id,node_id,number,title,user,user_label,state,locked,assignee,assignee_label,milestone,milestone_label,comments,created_at,updated_at,closed_at,author_association,pull_request,body,repo,repo_label,type,active_lock_reason,performed_via_github_app,reactions,draft,state_reason
1662951875,I_kwDOBm6k_c5jHqHD,2057,DeprecationWarning: pkg_resources is deprecated as an API,9599,simonw,closed,0,,,,,25,2023-04-11T17:41:20Z,2023-09-21T22:09:10Z,2023-09-21T22:09:10Z,OWNER,,"Got this running tests against Python 3.11.

```
../../../.local/share/virtualenvs/datasette-big-local-6Yn-280V/lib/python3.11/site-packages/datasette/app.py:14: in <module>
    import pkg_resources
../../../.local/share/virtualenvs/datasette-big-local-6Yn-280V/lib/python3.11/site-packages/pkg_resources/__init__.py:121: in <module>
    warnings.warn(""pkg_resources is deprecated as an API"", DeprecationWarning)
E   DeprecationWarning: pkg_resources is deprecated as an API
```

I ran with `pytest -Werror --pdb -x` to get the debugger for that warning, but it turned out searching the code worked better. It's used in these two places:

https://github.com/simonw/datasette/blob/5890a20c374fb0812d88c9b0ef26a838bfa06c76/datasette/plugins.py#L43-L50

https://github.com/simonw/datasette/blob/5890a20c374fb0812d88c9b0ef26a838bfa06c76/datasette/app.py#L1037",107914493,datasette,issue,,,"{""url"": ""https://api.github.com/repos/simonw/datasette/issues/2057/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed
1124731464,I_kwDOCGYnMM5DCgpI,399,"Make it easier to insert geometries, with documentation and maybe code",9599,simonw,open,0,,,,,25,2022-02-05T00:11:26Z,2023-05-16T03:11:52Z,,OWNER,,"In playing with the new SpatiaLite helpers from #385 I noticed that actually populating geometry columns is still a little bit tricky. Here's what I ended up doing:

```python
import httpx, sqlite_utils
db = sqlite_utils.Database(""/tmp/spatial.db"")
attractions = httpx.get(""https://latest.datasette.io/fixtures/roadside_attractions.json?_shape=array"").json()
db[""attractions""].insert_all(attractions, pk=""pk"")

# Schema of that table is now:
# CREATE TABLE [attractions] (
#    [pk] INTEGER PRIMARY KEY,
#    [name] TEXT,
#    [address] TEXT,
#    [latitude] FLOAT,
#    [longitude] FLOAT
# )

db.init_spatialite()
db[""attractions""].add_geometry_column(""point"", ""POINT"")

db.execute(""""""
    update attractions set point = GeomFromText(
      'POINT(' || longitude || ' ' || latitude || ')', 4326
    )
"""""")
```
That last line took some figuring out - especially the need for the SRID of `4326`, without which I got this error:

> `IntegrityError: attractions.point violates Geometry constraint [geom-type or SRID not allowed]`

It would be good to both document this in more detail, but ideally also to come up with a more obvious pattern for inserting common types of spatial data.

Also related:
- #398
- #79",140912432,sqlite-utils,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/399/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,
813880401,MDExOlB1bGxSZXF1ZXN0NTc3OTUzNzI3,5,WIP: Add Gmail takeout mbox import,306240,UtahDave,open,0,,,,,25,2021-02-22T21:30:40Z,2021-07-28T07:18:56Z,,FIRST_TIME_CONTRIBUTOR,dogsheep/google-takeout-to-sqlite/pulls/5,"WIP

This PR adds the ability to import emails from a Gmail mbox export from Google Takeout.

This is my first PR to a datasette/dogsheep repo. I've tested this on my personal Google Takeout mbox with ~520,000 emails going back to 2004. This took around ~20 minutes to process.

To provide some feedback on the progress of the import I added the ""rich"" python module. I'm happy to remove that if adding a dependency is discouraged. However, I think it makes a nice addition to give feedback on the progress of a long import.

Do we want to log emails that have errors when trying to import them?

Dealing with encodings with emails is a bit tricky. I'm very open to feedback on how to deal with those better. As well as any other feedback for improvements.",206649770,google-takeout-to-sqlite,pull,,,"{""url"": ""https://api.github.com/repos/dogsheep/google-takeout-to-sqlite/issues/5/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",0,
639993467,MDU6SXNzdWU2Mzk5OTM0Njc=,850,Proof of concept for Datasette on AWS Lambda with EFS,9599,simonw,open,0,,,,,25,2020-06-16T21:48:31Z,2020-06-16T23:52:16Z,,OWNER,,"https://aws.amazon.com/about-aws/whats-new/2020/06/aws-lambda-support-for-amazon-elastic-file-system-now-generally-/

If Datasette can run on Lambda with access to EFS it could both read AND write large databases there.",107914493,datasette,issue,,,"{""url"": ""https://api.github.com/repos/simonw/datasette/issues/850/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,