id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,pull_request,body,repo,type,active_lock_reason,performed_via_github_app,reactions,draft,state_reason
336924199,MDU6SXNzdWUzMzY5MjQxOTk=,330,Limit text display in cells containing large amounts of text,82988,closed,0,,,4,2018-06-29T09:15:22Z,2018-07-24T04:53:20Z,2018-07-10T16:20:48Z,CONTRIBUTOR,,"The default preview of a database shows all columns (is the row count limited?) which is fine in many cases but can take a long time to load / offer a large overhead if the table is a SpatiaLite table containing geometry columns that include large shapefiles.

Would it make sense to have a setting that can limit the amount of text displayed in any given cell in the table preview, or (less useful?) suppress (with notification) the display of overlong columns unless enabled by the user?

An issue then arises if a user does want to see all the text in a cell:

  1) for a particular cell;
  2) for every cell in the table;
  3) for all cells in a particular column or columns

(I haven't checked but what if a column contains e.g. raw image data? Does this display as raw data? Or can this be rendered in a context aware way as an image preview? I guess a custom template would be one way to do that?)",107914493,issue,,,"{""url"": ""https://api.github.com/repos/simonw/datasette/issues/330/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed
377155320,MDU6SXNzdWUzNzcxNTUzMjA=,370,Integration with JupyterLab,82988,open,0,,,4,2018-11-04T13:57:13Z,2022-09-29T08:17:47Z,,CONTRIBUTOR,,"I just watched a demo video for the [JupyterLab Chart Editor](https://www.crowdcast.io/e/introducing-JupyterLab-Chart-Editor/) which wraps the plotly chart editor app in a JupyterLab panel and lets you open a plotly chart JSON file in that editor.  Essentially, it pops an HTML app into a panel in JupyterLab, and I think registers the app as a file viewer for a particular file type. (I'm not completely taken by it, tbh, because it means you can do irreproducible things to the chart definition file, but that's another issue).

JupyterLab extensions can also open files from a dialogue as the iframe/html previewer shows: https://github.com/timkpaine/jupyterlab_iframe.

This made me wonder about what `datasette` integration with JupyterLab might do.

For example, by right-clicking on a CSV file (for which there is already a CSV table view) in the file browser, offer a *View / Run as datasette* file viewer option that will:

- run the CSV file through `csvs-to-sqlite`;
- launch the `datasette` server and display the `datasette` view in a JupyterLab panel.

(? Create a new SQLite db for each CSV file and launch each datasette view on a new port? Or have a JupyterLab (session?) SQLite db that stores all `datasette` viewed CSVs and runs on a single port?) 

As a freebie, the `datasette` API would allow you to run efficient SQL queries against the file eg using using `pandas.read_sql()` queries in a notebook in the same space.

Related:

- [JupyterLab extensions docs](https://jupyterlab.readthedocs.io/en/stable/user/extensions.html)
-  a [cookiecutter for wrting JupyterLab extensions using Javascript](https://github.com/jupyterlab/extension-cookiecutter-js)
- a [cookiecutter for writing JupyterLab extensions using Typescript](https://github.com/jupyterlab/extension-cookiecutter-ts)
- tutorial: [Let’s Make an xkcd JupyterLab Extension](https://jupyterlab.readthedocs.io/en/stable/developer/xkcd_extension_tutorial.html)",107914493,issue,,,"{""url"": ""https://api.github.com/repos/simonw/datasette/issues/370/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,
729017519,MDExOlB1bGxSZXF1ZXN0NTA5NTkwMjA1,1049,Add template block prior to extra URL loaders,82988,closed,0,,,4,2020-10-25T13:08:55Z,2020-10-29T09:20:52Z,2020-10-29T09:20:34Z,CONTRIBUTOR,simonw/datasette/pulls/1049,"To handle packages that require Javascript state setting prior to loading a package (eg [`thebelab`](https://thebelab.readthedocs.io/en/latest/examples/minimal_example.html), provide a template block before the URLs are loaded.",107914493,pull,,,"{""url"": ""https://api.github.com/repos/simonw/datasette/issues/1049/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",0,
1063388037,I_kwDOCGYnMM4_YgOF,343,Provide function to generate hash_id from specified columns,82988,closed,0,,,4,2021-11-25T10:12:12Z,2022-03-02T04:25:25Z,2022-03-02T04:25:25Z,NONE,,"Hi

I note that you define `_hash()` to create a `hash_id` from non-id column values in a table [here](https://github.com/simonw/sqlite-utils/blob/8f386a0d300d1b1c76132bb75972b755049fb742/sqlite_utils/db.py#L2996).

It would be useful to be able to call a complementary function to generate a corresponding `_id` from a subset of specified columns when adding items to another table, eg to support the creation of foreign keys.

Or is there a better pattern for doing that?",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/343/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed