Thanks again for such a powerful project.

For deploying to cloudrun from github actions, I'd like to create a service account with minimal permissions.

It would be great to document what those minimum permission that need to be set in the IAM.

The PR moves the following fields from metadata.yaml to datasette.yaml:

permissions allow allow_sql queries extra_css_urls extra_js_urls

This is a significant breaking change that users will need to upgrade their metadata.yaml files for. But the format/locations are similar to the previous version, so it shouldn't be too difficult to upgrade.

One note: I'm still working on the Configuration docs, specifically the "reference" section. Though it's pretty small, the rest of read to review

Part of #2093

In #2149 , we ported over "settings.json" into the new datasette.yaml config file, with a top-level "settings" key. This PR ports over plugin configuration into top-level "plugins" key, as well as nested database/table plugin config.

From now on, no plugin-related configuration is allowed in metadata.yaml, and must be in datasette.yaml in this new format. This is a pretty significant breaking change. Thankfully, you should be able to copy-paste your legacy plugin key/values into the new datasette.yaml format.

An example of what datasette.yaml would look like with this new plugin config:

```yaml

plugins: datasette-my-plugin: config_key: value

databases: fixtures: plugins: datasette-my-plugin: config_key: fixtures-db-value tables: students: plugins: datasette-my-plugin: config_key: fixtures-students-table-value

```

As an additional benefit, this now works with the new -s flag:

bash datasette --memory -s 'plugins.datasette-my-plugin.config_key' new_value

Marked as a "Draft" right now until I add better documentation. We also should have a plan for the next alpha release to document and publicize this change, especially for plugin authors (since their docs will have to change to say datasette.yaml instead of metadata.yaml

:books: Documentation preview :books:: https://datasette--2183.org.readthedocs.build/en/2183/

refs #2157

This PR adds a new --internal option to datasette serve. If provided, it is the path to a persistent internal database that Datasette core and Datasette plugins can use to store data, as discussed in the proposal issue.

This PR also removes and deprecates the previous in-memory _internal database. Those tables now appear in the internal database, with core_ prefixes (ex tables in _internal is now core_tables in internal).

A note on the new core_ tables

However, one important notes about those new core_ tables: If a --internal DB is passed in, that means those core_ tables will persist across multiple Datasette instances. This wasn't the case before, since _internal was always an in-memory database created from scratch.

I tried to put those core_ tables as TEMP tables - after all, there's always one 1 internal DB connection at a time, so I figured it would work. But, since we use the Database() wrapper for the internal DB, it has two separate connections: a default read-only connection and a write connection that is created when a write operation occurs. Which meant the TEMP tables would be created by the write connection, but not available in the read-only connection.

So I had a brillant idea: Attach an in-memory named database with cache=shared, and create those tables there!

sql ATTACH DATABASE 'file:datasette_internal_core?mode=memory&cache=shared' AS core;

We'd run this on both the read-only connection and the write-only connection. That way, those tables would stay in memory, they'd communicate with the cache=shared feature, and we'd be good to go.

However, I couldn't find an easy way to run a ATTACH DATABASE command on the read-only query.

Using Database() as a wrapper for the internal DB is pretty limiting - it's meant for Datasette "data" databases, where we want multiple readers and possibly 1 write connection at a time. But the internal database doesn't really require that kind of support - I think we could get away with a single read/write connection, but it seemed like too big of a rabbithole to go through now.

:books: Documentation preview :books:: https://datasette--2162.org.readthedocs.build/en/2162/

I've been thinking about what it might look like to allow command-line arguments to be used to define any of the configuration options in datasette.yml, as alternative and more convenient syntax.

Here's what I've come up with: datasette \ -s settings.sql_time_limit_ms 1000 \ -s plugins.datasette-auth-tokens.manage_tokens true \ -s plugins.datasette-auth-tokens.manage_tokens_database tokens \ mydatabase.db tokens.db Which would be equivalent to datasette.yml containing this: yaml plugins: datasette-auth-tokens: manage_tokens: true manage_tokens_database: tokens settings: sql_time_limit_ms: 1000 More details in https://github.com/simonw/datasette/issues/2143#issuecomment-1690792514

See: - https://github.com/simonw/datasette-configure-fts/issues/14 - https://github.com/simonw/datasette-auth-tokens/issues/12

I just noticed that https://latest.datasette.io/fixtures/roadside_attraction_characteristics.json?_labels=on&_size=1 returns: json { "ok": true, "next": "1", "rows": [ { "rowid": 1, "attraction_id": { "value": 1, "label": "The Mystery Spot" }, "characteristic_id": { "value": 2, "label": "Paranormal" } } ], "truncated": false } But https://latest.datasette.io/fixtures.json?sql=select+rowid%2C+attraction_id%2C+characteristic_id+from+roadside_attraction_characteristics+order+by+rowid+limit+1 returns: json { "rows": [ { "rowid": 1, "attraction_id": 1, "characteristic_id": 2 } ], "columns": [ "rowid", "attraction_id", "characteristic_id" ], "ok": true, "truncated": false } The columns key in the query response is inconsistent with the table response.

This will be the base that the remaining work builds on top of. Refs: - #2109

There are still a bunch of bugs in CodeMirror 5 that affect various mobile browsers - see Datasette Discord report here: https://discord.com/channels/823971286308356157/823971286941302908/1013878624992108645

https://user-images.githubusercontent.com/9599/187349269-7b7c0c8c-3894-4810-82f0-de7c1eb940b3.mp4

https://github.com/mitsuhiko/rye

I tried this:

rye install datasette

But now:

% ~/.rye/shims/datasette Traceback (most recent call last): File "/Users/simon/.rye/shims/datasette", line 5, in <module> from datasette.cli import cli File "/Users/simon/.rye/tools/datasette/lib/python3.11/site-packages/datasette/cli.py", line 17, in <module> from .app import ( File "/Users/simon/.rye/tools/datasette/lib/python3.11/site-packages/datasette/app.py", line 14, in <module> import pkg_resources ModuleNotFoundError: No module named 'pkg_resources' I think that's because setuptools is not included in Rye.

Related: - #262

I've made the change to the table view, now I need the new format to work for arbitrary SQL queries too.

Note that this incorporates both arbitrary SQL queries and canned queries.

Using nginx to redirect public IP to the local uvicorn server as 'normal'. I can't figure out how to redirect such that '/' results in accessing the one db/table I want to serve; redirecting / to /db/table breaks some of the CSS; fooling with base_url doesn't seem to help. Can someone explain this, if it's possible?

From https://docs.datasette.io/en/stable/plugin_hooks.html#render-cell-row-value-column-table-database-datasette:

row - sqlite.Row The SQLite row object that the value being rendered is part of

This appears to actually be a CustomRow, but I think that's unrelated to my issue.

