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
351845423,MDU6SXNzdWUzNTE4NDU0MjM=,3,Experiment with contentless FTS tables,9599,closed,0,,,1,2018-08-18T19:31:01Z,2019-07-22T20:58:55Z,2019-07-22T20:58:55Z,OWNER,,Could greatly reduce size of resulting database for large datasets: http://cocoamine.net/blog/2015/09/07/contentless-fts4-for-large-immutable-documents/,140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/3/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed
463544206,MDU6SXNzdWU0NjM1NDQyMDY=,537,"Populate ""endpoint"" key in ASGI scope",9599,open,0,,,12,2019-07-03T04:54:47Z,2019-07-22T06:03:18Z,,OWNER,,"This is a trick used by Starlette so that other layers of ASGI middleware can see which route was selected.

They added it here: https://github.com/encode/starlette/commit/34d0097feb6f057bd050d5057df5a2f96b97384e

If Datasette supports it as well we can benefit from it if we integrate this sentry_asgi middleware (probably as a `datasette-sentry` plugin): https://github.com/encode/sentry-asgi/blob/c6a42d44d31f85885b79e4ee898683ecf8104971/sentry_asgi/middleware.py#L34-L35",107914493,issue,,,"{""url"": ""https://api.github.com/repos/simonw/datasette/issues/537/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,
470691622,MDU6SXNzdWU0NzA2OTE2MjI=,5,Add progress bar,9599,closed,0,,,2,2019-07-20T16:29:07Z,2019-07-22T03:30:13Z,2019-07-22T02:49:22Z,MEMBER,,"Showing a progress bar would be nice, using Click.

The easiest way to do this would probably be be to hook it up to the length of the compressed content, and update it as this code pushes more XML bytes through the parser:

https://github.com/dogsheep/healthkit-to-sqlite/blob/d64299765064501f4efdd9a0b21dbdba9ec4287f/healthkit_to_sqlite/utils.py#L6-L10",197882382,issue,,,"{""url"": ""https://api.github.com/repos/dogsheep/healthkit-to-sqlite/issues/5/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed
470856782,MDU6SXNzdWU0NzA4NTY3ODI=,6,Break up records into different tables for each type,9599,closed,0,,,1,2019-07-22T01:54:59Z,2019-07-22T03:28:55Z,2019-07-22T03:28:50Z,MEMBER,,"I don't think there's much benefit to having all of the different record types stored in the same enormous table. Here's what I get when I use `_facet=type`:

<img width=""358"" alt=""hello2__records__2_672_233_rows"" src=""https://user-images.githubusercontent.com/9599/61601118-e2f54d00-abe8-11e9-8bf6-3df2ef969112.png"">

I'm going to try splitting these up into separate tables - so `HKQuantityTypeIdentifierBodyMassIndex` becomes a table called `rBodyMassIndex` - and see if that's nicer to work with.",197882382,issue,,,"{""url"": ""https://api.github.com/repos/dogsheep/healthkit-to-sqlite/issues/6/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed