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4 rows where author_association = "CONTRIBUTOR" and "created_at" is on date 2018-11-05 sorted by html_url
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id | html_url ▼ | issue_url | node_id | user | created_at | updated_at | author_association | body | reactions | issue | performed_via_github_app |
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435768450 | https://github.com/simonw/datasette/issues/369#issuecomment-435768450 | https://api.github.com/repos/simonw/datasette/issues/369 | MDEyOklzc3VlQ29tbWVudDQzNTc2ODQ1MA== | gfrmin 416374 | 2018-11-05T06:31:59Z | 2018-11-05T06:31:59Z | CONTRIBUTOR | That would be ideal, but you know better than me whether the CSV streaming trick works for custom SQL queries. | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | Interface should show same JSON shape options for custom SQL queries 374953006 | |
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`](https://github.com/yhat/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_`](https://pandas.pydata.org/pandas-docs/stable/api.html#id12)? | {"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 | |
435862009 | https://github.com/simonw/datasette/issues/371#issuecomment-435862009 | https://api.github.com/repos/simonw/datasette/issues/371 | MDEyOklzc3VlQ29tbWVudDQzNTg2MjAwOQ== | psychemedia 82988 | 2018-11-05T12:48:35Z | 2018-11-05T12:48:35Z | CONTRIBUTOR | I think you need to register a domain name you own separately in order to get a non-IP address address? https://www.digitalocean.com/docs/networking/dns/ | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | datasette publish digitalocean plugin 377156339 |
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created_at (date) 1 ✖