I have a table:

sql CREATE TABLE IF NOT EXISTS "dss_job_stats"( job_id integer not null references dss_job(id) on delete cascade, host text not null, // other columns elided as irrelevant primary key (job_id, host) );

On datasette 0.63.2, the render_cell hook receives a row value that looks like:

CustomRow([('job_id', {'value': 2, 'label': '2'}), ('host', 'cldellow.com')])

I expected the job_id value to be 2, but it's actually {'value': 2, 'label': '2'}.

I can work around this, but was wondering if this was intended behaviour?

I have linked Python3.11 on macOS against recent SQLite that was compiled using -DSQLITE_DQS=0. This option disables interpretation of double-quoted identifiers as string literals, described in the SQLite docs as a "MySQL 3.x misfeature". See https://www.sqlite.org/quirks.html#dblquote for background.

Datasette uses the double-quote syntax in a number of key places, and is thus completely broken in this environment.

My experience was to pip install datasette, then run datasette serve -I my-data.db. When I visit http://127.0.0.1:8001 I get a 500 response.

The error: sqlite3.OperationalError: no such column: geometry_columns

The responsible SQL: 'select 1 from sqlite_master where tbl_name = "geometry_columns"'

I then installed datasette from GitHub master in development mode and changed the offending SQL to use correct quotes: "select 1 from sqlite_master where tbl_name = 'geometry_columns'".

With this change, I get a little further, but have the same problem with the first table name in my database (in my case, "Meta"): OperationalError: no such column: Meta Traceback (most recent call last): File "/Users/gwk/external/datasette/datasette/app.py", line 1522, in route_path response = await view(request, send) ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/gwk/external/datasette/datasette/views/base.py", line 151, in view return await self.dispatch_request(request) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/gwk/external/datasette/datasette/views/base.py", line 105, in dispatch_request response = await handler(request) ^^^^^^^^^^^^^^^^^^^^^^ File "/Users/gwk/external/datasette/datasette/views/index.py", line 70, in get "fts_table": await db.fts_table(table), ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/gwk/external/datasette/datasette/database.py", line 363, in fts_table return await self.execute_fn(lambda conn: detect_fts(conn, table)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/gwk/external/datasette/datasette/database.py", line 213, in execute_fn return await asyncio.get_event_loop().run_in_executor( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/py/Python.framework/Versions/3.11/lib/python3.11/concurrent/futures/thread.py", line 58, in run result = self.fn(*self.args, **self.kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/gwk/external/datasette/datasette/database.py", line 211, in in_thread return fn(conn) ^^^^^^^^ File "/Users/gwk/external/datasette/datasette/database.py", line 363, in <lambda> return await self.execute_fn(lambda conn: detect_fts(conn, table)) ^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/gwk/external/datasette/datasette/utils/__init__.py", line 588, in detect_fts rows = conn.execute(detect_fts_sql(table)).fetchall() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ sqlite3.OperationalError: no such column: Meta INFO: 127.0.0.1:50258 - "GET / HTTP/1.1" 500 Internal Server Error

I will try to continue playing with this, but I also hope that the datasette developers will enable this mode in a test environment as I am unlikely to be able to exercise all of the SQL in the codebase, or make a pull request very soon.

Note that the DQS setting compile-time option can be overridden at runtime with calls to the C API: sqlite3_db_config(db, SQLITE_DBCONFIG_DQS_DDL, 0, (void*)0); sqlite3_db_config(db, SQLITE_DBCONFIG_DQS_DML, 0, (void*)0);

As far as I can tell, sqlite3_db_config is not exposed in Python, but perhaps we could figure out how to invoke it using ctypes.

I hadn't run into an issue with plugins like datasette-template-sql interfering with the existing context for other features before! Definitely not a good thing.

Originally posted by @simonw in https://github.com/simonw/datasette-write/issues/6#issuecomment-1379490596

Need to stop linking to it from the docs.

I'll link to https://www.python.org/about/gettingstarted/ instead.

This should be pretty easy because Uvicorn supports them already. Need a good mechanism for testing it - https://pypi.org/project/trustme/ looks ideal.

There are situations - such as loading SQLite files remotely using HTTP range headers - where counting all of the rows in a table should be avoided entirely.

Also, this chunked inefficiency means that I have to hack the URL to not load tables of a database as it seems to try to load the whole database when I click on a database.

I bet that's because Datasette tries to show a count of all of the rows in each table when it shows the list on that page, which triggers a full table scan.

Would be great to have a setting that turns that feature off, which could then be exposed as a query string option for Datasette Lite.

Originally posted by @simonw in https://github.com/simonw/datasette-lite/issues/49#issuecomment-1256880715

Motivation

• I have a directory of sqlite databases
• I'd like to use immutable mode when opening them for better performance docs

• Currently using this flag throws the following error

  IsADirectoryError: [Errno 21] Is a directory: '/name-of-directory'

Proposal

Immutable flag works for both single files and directories

datasette -i /folder-of-sqlite-files

I installed datasette==1.0a1.

When I go to http://127.0.0.1:8001/-/api I have a link: Use this tool to try out the [Datasette API](https://docs.datasette.io/en/1.0a1/json_api.html). but that documentation page does not exist.

I'm not sure where it has to be fixed, should it link to the stable page https://docs.datasette.io/en/stable/json_api.html , the latest one https://docs.datasette.io/en/latest/json_api.html#the-json-write-api or would it be more appropriated to deploy documentation for the 1.0a1 version?

Equivalent to https://sqlite-utils.datasette.io/en/stable/cli.html#insert-replacing-data

This release will mainly help preview the new Datasette write API: - #1850

API design: POST /db/table/row-pks/-/delete Or... DELETE /db/table/row-pks/-/delete I'm just going to do POST for the moment, like I did here: - #1874

Permission: delete-row

Still needed:

