html_url,issue_url,id,node_id,user,user_label,created_at,updated_at,author_association,body,reactions,issue,issue_label,performed_via_github_app
https://github.com/simonw/datasette/issues/371#issuecomment-435767775,https://api.github.com/repos/simonw/datasette/issues/371,435767775,MDEyOklzc3VlQ29tbWVudDQzNTc2Nzc3NQ==,9599,simonw,2018-11-05T06:27:33Z,2018-11-05T06:27:33Z,OWNER,"This would be fantastic - that tutorial looks like many of the details needed for this.
Do you know if Digital Ocean have the ability to provision URLs for a droplet without you needing to buy your own domain name? Heroku have https://example.herokuapp.com/ and Zeit have https://blah.now.sh/ - does Digital Ocean have an equivalent?
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",377156339,datasette publish digitalocean plugin,
https://github.com/simonw/datasette/issues/369#issuecomment-435767827,https://api.github.com/repos/simonw/datasette/issues/369,435767827,MDEyOklzc3VlQ29tbWVudDQzNTc2NzgyNw==,9599,simonw,2018-11-05T06:27:55Z,2018-11-05T06:28:48Z,OWNER,"This is a good idea. Basically a version of this bug but on the custom SQL query page:
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",374953006,Interface should show same JSON shape options for custom SQL queries,
https://github.com/simonw/datasette/issues/329#issuecomment-435772031,https://api.github.com/repos/simonw/datasette/issues/329,435772031,MDEyOklzc3VlQ29tbWVudDQzNTc3MjAzMQ==,9599,simonw,2018-11-05T06:53:28Z,2018-11-05T06:54:10Z,OWNER,"This works now! The `0.25.1` release was the first release which successfully pushed to Docker Hub: https://hub.docker.com/r/datasetteproject/datasette/tags/
Here's the log from the successful Travis release job: https://travis-ci.org/simonw/datasette/jobs/450714602
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",336465018,Travis should push tagged images to Docker Hub for each release,
https://github.com/simonw/datasette/issues/370#issuecomment-435974786,https://api.github.com/repos/simonw/datasette/issues/370,435974786,MDEyOklzc3VlQ29tbWVudDQzNTk3NDc4Ng==,9599,simonw,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}",377155320,Integration with JupyterLab,
https://github.com/simonw/datasette/issues/374#issuecomment-435976262,https://api.github.com/repos/simonw/datasette/issues/374,435976262,MDEyOklzc3VlQ29tbWVudDQzNTk3NjI2Mg==,9599,simonw,2018-11-05T18:11:10Z,2018-11-05T18:11:10Z,OWNER,"I think there is a useful way forward here though: the image size may be limited to 100MB, but once the instance launches it gets access to a filesystem with a lot more space than that (possibly as much as 15GB given my initial poking around).
So... one potential solution here is to teach Datasette to launch from a smaller image and then download a larger SQLite file from a known URL as part of its initial startup.
Combined with the ability to get Now to always run at least one copy of an instance this could allow Datasette to host much larger SQLite databases on that platform while playing nicely with the Zeit v2 platform.
See also https://github.com/zeit/now-cli/issues/1523","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",377518499,Get Datasette working with Zeit Now v2's 100MB image size limit,
https://github.com/simonw/datasette/issues/371#issuecomment-435862009,https://api.github.com/repos/simonw/datasette/issues/371,435862009,MDEyOklzc3VlQ29tbWVudDQzNTg2MjAwOQ==,82988,psychemedia,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}",377156339,datasette publish digitalocean plugin,
https://github.com/simonw/datasette/issues/370#issuecomment-436037692,https://api.github.com/repos/simonw/datasette/issues/370,436037692,MDEyOklzc3VlQ29tbWVudDQzNjAzNzY5Mg==,82988,psychemedia,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}",377155320,Integration with JupyterLab,
https://github.com/simonw/datasette/issues/370#issuecomment-436042445,https://api.github.com/repos/simonw/datasette/issues/370,436042445,MDEyOklzc3VlQ29tbWVudDQzNjA0MjQ0NQ==,82988,psychemedia,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}",377155320,Integration with JupyterLab,
https://github.com/simonw/datasette/issues/369#issuecomment-435768450,https://api.github.com/repos/simonw/datasette/issues/369,435768450,MDEyOklzc3VlQ29tbWVudDQzNTc2ODQ1MA==,416374,gfrmin,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}",374953006,Interface should show same JSON shape options for custom SQL queries,