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
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}",,
1128466114,I_kwDOCGYnMM5DQwbC,406,Creating tables with custom datatypes,82988,open,0,,,5,2022-02-09T12:16:31Z,2022-09-15T18:13:50Z,,NONE,,"Via https://stackoverflow.com/a/18622264/454773 I note the ability to register custom handlers for novel datatypes that can map into and out of things like sqlite `BLOB`s.

From a quick look and a quick play, I didn't spot a way to do this in `sqlite_utils`?

For example:

```python
# Via https://stackoverflow.com/a/18622264/454773
import sqlite3
import numpy as np
import io

def adapt_array(arr):
    """"""
    http://stackoverflow.com/a/31312102/190597 (SoulNibbler)
    """"""
    out = io.BytesIO()
    np.save(out, arr)
    out.seek(0)
    return sqlite3.Binary(out.read())

def convert_array(text):
    out = io.BytesIO(text)
    out.seek(0)
    return np.load(out)


# Converts np.array to TEXT when inserting
sqlite3.register_adapter(np.ndarray, adapt_array)

# Converts TEXT to np.array when selecting
sqlite3.register_converter(""array"", convert_array)
```

```python
from sqlite_utils import Database
db = Database('test.db')

# Reset the database connection to used the parsed datatype
# sqlite_utils doesn't seem to support eg:
#  Database('test.db', detect_types=sqlite3.PARSE_DECLTYPES)
db.conn = sqlite3.connect(db_name, detect_types=sqlite3.PARSE_DECLTYPES)

# Create a table the old fashioned way
# but using the new custom data type
vector_table_create = """"""
CREATE TABLE dummy 
    (title TEXT, vector array );
""""""

cur = db.conn.cursor()
cur.execute(vector_table_create)


# sqlite_utils doesn't appear to support custom types (yet?!)
# The following errors on the ""array"" datatype
""""""
db[""dummy""].create({
    ""title"": str,
    ""vector"": ""array"",
})
""""""
```

We can then add / retrieve records from the database where the datatype of the `vector` field is a custom registered `array` type (which is to say, a `numpy` array):

```python
import numpy as np

db[""dummy""].insert({'title':""test1"", 'vector':np.array([1,2,3])})

for row in db.query(""SELECT * FROM dummy""):
    print(row['title'], row['vector'], type(row['vector']))

""""""
test1 [1 2 3] <class 'numpy.ndarray'>
""""""
```

It would be handy to be able to do this idiomatically in `sqlite_utils`.",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/406/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,
527710055,MDU6SXNzdWU1Mjc3MTAwNTU=,640,Nicer error message for heroku publish name clash,82988,open,0,,,1,2019-11-24T14:57:07Z,2019-12-06T07:19:34Z,,CONTRIBUTOR,,"If you try to publish to Heroku using no set name (i.e. the default `datasette` name) and a project already exists under that name, you get a meaningful error report on the first line followed by Py error messages that drown it out:

```
Creating datasette... !
 ▸    Name datasette is already taken
Traceback (most recent call last):
  File ""/usr/local/bin/datasette"", line 10, in <module>
    sys.exit(cli())
  File ""/usr/local/lib/python3.7/site-packages/click/core.py"", line 764, in __call__
    return self.main(*args, **kwargs)
  File ""/usr/local/lib/python3.7/site-packages/click/core.py"", line 717, in main
    rv = self.invoke(ctx)
  File ""/usr/local/lib/python3.7/site-packages/click/core.py"", line 1137, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File ""/usr/local/lib/python3.7/site-packages/click/core.py"", line 1137, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File ""/usr/local/lib/python3.7/site-packages/click/core.py"", line 956, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File ""/usr/local/lib/python3.7/site-packages/click/core.py"", line 555, in invoke
    return callback(*args, **kwargs)
  File ""/Users/NNNNN/Library/Python/3.7/lib/python/site-packages/datasette/publish/heroku.py"", line 124, in heroku
    create_output = check_output(cmd).decode(""utf8"")
  File ""/usr/local/Cellar/python/3.7.5/Frameworks/Python.framework/Versions/3.7/lib/python3.7/subprocess.py"", line 411, in check_output
    **kwargs).stdout
  File ""/usr/local/Cellar/python/3.7.5/Frameworks/Python.framework/Versions/3.7/lib/python3.7/subprocess.py"", line 512, in run
    output=stdout, stderr=stderr)
subprocess.CalledProcessError: Command '['heroku', 'apps:create', 'datasette', '--json']' returned non-zero exit status 1.
```

It would be neater if:

- the Py error message was caught;
- the report suggested setting a project name using `-n` etc.

It may also be useful to provide a command to list the current names that are being used, which I assume is available via a Heroku call?",107914493,issue,,,"{""url"": ""https://api.github.com/repos/simonw/datasette/issues/640/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,
377166793,MDU6SXNzdWUzNzcxNjY3OTM=,372,Docker build tools,82988,open,0,,,0,2018-11-04T16:02:35Z,2018-11-04T16:02:35Z,,CONTRIBUTOR,,"In terms of small pieces lightly joined, I note that there are several tools starting to appear for building generating Dockerfiles and building Docker containers from simpler components such as `requirements.txt` files.

If plugin/extensions builders want to include additional packages, then things like incremental builds of composable builds that add additional items into a base `datasette` container may be required.

Examples of Dockerfile generators / container builders:

- [openshift/source-to-image (s2i)](https://github.com/openshift/source-to-image)
- [jupyter/repo2docker](https://github.com/jupyter/repo2docker)
- [stencila/dockter](https://github.com/stencila/dockter)

Discussions / threads  (via Binderhub gitter) on:
- [why `repo2docker` not `s2i`](http://words.yuvi.in/post/why-not-s2i/)
- [why `dockter` not `repo2docker`](https://twitter.com/choldgraf/status/1058499607309647872)
- [composability in `s2i`](https://trello.com/c/AexIVZNf/1008-8-composable-builds-builds-evg)

Relates to things like:

- https://github.com/simonw/datasette/pull/280",107914493,issue,,,"{""url"": ""https://api.github.com/repos/simonw/datasette/issues/372/reactions"", ""total_count"": 2, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 2, ""rocket"": 0, ""eyes"": 0}",,