• [ ] Tests for rowid tables
• [ ] Tests for compound primary keys

Reported on Discord: https://discord.com/channels/823971286308356157/823971286941302908/1042814317118115901

``` -----> Building on the Heroku-22 stack -----> Determining which buildpack to use for this app -----> Python app detected -----> Using Python version specified in runtime.txt ! Requested runtime 'python-3.8.10' is not available for this stack (heroku-22). ! For supported versions, see: https://devcenter.heroku.com/articles/python-support ! Push rejected, failed to compile Python app.

! Push failed ▸ Build failed ```

In trying to write this I realize that there's a lot of duplicated code with delete row, specifically around resolving the incoming URL into a row (or a database or a table).

Since this is so common, I think it's worth extracting the logic out first.

Originally posted by @simonw in https://github.com/simonw/datasette/issues/1863#issuecomment-1317755263

After the upgrade to 6 (#1893) I noticed this. I think it's because we're doing overflow:hidden to accomplish the CSS resizer.

When there's a single line of SQL there's a gap below that line where clicking doesn't do anything. It should focus at the end of the line.

Datasette maintains an in-memory SQLite database with details of the the databases, tables and columns for all of the attached databases.

The above is from the docs ^. There's two problems here - the number of datasette "instances" in a single server/VM and the size of the database itself. We want the opposite of in-memory, including what happens on SQLlite - documented in https://www.sqlite.org/inmemorydb.html

From the context in https://github.com/simonw/datasette/issues/1150 - does it mean datasette is memory-bound to the size of the dataset - which might be a deal-breaker for many large-scale use cases?

In an extreme case - let's say a single server had 100 SQLlite databases, which would enable 100 "instances" of datasette to run, one per client (e.g. in a SaaS multi-tenant environment). How could we achieve all these goals:

1. Allow any one of these 100 databases to grow to say 2Tb in size
2. Have one datasette instance, which connects to 1 of the 100 instances, based on incoming credentials/tenant ID
3. Minimize memory use entirely - both by datasette and SQLlite, such that almost all operations are executed in real-time on-disk with little to no memory consumption per-tenant, or per-database.

Any ideas appreciated - we're looking to use this in a SaaS type of setting - many instances, single server.

@simonw great work on datasette, in general! Possibly related to https://github.com/simonw/datasette/issues/1480 but we don't want use any kind of serverless infra - this is a long-running VM/server.

POST /db/table/-/drop

Require drop-table permission.

It's currently possible to use /-/create-token to create a token that lasts forever.

Some administrators may wish to have a maximum expiry instead. I should support that with a setting.

Is it possible to deploy a datasette application as a python web app?

In my enterprise, I have option to deploy python apps via Rstudio Connect, and I would like to publish a datasette dashboard for sharing.

I welcome any pointers to converting datasette serve into a python app that can be run as something like python datasette.py --my_data.db

Datasette Lite: https://lite.datasette.io/?sql=https://gist.githubusercontent.com/simonw/1f8a91123ccefd8844187225b1832d7a/raw/5069075b86aa79358fbab3d4482d1d269077d632/recipes.sql#/data?sql=select+id%2C+name%2C+ingredients%2C+%28%0A++select+json_group_array%28value%29+from+json_each%28ingredients%29%0A++where+value+in+%28select+value+from+json_each%28%3Ap0%29%29%0A%29+as+matching_ingredients%0Afrom+recipes%0Awhere+json_array_length%28matching_ingredients%29+%3E+0%0Aorder+by+json_array_length%28matching_ingredients%29+desc&p0=%5B%22sugar%22%2C+%22cheese%22%5D

I just watched a demo video for the 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
• a cookiecutter for wrting JupyterLab extensions using Javascript
• a cookiecutter for writing JupyterLab extensions using Typescript
• tutorial: Let’s Make an xkcd JupyterLab Extension

Many Datasette instances mainly exist to serve a single table - for example:

• https://global-power-plants.datasettes.com/global-power-plants/global-power-plants
• https://laion-aesthetic.datasette.io/laion-aesthetic-6pls/images

It would be neat if the / homepage of those instances could be configured to highlight that specific table.

Or maybe more than one?

I guess this issue is not very important and probably rare.

To reproduce: * create and populate a db named off.db * in the yaml file, add any kind of information below databases:\n off: * the data are not taken into account (because "off" is interpreted as "false")

YAML file: ```yaml title: Some title description_html: |-

This is an experiment.

databases: off: tables: products_from_owners: title: products_from_owners* description_html: |-

Description

The result for http://xxxx.xxx/-/metadata gives: json { "title": "Some title", "description_html": "<p>This is an experiment.</p>", "databases": { "false": { "tables": { "products_from_owners": { "title": "products_from_owners*", "description_html": "<p>Description</p>" } } } } } => see the "false" instead of "off".

Wide tables aren't a huge problem if you know to click and drag right. But it's not at all obvious to do that. (it also tends to blue-select any content as it's dragging.) Depending on column widths, public users might entirely miss all the columns to the right.

There is a scrollbar at the bottom of the table, but I'm displaying ALL my records because it's the only way for datasette-vega to make accurate charts. So that bottom scrollbar is likely to be missed. I wonder if some sort of javascript-y mouseover to an arrow might help, similar to those seen in image carousels. Ah: here's a perfect example:

1. Visit http://google.com
2. Search for: animals endangered
3. Note the 'g-right-button' (in the code) that looks like a right-facing caret in a circle.
4. Click on that and the carousel scrolls right (and 'g-left-button' appears on the left).

Might be tricky to do that on a table, rather than a one-row carousel, but it's worth experimenting with.

Another option is just to put the scrollbars at the top of the table, too.

Meantime, I'm trying to build a button like the "View/hide all columns on https://salaries.news.baltimoresun.com/salaries-be494cf/2019+Maryland+state+salaries Might be nice to have that available by default, with settings in the metadata showing which are on by default.

(I saw some other closed issues related to horizontal scrolling, and admit I don't entirely understand them. For instance, the animated gif at https://github.com/simonw/datasette/issues/998#issuecomment-714117534 confuses me. )

For example: https://latest.datasette.io/fixtures/sortable?_sort_desc=sortable&_col=sortable_with_nulls

That's ?_sort_desc=sortable&_col=sortable_with_nulls

To solve #241 JSON logging.

view-source:https://calands.datasettes.com/calands/CPAD_2020a_SuperUnits.geojson?_sort=id&id__exact=4&_labels=on&_trace=1 is showing me a blank page.

Refs: - #1733

Need something in the test suite such that if Datasette breaks against Pyodide in the future we hear about it.

I'm thinking this is an opportunity to use shot-scraper javascript.

Relates to #1533 - and to the work I've been doing on the https://github.com/simonw/datasette-table Web Component.

It would be useful to support users pasting in a URL to a Datasette table or query without first having to add the .json extension themselves - since then other systems could hit that URL with Accept: application/json to get back the JSON representation without first needing to read the Link: header from #1533 to figure out what the URL to that JSON is.

(There is weird logic deep in Datasette that says that you add .json to the path UNLESS the table name itself ends with .json, in which case you add ?_format=json - this is super-confusing).

[Update: I removed that confusing feature here: https://simonwillison.net/2022/Mar/19/weeknotes/]

Is it possible to configure the sql_time_limit_ms beyond 60 seconds? It seems queries are still timing out at 60 seconds when sql_time_limit_ms is set to 180000. We have a very large data set and often encounter timeouts when testing new queries from the datasette UI. We are optimizing our database as much as we can, but still may require more than 60 seconds for complex queries.

