html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,issue,performed_via_github_app
https://github.com/simonw/datasette/pull/1159#issuecomment-1399589414,https://api.github.com/repos/simonw/datasette/issues/1159,1399589414,IC_kwDOBm6k_c5TbAom,193185,2023-01-22T19:48:41Z,2023-01-22T19:48:41Z,CONTRIBUTOR,"Hey @lovasoa, I hope you don't mind - I pulled this PR into [datasette-ui-extras](https://github.com/cldellow/datasette-ui-extras), a plugin I'm making that collects UI tweaks to Datasette.

You can apply it to your own Datasette instance by running `datasette install datasette-ui-extras`","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",774332247,
https://github.com/simonw/datasette/pull/1893#issuecomment-1317681193,https://api.github.com/repos/simonw/datasette/issues/1893,1317681193,IC_kwDOBm6k_c5Oijgp,95570,2022-11-16T21:19:13Z,2022-11-16T21:19:13Z,CONTRIBUTOR,"Alright, added Cmd+Enter to submit (Ctrl+Enter on Windows as well bc of using Meta-Enter on codemirror). We can make that MacOS only by changing the combo to Cmd+Enter specifically but I think it's probably fine to have both.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1450363982,
https://github.com/simonw/datasette/issues/1384#issuecomment-1066222323,https://api.github.com/repos/simonw/datasette/issues/1384,1066222323,IC_kwDOBm6k_c4_jULz,2670795,2022-03-14T00:36:42Z,2022-03-14T00:36:42Z,CONTRIBUTOR,"> Ah, sorry, I didn't get what you were saying you the first time. Using _metadata_local in that way makes total sense -- I agree, refreshing metadata each cell was seeming quite excessive. Now I'm on the same page! :)

All good. Report back any issues you find with this stuff. Metadata/dynamic config hasn't been tested widely outside of what I've done AFAIK. If you find a strong use case for async meta, it's going to be better to know sooner rather than later!","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",930807135,
https://github.com/simonw/sqlite-utils/issues/399#issuecomment-1030740653,https://api.github.com/repos/simonw/sqlite-utils/issues/399,1030740653,IC_kwDOCGYnMM49b9qt,25778,2022-02-06T02:57:17Z,2022-02-06T02:57:17Z,CONTRIBUTOR,"I like the idea of having stock conversions you could import. I'd actually move them to a dedicated module (call it `sqlite_utils.conversions` or something), because it's different from other utilities. Maybe they even take configuration, or they're composable.

```python
from sqlite_utils.conversions import LongitudeLatitude

db[""places""].insert(
    {
        ""name"": ""London"",
        ""lng"": -0.118092,
        ""lat"": 51.509865,
    },
    conversions={""point"": LongitudeLatitude(""lng"", ""lat"")},
)
```

I would definitely use that for every CSV I get with lat/lng columns where I actually need GeoJSON.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1124731464,
https://github.com/simonw/datasette/issues/1522#issuecomment-976117989,https://api.github.com/repos/simonw/datasette/issues/1522,976117989,IC_kwDOBm6k_c46LmDl,813732,2021-11-23T03:00:34Z,2021-11-23T03:00:34Z,CONTRIBUTOR,"I tried deploying the most recent version of the Dockerfile in this thread ([link to comment](https://github.com/simonw/datasette/issues/1522#issuecomment-974605128)), and after trying a few different different combinations, I was only successful when I used `--no-cpu-throttling` (""CPU Is always allocated"" in the UI)

Using this method, I got a very similar issue to you: The first time I'd load the site I'd get a 503. But after that first load, I didn't get the issue again. It would re-occur if the service started from cold boot. 

I suspect this is a race condition in the supervisord configuration. The errors I got were the same `Connection refused: AH00957: http: attempt to connect to 127.0.0.1:8001 (127.0.0.1) failed`, and that seems to indicate that `datasette` hadn't yet started. 

Looking at the order of logs getting back, the processes reported successfully completing loading after the first 503 was returned, so that makes me think race condition. 

I can replicate this locally, if I `docker run` and request `localhost:5000/prefix` _before_ I get the `datasette entered RUNNING state` message. Cloud Run wakes up when requests are received, so this test would semi-replicate that, but local docker would be the equivalent of a persistent process, hence it doesn't normally exhibit the same issues.

