issues

When starting datasette on a SpatialLite database without loading the SpatiaLite extension (using eg --load-extension=/usr/local/lib/mod_spatialite.dylib) an error is thrown and the server fails to start:

datasette -p 8003 adminboundaries.db Serve! files=('adminboundaries.db',) on port 8003 Traceback (most recent call last): File "/Users/ajh59/anaconda3/bin/datasette", line 11, in <module> sys.exit(cli()) File "/Users/ajh59/anaconda3/lib/python3.6/site-packages/click/core.py", line 722, in __call__ return self.main(*args, **kwargs) File "/Users/ajh59/anaconda3/lib/python3.6/site-packages/click/core.py", line 697, in main rv = self.invoke(ctx) File "/Users/ajh59/anaconda3/lib/python3.6/site-packages/click/core.py", line 1066, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/Users/ajh59/anaconda3/lib/python3.6/site-packages/click/core.py", line 895, in invoke return ctx.invoke(self.callback, **ctx.params) File "/Users/ajh59/anaconda3/lib/python3.6/site-packages/click/core.py", line 535, in invoke return callback(*args, **kwargs) File "/Users/ajh59/anaconda3/lib/python3.6/site-packages/datasette/cli.py", line 552, in serve ds.inspect() File "/Users/ajh59/anaconda3/lib/python3.6/site-packages/datasette/app.py", line 273, in inspect "tables": inspect_tables(conn, self.metadata.get("databases", {}).get(name, {})) File "/Users/ajh59/anaconda3/lib/python3.6/site-packages/datasette/inspect.py", line 79, in inspect_tables "PRAGMA table_info({});".format(escape_sqlite(table)) sqlite3.OperationalError: no such module: VirtualSpatialIndex

It would be nice to trap this and return a message saying something like:

``` It looks like you're trying to load a SpatiaLite database? Make sure you load in the SpatiaLite extension when starting datasette.

Read more: https://datasette.readthedocs.io/en/latest/spatialite.html ```

I might be wrong but I was not able to publish to heroku with --extra-options, I think extra_options is not being used in this function here.

Any help appreciated!

The default preview of a database shows all columns (is the row count limited?) which is fine in many cases but can take a long time to load / offer a large overhead if the table is a SpatiaLite table containing geometry columns that include large shapefiles.

Would it make sense to have a setting that can limit the amount of text displayed in any given cell in the table preview, or (less useful?) suppress (with notification) the display of overlong columns unless enabled by the user?

An issue then arises if a user does want to see all the text in a cell:

1) for a particular cell; 2) for every cell in the table; 3) for all cells in a particular column or columns

(I haven't checked but what if a column contains e.g. raw image data? Does this display as raw data? Or can this be rendered in a context aware way as an image preview? I guess a custom template would be one way to do that?)

Might be as simple as: pick he type of chart (bar, line) and then pick the column for the X axis and the column for the Y axis. Maybe also allow a pie chart. It’s up to the user to come up with SQL that gets the right values.

https://docs.travis-ci.com/user/deployment/pypi/

Each visualization should have a way of deciding if it might be appropriate for the current view of data.

We can then offer a "suggested visualizations" prompt which shows previews.

https://vega.github.io/vega/examples/population-pyramid/ for example looks pretty easy to hook up to Datasette.

Depends on #14

The version of SQLite that ships with Python 3 is a bit limited - it doesn't support row values for example https://www.sqlite.org/rowvalue.html

Figure out how to bundle a more recent SQLite engine with datasette. We need to figure out two cases:

• Bundling a recent version in a Dockerfile build. I expect this to be quite easy.
• Making a more recent version available to people hacking around in Mac OS X. I have no idea how to start on this.

I want it working on Mac OS X too because I don't want to force Docker as a dependency for anyone who just want to hack around with Datasette a little and run the test suite.

They've got a bit slow. Part of this is the Zeit Now deploy, but the build-and-test cycle is taking at least a couple of minutes.