I realized that one of the reasons I'm having trouble committing to nailing down the JSON API for 1.0 is that I don't use it much myself - I use the ?_shape=array one quite often, but I don't have any projects that are using the default, more fully-featured API.

As an experiment I built a Web Component for embedding Datasette tables on pages - https://github.com/simonw/datasette-table - and I think it's actually going to be a really useful tool for helping me dog food the v1.0 API design.

The generated Dockerfile currently looks something like this: ```Dockerfile FROM python:3.8 COPY . /app WORKDIR /app

ENV DATASETTE_SECRET 'edab49cbc5d5f6f33238f54852037e3fee710821960b73edd2ce743454182ae2' RUN pip install -U datasette datasette-auth-passwords datasette-tiddlywiki datasette-graphql RUN datasette inspect fixtures.db other.db --inspect-file inspect-data.json ENV PORT 8080 EXPOSE 8080 CMD datasette serve --host 0.0.0.0 -i fixtures.db -i other.db --cors --inspect-file inspect-data.json --metadata metadata.json --create --port $PORT /data/*.db `` This is still on Python 3.8, and it generates a pretty large image compared to theDockerfile` used for https://hub.docker.com/datasetteproject/datasette - https://github.com/simonw/datasette/blob/0.60.2/Dockerfile

Here's the code that generates it: https://github.com/simonw/datasette/blob/7d24fd405f3c60e4c852c5d746c91aa2ba23cf5b/datasette/utils/init.py#L389-L400

What I'm seeing

With default_cache_ttl = 86400, I see the following:

A table view returns Cache-control: max-age=86400:

A static asset returns no Cache-control header:

What I expected to see

I expected the static asset to return a Cache-control header indicating that this response can be cached.

Why this matters

I'm productionising a Datasette deployment right now and was looking into putting it behind a Varnish instance. I was surprised to see requests for static assets being served from Datasette rather than Varnish, this is what led me to look more closely at the response headers.

While Datasette serves those static assets pretty quickly, I don't see why Datasette should serve them. By their nature, static assets like images and JS files are very cacheable, so it should be easy to serve them from a cache like Varnish.

(Note that Varnish can easily be configured to override this header, enabling caching for static assets. But it would be better if this override was not necessary.)

Discussion

It seems clear to me that serving static assets without a Cache-control header is not ideal.

I see two options here:

A. Static assets use the same logic as table / SQL views to set the Cache-control header based on default_cache_ttl. B. An additional setting for static assets is introduced (default_static_cache_ttl, say).

Errors like this one:

https://github.com/simonw/datasette/pull/927/checks?check_run_id=973559696

2020-08-11T23:36:39.8801334Z =================================== FAILURES =================================== 2020-08-11T23:36:39.8802411Z _________________________________ test_install _________________________________ 2020-08-11T23:36:39.8803242Z 2020-08-11T23:36:39.8804935Z thing = <module 'pip._internal.cli' from '/opt/hostedtoolcache/Python/3.8.5/x64/lib/python3.8/site-packages/pip/_internal/cli/__init__.py'> 2020-08-11T23:36:39.8806663Z comp = 'main', import_path = 'pip._internal.cli.main' 2020-08-11T23:36:39.8807696Z 2020-08-11T23:36:39.8808728Z def _dot_lookup(thing, comp, import_path): 2020-08-11T23:36:39.8810573Z try: 2020-08-11T23:36:39.8812262Z > return getattr(thing, comp) 2020-08-11T23:36:39.8817136Z E AttributeError: module 'pip._internal.cli' has no attribute 'main' 2020-08-11T23:36:39.8843043Z 2020-08-11T23:36:39.8855951Z /opt/hostedtoolcache/Python/3.8.5/x64/lib/python3.8/unittest/mock.py:1215: AttributeError 2020-08-11T23:36:39.8873372Z 2020-08-11T23:36:39.8877803Z During handling of the above exception, another exception occurred: 2020-08-11T23:36:39.8906532Z 2020-08-11T23:36:39.8925767Z def get_src_prefix(): 2020-08-11T23:36:39.8928277Z # type: () -> str 2020-08-11T23:36:39.8930068Z if running_under_virtualenv(): 2020-08-11T23:36:39.8949721Z src_prefix = os.path.join(sys.prefix, 'src') 2020-08-11T23:36:39.8951813Z else: 2020-08-11T23:36:39.8969014Z # FIXME: keep src in cwd for now (it is not a temporary folder) 2020-08-11T23:36:39.9012110Z try: 2020-08-11T23:36:39.9013489Z > src_prefix = os.path.join(os.getcwd(), 'src') 2020-08-11T23:36:39.9014538Z E FileNotFoundError: [Errno 2] No such file or directory 2020-08-11T23:36:39.9016122Z 2020-08-11T23:36:39.9017617Z /opt/hostedtoolcache/Python/3.8.5/x64/lib/python3.8/site-packages/pip/_internal/locations.py:50: FileNotFoundError 2020-08-11T23:36:39.9018802Z 2020-08-11T23:36:39.9020070Z During handling of the above exception, another exception occurred: 2020-08-11T23:36:39.9020930Z 2020-08-11T23:36:39.9022275Z args = (), keywargs = {} 2020-08-11T23:36:39.9023183Z 2020-08-11T23:36:39.9024077Z @wraps(func) 2020-08-11T23:36:39.9024984Z def patched(*args, **keywargs): 2020-08-11T23:36:39.9028770Z > with self.decoration_helper(patched, 2020-08-11T23:36:39.9031861Z args, 2020-08-11T23:36:39.9038358Z keywargs) as (newargs, newkeywargs): 2020-08-11T23:36:39.9039654Z 2020-08-11T23:36:39.9040566Z /opt/hostedtoolcache/Python/3.8.5/x64/lib/python3.8/unittest/mock.py:1322: 2020-08-11T23:36:39.9041492Z _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

Inspired by this article: https://cldellow.com/2018/06/22/sqlite-parquet-vtable.html#sqlite-database-indexed--squashed

https://en.wikipedia.org/wiki/SquashFS is "a compressed read-only file system for Linux" - which means it could be a really nice fit for Datasette and its read-only SQLite databases.

It would be interesting to explore a Dockerfile recipe that used SquashFS to compress the SQLite database file that was bundled up by datasette package and friends.

Originally explored in https://github.com/simonw/datasette-notebook/issues/2#issuecomment-980789406 - I wanted an efficient way to scan a list of URLs and figure out which if any of those corresponded to Datasette tables, canned queries or SQL output that could be represented as a table on a page.

It looks like a neat way to do that is with Link: header like this:

Link: http://127.0.0.1:8058/fixtures/compound_three_primary_keys.json; rel="alternate"; type="application/datasette+json"

I can put a <link href=... in the page header too.

https://github.com/simonw/datasette/commit/6aa5886379dd9017215904fb28567b80018902f9 added the --load-extension=spatialite shortcut looking for the extension in these places:

https://github.com/simonw/datasette/blob/12877d7a48e2aa28bb5e780f929a218f7265d849/datasette/utils/init.py#L56-L60

However, in the datasetteproject/datasette docker image the file is at /usr/local/lib/mod_spatialite.so.

This results in the example command here failing:

% docker run --rm -p 8001:8001 -v `pwd`:/mnt datasetteproject/datasette datasette -p 8001 -h 0.0.0.0 /mnt/data.db --load-extension=spatialite Error: Could not find SpatiaLite extension

But it does work when given an explicit path:

% docker run --rm -p 8001:8001 -v `pwd`:/mnt datasetteproject/datasette datasette -p 8001 -h 0.0.0.0 /mnt/data.db --load-extension=/usr/local/lib/mod_spatialite.so INFO: Started server process [1] INFO: Waiting for application startup. INFO: Application startup complete. INFO: Uvicorn running on http://0.0.0.0:8001 (Press CTRL+C to quit) ...

Perhaps SPATIALITE_PATHS should include /usr/local/lib/mod_spatialite.so?

https://docs.datasette.io/en/0.55/spatialite.html was written before I had tools like geojson-to-sqlite and shapefile-to-sqlite.

Found this while working on https://github.com/simonw/datasette-tiddlywiki

Then clicking on /tiddlywiki/tiddlers/%24%3A%2FDefaultTiddlers returns a 404.

I have a file named test-database (1).sqlite. When requesting the home route /, I see datasette is able to read it correctly:

However, if I click any of the links, datasette replies with: Error 404 Database not found: None

It seems the hash is crucial, as renaming the file to database (1).sqlite makes the error go away.

This lines checks for a single dash: https://github.com/simonw/datasette/blob/97fb10c17dd007a275ab743742e93e932335ad67/datasette/views/base.py#L184