Unfortunately supervisor/supervisor issue 122 (not linking as to prevent cross-project link spam) seems to say that dependency chaining is a feature that's been asked for for a long time, but hasn't been implemented. You could try some suggestions in that thread. ","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1058896236,
https://github.com/simonw/datasette/issues/1284#issuecomment-949604763,https://api.github.com/repos/simonw/datasette/issues/1284,949604763,IC_kwDOBm6k_c44mdGb,536941,2021-10-22T12:54:34Z,2021-10-22T12:54:34Z,CONTRIBUTOR,i'm going to take a swing at this today. we'll see.,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",845794436,
https://github.com/simonw/datasette/pull/1455#issuecomment-913001282,https://api.github.com/repos/simonw/datasette/issues/1455,913001282,IC_kwDOBm6k_c42a0tC,51016,2021-09-04T16:31:24Z,2021-09-04T16:31:24Z,CONTRIBUTOR,I love it! maybe 'researchers' instead? Or 'scientists and researchers'?,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",988325628,
https://github.com/simonw/datasette/issues/1286#issuecomment-815978405,https://api.github.com/repos/simonw/datasette/issues/1286,815978405,MDEyOklzc3VlQ29tbWVudDgxNTk3ODQwNQ==,192568,2021-04-08T16:47:29Z,2021-04-10T03:59:00Z,CONTRIBUTOR,"This worked for me:                      
`<td class=""col-{{ cell.column|to_css_class }} type-{{ cell.value_type }}"">{{ cell.value | replace('"", ""','; ') | replace('[\""','') | replace('\""]','')}}</td>`

I'm sure there is a prettier (and more flexible) way, but for now, this is ever-so-much more pleasant to look at. 

------ AFTER:
<img width=""778"" alt=""Screen Shot 2021-04-08 at 12 27 36 PM"" src=""https://user-images.githubusercontent.com/192568/114062829-f2f20c00-9865-11eb-891d-b0c348a9b433.png"">

------ BEFORE:
<img width=""795"" alt=""Screen Shot 2021-04-08 at 12 25 54 PM"" src=""https://user-images.githubusercontent.com/192568/114062871-01402800-9866-11eb-91ce-91efe4ee45cd.png"">



(Note: I didn't figure out how to have one item have no semicolon, while multi-items close with a semicolon, but this is good enough for now. I also didn't figure out how to set up a new jinja filter. I don't want to add to /datasette/utils/__init__.py as I assume that would get overwritten when upgrading datasette. Having a starter guide on creating jinja filters in datasette would be helpful. (The jinja documentation isn't datasette-specific enough for me to quite nail it.)
","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",849220154,
https://github.com/simonw/datasette/issues/1274#issuecomment-805214307,https://api.github.com/repos/simonw/datasette/issues/1274,805214307,MDEyOklzc3VlQ29tbWVudDgwNTIxNDMwNw==,7476523,2021-03-23T20:12:29Z,2021-03-23T20:12:29Z,CONTRIBUTOR,"One issue I could see with adding first class support for metadata in hjson format is that this would require adding an additional dependency to handle this, for a feature that would be unused by many users. I wonder if this could fit in as a plugin instead; if a hook existed for loading metadata (maybe as part of https://github.com/simonw/datasette/issues/860) the metadata could then come from any source, as specified by plugins, e.g. hjson, toml, XML, a database table etc.

Until/unless this exists, a few ideas for how you could add comments:
- Using YAML as you suggest.
- A common pattern is adding a `""comment""` key for comments to any object in JSON - I don't think including an unnecessary key like this would break anything in Datasette, but not certain.
- You could use another tool as a preprocessor for your JSON metadata - e.g. hjson or Jsonnet. You'd write the metadata in that format, and then convert that into JSON to actually use as your final metadata.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",839008371,
https://github.com/simonw/sqlite-utils/pull/189#issuecomment-717359145,https://api.github.com/repos/simonw/sqlite-utils/issues/189,717359145,MDEyOklzc3VlQ29tbWVudDcxNzM1OTE0NQ==,35681,2020-10-27T16:20:32Z,2020-10-27T16:20:32Z,CONTRIBUTOR,"No problem. I added a test. Let me know if it looks sufficient or if you want me to to tweak something!

