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
836829560,MDU6SXNzdWU4MzY4Mjk1NjA=,248,support for Apache Arrow / parquet files I/O,649467,open,0,,,1,2021-03-20T14:59:30Z,2021-10-28T23:46:48Z,,NONE,,"I just started looking at Apache Arrow using pyarrow for import and export of tabular datasets, and it looks quite compelling. It might be worth looking at for sqlite-utils and/or datasette.

As a test, I took a random jsonl data dump of a dataset I have with floats, strings, and ints and converted it to arrow's parquet format using the naive `pyarrow.parquet.write_file()` command, which has automatic type inferrence. It compressed down to 7% of the original size. Conversion of a 26MB JSON file and serializing it to parquet was eyeblink instantaneous. Parquet files are portable and can be directly imported into pandas and other analytics software. 

The only hangup is the automatic type inference of the naive reader. It's great for general laziness and for parsing JSON columns (it correctly interpreted a table of mine with a JSON array). However, I did get an exception for a string column where most entries looked integer-like but had a couple values that weren't -- the reader tried to coerce all of them for some reason, even though the JSON type is string. Since the writer optionally takes a schema, it shouldn't be too hard to grab the sqlite header types. With some additional hinting, you might get datetime columns and JSON, which are native Arrow types. 

Somewhat tangentially, someone even wrote an sqlite vfs extension for Parquet: https://cldellow.com/2018/06/22/sqlite-parquet-vtable.html

",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/248/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,
808771690,MDU6SXNzdWU4MDg3NzE2OTA=,1225,More flexible formatting of records with CSS grid,649467,open,0,,,0,2021-02-15T19:28:17Z,2021-02-15T19:28:35Z,,NONE,,"In several applications I've been experimenting with alternate formatting of datasette query results. Lately I've found that CSS grids work very well and seem quite general for formatting rows. In CSS I use grid templates to define the layout of each record and the regions for each field, hiding the fields I don't want. It's pretty flexible and looks good. It's also a great basis for highly responsive layout.

I initially thought I'd only use this feature for record detail views, but now I use it for index views as well. 

However, there are some limitations:
* With the existing table templates, it seems that you can change the `display` property on the enclosing `table`, `tbody`, and `tr` to make them be grid-like, but that seems hacky (convert `table` and `tbody` to be `display: block` and `tr` to be `display: grid`).
* More significantly, it's very nice to have the column name available when rendering each record to display headers/field labels. The existing templates don't do that, so a custom `_table` template is necessary.
* I don't know if any plugins are sensitive to whether data is rendered as a table or not since I'm not completely clear how plugins get their data. 
* Regardless, you need custom CSS to take full advantage of grids. I don't have a proposal on how to integrate them more deeply.

It would be helpful to at least have an official example or test that used a grid layout for records to make sure nothing in datasette breaks with it. ",107914493,issue,,,"{""url"": ""https://api.github.com/repos/simonw/datasette/issues/1225/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,
718238967,MDU6SXNzdWU3MTgyMzg5Njc=,1003,from_json jinja2 filter,649467,open,0,,,4,2020-10-09T15:30:58Z,2020-10-09T17:17:07Z,,NONE,,"When JSON fields are rendered in a jinja2 template, it is handy to be able to manipulate them as data (e.g., iterate over an array of values). 

Ansible has a ""from_json"" function, which just called json.loads. It's a trivial as a datasette plugin, but it seems generally useful. Does it makes sense to add it directly into the app?",107914493,issue,,,"{""url"": ""https://api.github.com/repos/simonw/datasette/issues/1003/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,