issue_comments

Table actions

4 rows where issue = 377155320 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

author_association 2

issue 1

  • Integration with JupyterLab · 4 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions issue performed_via_github_app
1261930179 https://github.com/simonw/datasette/issues/370#issuecomment-1261930179 https://api.github.com/repos/simonw/datasette/issues/370 IC_kwDOBm6k_c5LN4bD MichaelTiemannOSC 72577720 2022-09-29T08:17:46Z 2022-09-29T08:17:46Z CONTRIBUTOR

Just watched this video which demonstrates the integration of any webapp into JupyterLab: https://youtu.be/FH1dKKmvFtc

Maybe this is the answer?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Integration with JupyterLab 377155320  
436042445 https://github.com/simonw/datasette/issues/370#issuecomment-436042445 https://api.github.com/repos/simonw/datasette/issues/370 MDEyOklzc3VlQ29tbWVudDQzNjA0MjQ0NQ== psychemedia 82988 2018-11-05T21:30:42Z 2018-11-05T21:31:48Z CONTRIBUTOR

Another route would be something like creating a datasette IPython magic for notebooks to take a dataframe and easily render it as a datasette. You'd need to run the app in the background rather than block execution in the notebook. Related to that, or to publishing a dataframe in notebook cell for use in other cells in a non-blocking way, there may be cribs in something like https://github.com/micahscopes/nbmultitask .

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Integration with JupyterLab 377155320  
436037692 https://github.com/simonw/datasette/issues/370#issuecomment-436037692 https://api.github.com/repos/simonw/datasette/issues/370 MDEyOklzc3VlQ29tbWVudDQzNjAzNzY5Mg== psychemedia 82988 2018-11-05T21:15:47Z 2018-11-05T21:18:37Z CONTRIBUTOR

In terms of integration with pandas, I was pondering two different ways datasette/csvs_to_sqlite integration may work:

  • like pandasql, to provide a SQL query layer either by a direct connection to the sqlite db or via datasette API;
  • as an improvement of pandas.to_sql(), which is a bit ropey (e.g. pandas.to_sql_from_csvs(), routing the dataframe to sqlite via csvs_tosqlite rather than the dodgy mapping that pandas supports).

The pandas.publish_* idea could be quite interesting though... Would it be useful/fruitful to think about publish_ as a complement to pandas.to_?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Integration with JupyterLab 377155320  
435974786 https://github.com/simonw/datasette/issues/370#issuecomment-435974786 https://api.github.com/repos/simonw/datasette/issues/370 MDEyOklzc3VlQ29tbWVudDQzNTk3NDc4Ng== simonw 9599 2018-11-05T18:06:56Z 2018-11-05T18:06:56Z OWNER

I've been thinking a bit about ways of using Jupyter Notebook more effectively with Datasette (thinks like a publish_dataframes(df1, df2, df3) function which publishes some Pandas dataframes and returns you a URL to a new hosted Datasette instance) but you're right, Jupyter Lab is potentially a much more interesting fit.

 
{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Integration with JupyterLab 377155320  

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,
   [issue] INTEGER REFERENCES [issues]([id])
, [performed_via_github_app] TEXT);
CREATE INDEX [idx_issue_comments_issue]
                ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
                ON [issue_comments] ([user]);