If you don't mind, would you tag this PR as ""hacktoberfest-accepted""? If you do mind, no problem and I'm sorry for asking :) My kiddos like the shirts.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",729818242,
https://github.com/simonw/sqlite-utils/issues/121#issuecomment-655652679,https://api.github.com/repos/simonw/sqlite-utils/issues/121,655652679,MDEyOklzc3VlQ29tbWVudDY1NTY1MjY3OQ==,79913,2020-07-08T17:24:46Z,2020-07-08T17:24:46Z,CONTRIBUTOR,"Better transaction handling would be really great. Some of my thoughts on implementing better transaction discipline are in https://github.com/simonw/sqlite-utils/pull/118#issuecomment-655239728.

My preferences:

- Each CLI command should operate in a single transaction so that either the whole thing succeeds or the whole thing is rolled back. This avoids partially completed operations when an error occurs part way through processing. Partially completed operations are typically much harder to recovery from gracefully and may cause inconsistent data states.

- The Python API should be transaction-agnostic and rely on the caller to coordinate transactions. Only the caller knows how individual insert, create, update, etc operations/methods should be bundled conceptually into transactions. When the caller is the CLI, for example, that bundling would be at the CLI command-level. Other callers might want to break up operations into multiple transactions. Transactions are usually most useful when controlled at the application-level (like logging configuration) instead of the library level. The library needs to provide an API that's conducive to transaction use, though.

- The Python API should provide a context manager to provide consistent transactions handling with more useful defaults than Python's `sqlite3` module. The latter issues implicit `BEGIN` statements by default for most DML (`INSERT`, `UPDATE`, `DELETE`, … but not `SELECT`, I believe), but **not** DDL (`CREATE TABLE`, `DROP TABLE`, `CREATE VIEW`, …). Notably, the `sqlite3` module doesn't issue the implicit `BEGIN` until the first DML statement. It _does not_ issue it when entering the `with conn` block, like other DBAPI2-compatible modules do. The `with conn` block for `sqlite3` only arranges to commit or rollback an existing transaction when exiting. Including DDL and `SELECT`s in transactions is important for operation consistency, though. There are several existing bugs.python.org tickets about this and future changes are in the works, but sqlite-utils can provide its own API sooner. sqlite-utils's `Database` class could itself be a context manager (built on the `sqlite3` connection context manager) which additionally issues an explicit `BEGIN` when entering. This would then let Python API callers do something like:

```python
db = sqlite_utils.Database(path)

with db: # ← BEGIN issued here by Database.__enter__
    db.insert(…)
    db.create_view(…)
# ← COMMIT/ROLLBACK issue here by sqlite3.connection.__exit__
```","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",652961907,
https://github.com/simonw/datasette/issues/394#issuecomment-602907207,https://api.github.com/repos/simonw/datasette/issues/394,602907207,MDEyOklzc3VlQ29tbWVudDYwMjkwNzIwNw==,127565,2020-03-23T23:12:18Z,2020-03-23T23:12:18Z,CONTRIBUTOR,"This would also be useful for running Datasette in Jupyter notebooks on [Binder](https://mybinder.org/). While you can use [Jupyter-server-proxy](https://github.com/jupyterhub/jupyter-server-proxy) to access Datasette on Binder, the links are broken.

Why run Datasette on Binder? I'm developing a [range of Jupyter notebooks](https://glam-workbench.github.io/) that are aimed at getting humanities researchers to explore data from libraries, archives, and museums. Many of them are aimed at researchers with limited digital skills, so being able to run examples in Binder without them installing anything is fantastic.

For example, there are a [series of notebooks](https://glam-workbench.github.io/trove-harvester/) that help researchers harvest digitised historical newspaper articles from Trove. The metadata from this harvest is saved as a CSV file that users can download. I've also provided some extra notebooks that use Pandas etc to demonstrate ways of analysing and visualising the harvested data.

But it would be really nice if, after completing a harvest, the user could spin up Datasette for some initial exploration of their harvested data without ever leaving their browser.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",396212021,