issue_comments

Table actions

5 rows where author_association = "MEMBER" and issue = 527296094 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

issue 1

  • environment file for binderized examples · 5 ✖

author_association 1

  • MEMBER · 5 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
557978117 https://github.com/pydata/xarray/issues/3563#issuecomment-557978117 https://api.github.com/repos/pydata/xarray/issues/3563 MDEyOklzc3VlQ29tbWVudDU1Nzk3ODExNw== jhamman 2443309 2019-11-25T04:05:31Z 2019-11-25T04:05:31Z MEMBER

See https://github.com/pydata/xarray/pull/3568 for a basic environment that should do the trick. Going forward, I think it would be nice to split these out into a separate repo. Let's save that for https://github.com/pydata/xarray/issues/2378.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   environment file for binderized examples 527296094
557945408 https://github.com/pydata/xarray/issues/3563#issuecomment-557945408 https://api.github.com/repos/pydata/xarray/issues/3563 MDEyOklzc3VlQ29tbWVudDU1Nzk0NTQwOA== dcherian 2448579 2019-11-25T00:22:55Z 2019-11-25T00:22:55Z MEMBER

Thanks all. Now we just need some one to volunteer to do this :)

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   environment file for binderized examples 527296094
557615479 https://github.com/pydata/xarray/issues/3563#issuecomment-557615479 https://api.github.com/repos/pydata/xarray/issues/3563 MDEyOklzc3VlQ29tbWVudDU1NzYxNTQ3OQ== mrocklin 306380 2019-11-22T17:12:07Z 2019-11-22T17:12:07Z MEMBER

You're probably already aware, but https://examples.dask.org and https://github.com/dask/dask-examples might be a nice model to look at. 

{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   environment file for binderized examples 527296094
557613920 https://github.com/pydata/xarray/issues/3563#issuecomment-557613920 https://api.github.com/repos/pydata/xarray/issues/3563 MDEyOklzc3VlQ29tbWVudDU1NzYxMzkyMA== max-sixty 5635139 2019-11-22T17:07:45Z 2019-11-22T17:07:45Z MEMBER

Not in reference to this exact issue, but the binder functionality is really awesome! Well done!

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   environment file for binderized examples 527296094
557610023 https://github.com/pydata/xarray/issues/3563#issuecomment-557610023 https://api.github.com/repos/pydata/xarray/issues/3563 MDEyOklzc3VlQ29tbWVudDU1NzYxMDAyMw== scottyhq 3924836 2019-11-22T16:56:42Z 2019-11-22T16:56:42Z MEMBER

Awesome @dcherian ! I like the approach of defining a binder environment then pulling the examples directory into the binder session with nbgitpuller. There are options for where to store the binder environment config (1) master branch .binder, 2) a new branch called 'binder', or 3) even a separate repo... maybe pydata/xarray-binder-env - see https://github.com/scottyhq/repo2docker-githubci ?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   environment file for binderized examples 527296094

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]);