``` $ datasette test-database\ (1).sqlite INFO: Started server process [68314] INFO: Waiting for application startup. INFO: Application startup complete. INFO: Uvicorn running on http://127.0.0.1:8001 (Press CTRL+C to quit) INFO: 127.0.0.1:54043 - "GET /favicon.ico HTTP/1.1" 200 OK INFO: 127.0.0.1:54043 - "GET / HTTP/1.1" 200 OK ... INFO: 127.0.0.1:54044 - "GET /favicon.ico HTTP/1.1" 200 OK INFO: 127.0.0.1:54044 - "GET /test-database (1) HTTP/1.1" 404 Not Found

Version: $ datasette --version datasette, version 0.53 ```

Updates the requirements on janus to permit the latest version.

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

https://docs.datasette.io/en/stable/sql_queries.html#named-parameters

I thought that I had seen an example of how to do this example below, but I can't seem to find it

sql select * from bib where bib.bib_record_num in (1008088,1008092)

sql select * from bib where bib.bib_record_num in (:bib_record_numbers)

https://ilsweb.cincinnatilibrary.org/collection-analysis/current_collection-204d100?sql=select%0D%0A++*%0D%0Afrom%0D%0A++bib%0D%0Awhere%0D%0A++bib.bib_record_num+in+%28%3Abib_record_numbers%29&bib_record_numbers=1008088%2C1008092

Or, maybe this isn't a fully supported feature.

The latest demo is now live at https://datasette-apache-proxy-demo.fly.dev/prefix/fixtures/sortable?_facet=pk2

Originally posted by @simonw in https://github.com/simonw/datasette/issues/1519#issuecomment-974697824

I'm going to put out 0.59.3 bugfix release with this, but I'd like to first improve the documentation on https://docs.datasette.io/en/stable/deploying.html#apache-proxy-configuration to highlight the new demo.

Datasette ASGI #272 is a big part of it... but 1.0 will generally be an indicator that Datasette is a stable platform for developers to write plugins and custom templates against. So lots to think about.

It would be great to have a sample showing how to move a single database that has a single table, to the index page. I'm trying it now, and find there is a real depth of Datasette and Python understanding that's required to be successful.

I've got all the basic jinja concepts down... variables, template control structures, template inheritance, template overrides, css, html, the --template-dir and --static arguments, etc.

But copying the table.html file to index.html doesn't work. There are undocumented functions and filters... I can figure some of them out (yay, url_builder.py and utils/init.py!) but it's a slog better handled by a much stronger Python developer.

One sample would make a world of difference. The ideal form of this documentation would be a diff between the default table.html and how that would look if essentially moved to index.html. The use case is for everyone who wants to create a public-facing website to explore a single table at the root directory. (Maybe a second bit of documentation for people who have a single database with multiple tables.)

(Hmm... might be cool to have a setting for that, where it happens automagically! If only one table, then home page is at the table level. if only one database, then home page is at the database level.... as an option.)

I suppose I could ignore this, and somehow do this in the DNS settings once I hook up Vercel to a domain name, maybe.. and remove the breadcrumbs in table.html... but for now, a documentation request in the form of a diff... for viewing a single table (or a single database) at the root.

(Actually, there's probably room for a whole expanded section on templates. Noticed some nice table metadata in one of the datasette examples, for instance... Hmm... maybe a whole library of solutions in one place... maybe a documentation hackathon! If that's of interest, of course it's a separate issue. )

For example:

• Go to https://cryptics.eigenfoo.xyz/clues/clues?_next=100 (this is the second page of results in a Datasette site)
• Search anything using the FTS search bar. For example, searching for hello will take you to https://cryptics.eigenfoo.xyz/clues/clues?_search=hello&_sort=rowid&_next=100
• A 500 Error: list index out of range is raised.

This is because the search URL includes the &_next=100 UTM parameter, carried over from where the FTS search was run. However, there isn't a second page in the search results, so a list index out of range error is raised. You can confirm that removing this UTM parameter from the URL returns the appropriate search results.

The FTS search request should strip any _next UTM parameter.

bash datasette, version 0.58.1 sqlite-utils, version 3.17

I’m currently operating under the assumption that it’s safe to allow arbitrary SQL statements because we are dealing with an immutable database. But this might not be the case - there are some pretty weird SQLite language extensions (ATTACH, PRAGMA etc) and I’m not certain they cannot be used to break things in a way that would affect future requests to the API.

Solution: provide a “safe mode” option which disables the ?sql= mechanism. This still leaves the URL filter lookups, so I need to make sure that those are “safe”.

In the future I may also implement a whitelist option where datasets can be configured to only allow specific filters against specific columns.

Not currently covered here: https://docs.datasette.io/en/stable/internals.html#await-db-execute-sql

I'm working on a project with some HUGE (400+ lines of SQL) canned queries right now.

Any time you land on the canned query page you have to scroll down a long distance to get to the results!

Would be useful to be able to default to https://latest.datasette.io/fixtures/magic_parameters?_hide_sql=1 without needing the parameter.

This PR changes the main Dockerfile to use ubuntu:20.10 as base image instead of python:3.9.2-slim-buster (itself based on debian:buster-slim).

The Dockerfile is essentially the one from https://github.com/simonw/datasette/issues/1249#issuecomment-803698983 with some additional cleanups to slim it down.

