE

Yeah Jacob and I played with this a few months back. There were some issues, but my recollection is pretty hazy. If someone gives this another try, it would be interesting to hear how things go.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Use pytorch as backend for xarrays 482543307

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

CREATE TABLE [issue_comments] (
   [html_url] TEXT,
   [issue_url] TEXT,
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [created_at] TEXT,
   [updated_at] TEXT,
   [author_association] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [issue] INTEGER REFERENCES [issues]([id])
);
CREATE INDEX [idx_issue_comments_issue]
    ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
    ON [issue_comments] ([user]);