issue_comments

Table actions

3 rows where issue = 327166000 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

user 3

author_association 2

issue 1

  • WIP: explicit indexes · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1074000622 https://github.com/pydata/xarray/pull/2195#issuecomment-1074000622 https://api.github.com/repos/pydata/xarray/issues/2195 IC_kwDOAMm_X85AA_Lu benbovy 4160723 2022-03-21T14:55:18Z 2022-03-21T14:55:18Z MEMBER

I guess we can close this one now that #5692 is merged?

 
{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   WIP: explicit indexes 327166000
442554179 https://github.com/pydata/xarray/pull/2195#issuecomment-442554179 https://api.github.com/repos/pydata/xarray/issues/2195 MDEyOklzc3VlQ29tbWVudDQ0MjU1NDE3OQ== shoyer 1217238 2018-11-28T18:28:50Z 2018-11-28T18:29:58Z MEMBER

I've pushed a few commits with some additional progress here. Here's my current plan:

  1. Automatically create new variables for MultiIndex levels, and store these in Dataset._variables / DataArray._coords. This lets us use the normal variable consistency checks and indexing operations, rather than requiring explicit checks like assert_unique_multiindex_level_names or "virtual variables". This is mostly complete (still under-tested) as of the last commit, but it should be a big win for consistency when using a MultiIndex since the level variables will be built into xarray's data model. The MultiIndex itself will still be an xarray variable (an object array of tuples).
  2. Add explicit indexes, as a map from coordinate names to a pandas.Index or pandas.MultiIndex used for indexing. Note that if a MultiIndex is used, coordinates corresponding to levels will all point to the same MultiIndex, e.g., if MultiIndex foo has levels x and y, indexes will look like {'foo': foo, 'x': foo, 'y': foo}.
  3. Remove/fixup code that assumes that only dimension names are used for indexes. Instead, we look for indexes by looking up coordinate names in .indexes.
  4. Add an xarray specific Index API so we can add our own index classes, e.g., a KDTree. This will happen in a later PR.
 
{
    "total_count": 1,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 1,
    "rocket": 0,
    "eyes": 0
}
   WIP: explicit indexes 327166000
442315949 https://github.com/pydata/xarray/pull/2195#issuecomment-442315949 https://api.github.com/repos/pydata/xarray/issues/2195 MDEyOklzc3VlQ29tbWVudDQ0MjMxNTk0OQ== pep8speaks 24736507 2018-11-28T04:30:29Z 2018-11-28T04:30:29Z NONE

Hello @shoyer! Thanks for updating the PR.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   WIP: explicit indexes 327166000

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]);