This fixes a couple of issues: 1. The SQLite version in Debian Buster (2.6.0) doesn't support generated columns 2. Installing SpatiaLite from the Debian sid repositories has the side effect of also installing updates to libc and libstdc++ from sid.

As a bonus, the Docker image becomes smaller:

$ docker image ls REPOSITORY TAG IMAGE ID CREATED SIZE datasette 0.56-ubuntu f7aca255140a 5 hours ago 212MB datasetteproject/datasette 0.56 efb3b282f390 13 days ago 258MB

Reproduction of the first issue

``` $ curl -O https://latest.datasette.io/fixtures.db % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 260k 0 260k 0 0 489k 0 --:--:-- --:--:-- --:--:-- 489k

$ docker run -v pwd:/mnt datasetteproject/datasette:0.56 datasette /mnt/fixtures.db Traceback (most recent call last): File "/usr/local/bin/datasette", line 8, in <module> sys.exit(cli()) File "/usr/local/lib/python3.9/site-packages/click/core.py", line 829, in call return self.main(args, kwargs) File "/usr/local/lib/python3.9/site-packages/click/core.py", line 782, in main rv = self.invoke(ctx) File "/usr/local/lib/python3.9/site-packages/click/core.py", line 1259, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/usr/local/lib/python3.9/site-packages/click/core.py", line 1066, in invoke return ctx.invoke(self.callback, ctx.params) File "/usr/local/lib/python3.9/site-packages/click/core.py", line 610, in invoke return callback(args, kwargs) File "/usr/local/lib/python3.9/site-packages/datasette/cli.py", line 544, in serve asyncio.get_event_loop().run_until_complete(check_databases(ds)) File "/usr/local/lib/python3.9/asyncio/base_events.py", line 642, in run_until_complete return future.result() File "/usr/local/lib/python3.9/site-packages/datasette/cli.py", line 584, in check_databases await database.execute_fn(check_connection) File "/usr/local/lib/python3.9/site-packages/datasette/database.py", line 155, in execute_fn return await asyncio.get_event_loop().run_in_executor( File "/usr/local/lib/python3.9/concurrent/futures/thread.py", line 52, in run result = self.fn(*self.args, self.kwargs) File "/usr/local/lib/python3.9/site-packages/datasette/database.py", line 153, in in_thread return fn(conn) File "/usr/local/lib/python3.9/site-packages/datasette/utils/init.py", line 892, in check_connection for r in conn.execute( sqlite3.DatabaseError: malformed database schema (generated_columns) - near "AS": syntax error ```

Here is the SQLite version:

`` $ docker run -vpwd`:/mnt -it datasetteproject/datasette:0.56 /bin/bash root@d9220d3b95dd:/# python3 Python 3.9.2 (default, Mar 27 2021, 02:50:26) [GCC 8.3.0] on linux Type "help", "copyright", "credits" or "license" for more information.

import sqlite3 sqlite3.version '2.6.0' ```

Reproduction of the second issue

$ docker build . -t datasette --build-arg VERSION=0.55 [...snip...] The following packages will be upgraded: libc-bin libc6 libstdc++6 [...snip...] Unpacking libc6:amd64 (2.31-11) over (2.28-10) ... [...snip...] Unpacking libstdc++6:amd64 (10.2.1-6) over (8.3.0-6) ... [...snip...]

Both libc and libstdc++ are backwards compatible, so the image still works, but it will result in a combination of libraries and Python versions that exists only in the Datasette image, so it's likely untested. In addition, since Debian sid is an always-changing rolling-release, the versions of libc, libstdc++, Spatialite, and their dependencies change frequently, so the library versions in the Datasette image will depend on the day when it was built.

I just noticed something that could make for a huge performance improvement in faceting.

The default query used by Datasette when faceting looks like this: sql select country_long, count(*) from ( select * from [global-power-plants] order by rowid ) where country_long is not null group by country_long order by count(*) desc Here it takes 53ms: https://global-power-plants.datasettes.com/global-power-plants?sql=select%0D%0A++country_long%2C%0D%0A++count%28%29%0D%0Afrom+%28%0D%0A++select++from+%5Bglobal-power-plants%5D+order+by+rowid%0D%0A%29%0D%0Awhere%0D%0A++country_long+is+not+null%0D%0Agroup+by%0D%0A++country_long%0D%0Aorder+by%0D%0A++count%28*%29+desc

Note that there's a order by rowid in there which isn't necessary - the order on that inner query doesn't matter since we're grouping and counting.

I had assumed SQLite would optimize this away - but it turns out it doesn't! Consider this version of the query, with that pointless order by removed: select country_long, count(*) from ( select * from [global-power-plants] ) where country_long is not null group by country_long order by count(*) desc https://global-power-plants.datasettes.com/global-power-plants?sql=select%0D%0A++country_long%2C%0D%0A++count%28%29%0D%0Afrom+%28%0D%0A++select++from+%5Bglobal-power-plants%5D%0D%0A%29%0D%0Awhere%0D%0A++country_long+is+not+null%0D%0Agroup+by%0D%0A++country_long%0D%0Aorder+by%0D%0A++count%28*%29+desc runs in 7.2ms!

I tried this optimization on a table with 2.5m rows in it - without the optimization it took 5 seconds, with the optimization it took 450ms. So this is a very significant improvement!

Refs #511

Fixes https://github.com/simonw/datasette/issues/1129

e.g. in https://github.com/simonw/datasette/runs/2754772233 - this is an intermittent error: ``` _ ERROR at setup of testhook_register_routes_render_message __ [gw0] linux -- Python 3.8.10 /opt/hostedtoolcache/Python/3.8.10/x64/bin/python

tmpdir = local('/tmp/pytest-of-runner/pytest-0/popen-gw0/test_hook_register_routes_rend0') request = <SubRequest 'restore_working_directory' for \<Function test_hook_register_routes_render_message>>

@pytest.fixture
def restore_working_directory(tmpdir, request):

  previous_cwd = os.getcwd()

E FileNotFoundError: [Errno 2] No such file or directory ```

Refs #1305

It looks like all I need to do to ship an alpha version to Docker Hub is NOT point the latest tag at it after it goes live: https://github.com/simonw/datasette/blob/1a8972f9c012cd22b088c6b70661a9c3d3847853/.github/workflows/publish.yml#L75-L77

Originally posted by @simonw in https://github.com/simonw/datasette/issues/1319#issuecomment-849780481

The datasette base Docker image is super convenient, but there's one problem: if any of the plugins you install require additional system dependencies (e.g., xz, git, curl) then any attempt to use apt in said Dockerfile results in an explosion:

``` $ docker-compose build Building server [+] Building 9.9s (7/9) => [internal] load build definition from Dockerfile 0.0s => => transferring dockerfile: 666B 0.0s => [internal] load .dockerignore 0.0s => => transferring context: 34B 0.0s => [internal] load metadata for docker.io/datasetteproject/datasette:latest 0.6s => [base 1/4] FROM docker.io/datasetteproject/datasette@sha256:2250d0fbe57b1d615a8d6df0c9d43deb9533532e00bac68854773d8ff8dcf00a 0.0s => [internal] load build context 1.8s => => transferring context: 2.44MB 1.8s => CACHED [base 2/4] WORKDIR /datasette 0.0s => ERROR [base 3/4] RUN apt-get update && apt-get install --no-install-recommends -y git ssh curl xz-utils 9.2s

[base 3/4] RUN apt-get update && apt-get install --no-install-recommends -y git ssh curl xz-utils:

6 0.446 Get:1 http://security.debian.org/debian-security buster/updates InRelease [65.4 kB]

6 0.449 Get:2 http://deb.debian.org/debian buster InRelease [121 kB]

6 0.459 Get:3 http://httpredir.debian.org/debian sid InRelease [157 kB]

6 0.784 Get:4 http://deb.debian.org/debian buster-updates InRelease [51.9 kB]

6 0.790 Get:5 http://httpredir.debian.org/debian sid/main amd64 Packages [8626 kB]

6 1.003 Get:6 http://deb.debian.org/debian buster/main amd64 Packages [7907 kB]

6 1.180 Get:7 http://security.debian.org/debian-security buster/updates/main amd64 Packages [286 kB]

6 7.095 Get:8 http://deb.debian.org/debian buster-updates/main amd64 Packages [10.9 kB]

6 8.058 Fetched 17.2 MB in 8s (2243 kB/s)

6 8.058 Reading package lists...

6 9.166 E: flAbsPath on /var/lib/dpkg/status failed - realpath (2: No such file or directory)

6 9.166 E: Could not open file - open (2: No such file or directory)

6 9.166 E: Problem opening

6 9.166 E: The package lists or status file could not be parsed or opened.

```

The problem seems to be from completely wiping out /var/lib/dpkg in the upstream Dockerfile:

https://github.com/simonw/datasette/blob/1b697539f5b53cec3fe13c0f4ada13ba655c88c7/Dockerfile#L18

I've tested without removing the directory and apt works as expected.

https://nhs-england-hospitals.now.sh

and an associated map visualisation:

http://run.plnkr.co/preview/cj9zlf1qc0003414y90ajkwpk/

Datasette is wonderful!

Working on my PR i noticed that tests are very slow.

The plain pytest run took about 37 minutes for me. However i could shave of about 10 minutes from that if i used pytest-xdist to parallelize execution. pytest -n 8 is run only in 28 minutes on my machine.

I can create a PR to mention that in your documentation. This will be a simple change to add pytest-xdist to requirements and change a command to run pytest in documentation.

Does that make sense to you?

After a bit more investigation it looks like python-xdist is not an answer. It creates a race condition for tests that try to clead temp dir before run.

Profiling shows that most time is spent on conn.executescript(TABLES) in make_app_client function. Which makes sense.

Perhaps the better approach would be look at the app_client fixture which is already session scoped, but not used by all test cases. And/or use conn = sqlite3.connect(":memory:") which is much faster. And/or truncate tables after each TC instead of deleting the file and re-creating them.

I can take a look which is the best approach if you give the go-ahead.

Currently throws an ugly error message: (datasette-graphql) datasette-graphql % datasette fivethirtyeight.db -p 80094 INFO: Started server process [45497] INFO: Waiting for application startup. INFO: Application startup complete. Traceback (most recent call last): File "/Users/simon/.local/share/virtualenvs/datasette-graphql-n1OSJCS8/bin/datasette", line 8, in <module> sys.exit(cli()) ... server = await loop.create_server( File "/Users/simon/.pyenv/versions/3.8.2/lib/python3.8/asyncio/base_events.py", line 1461, in create_server sock.bind(sa) OverflowError: bind(): port must be 0-65535.

Hi, If I run

docker run -p 8001:8001 -v `pwd`:/mnt \ 1 ↵ datasetteproject/datasette \ datasette -p 8001 -h 0.0.0.0 fixtures.db

I have

Error: Invalid value for '[FILES]...': Path 'fixtures.db' does not exist.

If I run test -f fixtures.db && echo "it exists." I have it exists..

What's my error?

Thank you

It uses view_name of database at the moment which isn't as useful.

• compact dict and set building
• remove redundant parentheses
• simplify chained conditions
• change method name to lowercase
• use triple double quotes for docstrings

please feel free to accept/reject any of these independent commits

Hi,

I've been experimenting with SQLite reading from huge datasets using this excellent Parquet extension from @cldellow. https://cldellow.com/2018/06/22/sqlite-parquet-vtable.html https://github.com/cldellow/sqlite-parquet-vtable

This works really well, but I was keen to see if I could combine datasette with this. Having previously experimented with the spatialite extension I knew that datasette supports loading extensions in the underlying sqlite instance. However I hit a blocker as the current design only allows SELECT statements to be executed and so I am unable to execute the crucial

CREATE VIRTUAL TABLE .........

command that is required to load the data from the parquet file into the table.

It seems like this would be a simple-ish change, but I don't know enough about the architecture of datasette to start implementing this myself? Could this be done as a datasette plugin? or would this require more fundamental changes at initialisation time?

My thoughts are that something at init time could detect that the user was loading a .parquet file and then switch to a mode were it loads that via the "CREATE VIRTUAL TABLE..." rather than loading the .db file in the default case??

I'm happy to contribute code and testing, I just need some pointers on the best approach.

Thanks Darren

With the current configuration Prettier seems to be installed on every run - which can been seen from the output:

npx: installed 1 in 5.166s

Prettier isn't explicitly being installed (it's surprising that actually installing the dependencies isn't included in the actions/cache docs) but it turns out that npx will automatically install the package for the specified command (it actually guesses the package name from the name of the command). I'm not sure where Prettier ends up being installed but it doesn't appear to be in ~/.npm according to the post-cache output (or ./node_modules when I tested locally):

Cache hit occurred on the primary key Linux-npm-565329898f77080e58b14d45cf816ab94877e6f2ece9d395c369c533548a7ee7, not saving cache.

I think there are a couple of approaches to tackling this, you could manually install/cache Prettier within the action, or add a package.json with Prettier. I would go with the latter because it's a more standard and maintainable approach and it will also ensure that, along with CI, anyone working on the project will run the same version of Prettier (you'll also get Dependabot JavaScript updates).

I've tested the package.json approach on a branch and am happy to turn it into a pull request if you fancy.

e.g. I should be able to do this:

datasette App/data.db Other_App/data.db

This currently errors because you can't have two databases taking the /data URL path.

Instead, how about in this particular case assigning the second database /data-1?

Split out from #460 - in order to support large numbers of connected databases the homepage needs to be paginated.

Hi Simon! Maybe it's just me, but when using _searchmode=raw (trying to enable wildcard-searching) in combination with the "_search_COLUMN"-table argument, I get a list index out of range error. When combining with the simpler "_search"-argument everything works, including wildcard-seaches.. Here's the traceback:

``` Traceback (most recent call last): File "/Users/cjk/.local/share/virtualenvs/minutes-jMDZ8Ssk/lib/python3.7/site-packages/datasette/utils/asgi.py", line 122, in route_path return await view(new_scope, receive, send) File "/Users/cjk/.local/share/virtualenvs/minutes-jMDZ8Ssk/lib/python3.7/site-packages/datasette/utils/asgi.py", line 196, in view request, scope["url_route"]["kwargs"] File "/Users/cjk/.local/share/virtualenvs/minutes-jMDZ8Ssk/lib/python3.7/site-packages/datasette/views/base.py", line 204, in get request, database, hash, correct_hash_provided, kwargs File "/Users/cjk/.local/share/virtualenvs/minutes-jMDZ8Ssk/lib/python3.7/site-packages/datasette/views/base.py", line 342, in view_get request, database, hash, **kwargs File "/Users/cjk/.local/share/virtualenvs/minutes-jMDZ8Ssk/lib/python3.7/site-packages/datasette/views/table.py", line 393, in data search_col = key.split("search", 1)[1] IndexError: list index out of range

```

One of the nicest qualities of SQLite as a data format is that you get a single file which you can then backup or share with other people.

Datasette breaks this a little once you start including custom metadata.json or template files and CSS.

It would be cool if there was an optional mechanism for baking that extra configuration into the SQLite file itself. That way entire datasette mini-applications (including canned queries and custom HTML and CSS) could be constructed as single .db files.

Since datasette configuration is all file-based, one way to achieve that would be to support a "datasette_files" table which, if present is used to search for file contents by path.

This is inline with the philosophy described by https://www.sqlite.org/appfileformat.html

https://cloud.google.com/run/quotas lists the maximum response size as 32MB.

I spotted a bug where attempting to download a database file larger than that from a Cloud Run deployment (in this case it was https://github-to-sqlite.dogsheep.net/github.db after I accidentally increased the size of that database) returned a 500 error because of this.

I'd like to redirect https://docs.datasette.io/en/stable/config.html to a new https://docs.datasette.io/en/stable/settings.html page too. I can use https://docs.readthedocs.io/en/stable/user-defined-redirects.html for that.

Originally posted by @simonw in https://github.com/simonw/datasette/issues/1105#issuecomment-733190827

Originally posted by @simonw in https://github.com/simonw/datasette/issues/1033#issuecomment-714681365

Refs #1023

• [x] Remove the /-/...blob/... route I added in #1040 in place of the new .blob renderer URLs
• [x] Link to new .blob download links on the arbitrary query page (using _blob_hash=...) - plus tests for this

Closes #1050, Closes #1051

To handle packages that require Javascript state setting prior to loading a package (eg thebelab, provide a template block before the URLs are loaded.

Hi, thanks for datasette!

This PR adds the LICENSE to source distributions, which seems the norm for Apache-2.0 stuff.

I noticed the 0.50.2 sdist doesn't ship LICENSE, but the 0.5.2 whl does, so I'm assuming the intent is to ship... and it's a one-liner!

Motivation:

It might be a bit of a slog, but I'm looking to see about getting datasette (and friends!) available on conda-forge. There are a few missing upstreams (asgi-csrf, python-basecov, mergedeep) and some of the plugins don't even appear to have tarballs (just whl!), but the little stuff like licenses are nice to get out handled upstream vs separately grabbing them.

I just upgraded from 0.49 to 0.50.1 and found that the links on column headers are broken.

If I inspect the source, they have a leading "//" (without host or port) rather than including base_url like other links on the page do. The links in the "gears" menu for each column do work.

I don't have custom templates for my project.

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?

This is a request for a "convenience" feature, and only a nice to have. It's based on seeing this feature in several little command line hypertext server apps.

If you run, for example:

datasette.exe serve --open "mydb.s3db"

I would like it if default browser is launched, at the URL that is being served.

The angular cli does this, for example

ng serve <project> --open #see https://angular.io/cli/serve

...as does my usual mini web server of choice when inspecting local static files....

npx http-server -o # see https://www.npmjs.com/package/http-server

Just a tiny thing. Love your work!

https://github.com/simonw/datasette/blob/master/docs/ecosystem.rst

Steps to reproduce: visit https://2a4b892.datasette.io/fixtures/roadside_attractions?_facet_m2m=attraction_characteristic and click "Apply"

Result is a 500: no such column: attraction_characteristic

The error occurs because of this hidden HTML input:

<input type="hidden" name="_facet" value="attraction_characteristic">

This should be:

<input type="hidden" name="_facet_m2m" value="attraction_characteristic">

The HTML form for a read-only canned query includes the hidden CSRF token field added in #798 for writable canned queries (#698).

This means that submitting those read-only forms exposes the CSRF token in the URL - for example on https://latest.datasette.io/fixtures/neighborhood_search submitting the form took me to:

https://latest.datasette.io/fixtures/neighborhood_search?text=down&csrftoken=IlFubnoxVVpLU1NGT3NMVUoi.HbOPd2YH_epQmp8f_aAt0s-MxtU

This token could potentially leak to an attacker if the resulting page has a link to an external site on it and the user clicks the link, since the token would be exposed in the referral logs.

Is there any reason NOT to apply white-space: pre-wrap to the contents of all table cells in Datasette?

The default display mechanism of HTML (stripping leading/trailing slashes and collapsing all other whitespace) doesn't really make sense for displaying the kind of data that Datasette works with.

Potential fix for https://github.com/simonw/datasette/issues/859.

Disabling table counts for hidden tables speeds up database page quite a bit. In my setup it reduced load time by 2/3 (~300 -> ~90ms)

Need a cookie clearing mechanism and a way to show that you are logged in.

datasette-auth-github had a solution for this that can be pulled into core.

The .coverage file generated by running pytest-cov is now a SQLite database!

I could do something interesting with this. Maybe after each test run for a new commit I could store that database file somewhere?

Lots of interesting challenges here.

I got a change into coveragepy last year which helps make the custom SQL functions available for doing fun things in Datasette: https://github.com/nedbat/coveragepy/issues/868

Bigger challenge: if I have a DB file for every commit, that's hundreds (potentially thousands) of DB files. Datasette isn't designed to handle thousands of files like that.

So, do I figure out how to have Datasette open a file on-command for just a single request? Or, an easier option, do I copy data from those files into a single database with a modified schema to include the commit hash in each table row?

(Following on from #841 and #844)

https://github.com/simonw/datasette-auth-github/issues/62 will work for this.