issue_comments

This feels quite nice:

I want to package together all of the extras that are needed for the HTML format. A few options for doing that:

• Introduce ?_extra=_html where the leading underscore indicates that this is a "bundle" of extras, then define a bundle that's everything needed for the HTML renderer
• Have some other mechanism whereby different renderers can request a bundle of extras.

I'm leaning towards the first option. I'll try that and see what it looks like.

To get this unblocked, I'm going to allow myself to pass non-JSON-serializable objects to the HTML template version of things. If I can get that working (and get the existing tests to pass) I can consider a later change that makes those JSON serializable - or admit that it's OK for the templates to have non-JSON data passed to them and figure out how best to document those variables independently from the JSON documentation.

The reason for that Row thing is that it allows custom templates that do things like this:

https://docs.datasette.io/en/stable/changelog.html#easier-custom-templates-for-table-rows

html+jinja {% for row in display_rows %} <div> <h2>{{ row["title"] }}</h2> <p>{{ row["description"] }}<lp> <p>Category: {{ row.display("category_id") }}</p> </div> {% endfor %} Is that a good design? the .display() thing feels weird - I wonder if anyone has ever actually used that.

It's documented here: https://docs.datasette.io/en/0.64.2/custom_templates.html#custom-templates

If you want to output the rendered HTML version of a column, including any links to foreign keys, you can use {{ row.display("column_name") }}.

I can't see any examples of anyone using it in this code search: https://cs.github.com/?scopeName=All+repos&scope=&q=datasette+row.display

It is however useful to have some kind of abstraction layer here that insulates the SQLite Row object, since having an extra layer will help if Datasette ever grows support for alternative database backends such as DuckDB or PostgreSQL.

Aside idea: it might be interesting if there were "lazy" template variables available in the context: things that are not actually executed unless a template author requests them.

Imagine if metadata was a lazy template reference, such that custom templates that don't display any metadata don't trigger it to be resolved (which might involve additional database queries some day).

Figuring out what to do with display_columns_and_rows() is hard. That returns rows as this special kind of object, which is designed to be accessed from the HTML templates:

https://github.com/simonw/datasette/blob/96e94f9b7b2db53865e61390bcce6761727f26d8/datasette/views/table.py#L45-L71

For the HTML version, I need to decide where all of the stuff that happens in async def extra_template() is going to live.

I think it's another one of those extra functions, triggered for ?_extra=context.

https://github.com/simonw/datasette/blob/96e94f9b7b2db53865e61390bcce6761727f26d8/datasette/views/table.py#L813-L912

The ease with which I added that ?_extra=query feature in https://github.com/simonw/datasette/pull/1999/commits/96e94f9b7b2db53865e61390bcce6761727f26d8 made me feel really confident that this architecture is going in the right direction.

```diff diff --git a/datasette/views/table.py b/datasette/views/table.py index 8d3bb2c930..3e1db9c85f 100644 --- a/datasette/views/table.py +++ b/datasette/views/table.py @@ -1913,6 +1913,13 @@ async def extra_request(): "args": request.args._data, }

• async def extra_query():
• "Details of the underlying SQL query"
• return {
• "sql": sql,
• "params": params,
• } + async def extra_extras(): "Available ?_extra= blocks" return { @@ -1938,6 +1945,7 @@ async def extra_extras(): extra_primary_keys, extra_debug, extra_request,
• extra_query, extra_extras, ) ```

Just noticed that _json=colname is not working, and that's because it's handled by the renderer here:

https://github.com/simonw/datasette/blob/56b0758a5fbf85d01ff80a40c9b028469d7bb65f/datasette/renderer.py#L29-L40

But that's not currently being called by my new code.

I'm going to hold off on that refactor until later, when I have tests to show me if the refactor works or not.

So maybe I can refactor it to look a bit more like this:

https://github.com/simonw/datasette/blob/db1a88f4e17a1f50bdaa681e8beddb2276503e7c/datasette/views/table.py#L1602-L1604

One thing that's useful here is that is_view is handled early, like this:

https://github.com/simonw/datasette/blob/db1a88f4e17a1f50bdaa681e8beddb2276503e7c/datasette/views/table.py#L466-L472

So if I omit the is_view bit from the extracted function I can simplify more.

I'd really like to extract this ugly logic out into a helper function:

https://github.com/simonw/datasette/blob/db1a88f4e17a1f50bdaa681e8beddb2276503e7c/datasette/views/table.py#L1617-L1684

I copied it in and asked ChatGPT to "List all of the variable that are either modified or assigned to by the above code":

Modified variables:

offset
where_clauses
params
order_by

Assigned variables:

sort_value
next_by_pk_clauses
order_by (when sort or sort_desc is not None)

Then I asked which variables were used as inputs, and argued with it a bit about whether it should be counting functions. Eventually got to this:

My apologies for the oversight. Here are the variables needed as input by the above code, excluding any functions:

_next
is_view
sort
sort_desc
use_rowid
pks
order_by

Note that use_rowid is actually defined earlier in terms of two of those other variables: https://github.com/simonw/datasette/blob/db1a88f4e17a1f50bdaa681e8beddb2276503e7c/datasette/views/table.py#L1540

This fix is released in 0.64.2 https://docs.datasette.io/en/stable/changelog.html#v0-64-2

Here's the https://latest.datasette.io/ deployment that just went out, further demonstrating that this change is working correctly:

Got the same failure again for a recent commit: https://github.com/simonw/datasette/actions/runs/4368239376/jobs/7640567282

It's this test here:

https://github.com/simonw/datasette/blob/1ad92a1d87d79084ebe524ed186c900ff042328c/tests/test_cli.py#L181-L189

Added in: - #2033

Instead of using isolated_filesystem() I could use a tmpdir fixture instead.

https://console.cloud.google.com/run/detail/us-central1/new-service/revisions?project=datasette-222320 confirms that the image deployed is:

Compared to https://console.cloud.google.com/run/detail/us-central1/datasette-io/revisions?project=datasette-222320 which shows that datasette.io is running:

Testing this manually:

``` % datasette publish cloudrun content.db --service new-service Creating temporary tarball archive of 2 file(s) totalling 13.8 MiB before compression. Uploading tarball of [.] to [gs://datasette-222320_cloudbuild/source/1678306859.271661-805303f364144b6094cc9c8532ab5133.tgz] Created [https://cloudbuild.googleapis.com/v1/projects/datasette-222320/locations/global/builds/290f41a4-e29a-443c-a1e5-c54513c6143d]. Logs are available at [ https://console.cloud.google.com/cloud-build/builds/290f41a4-e29a-443c-a1e5-c54513c6143d?project=99025868001 ]. ---- REMOTE BUILD OUTPUT ---- starting build "290f41a4-e29a-443c-a1e5-c54513c6143d"

FETCHSOURCE Fetching storage object: gs://datasette-222320_cloudbuild/source/1678306859.271661-805303f364144b6094cc9c8532ab5133.tgz#1678306862810483 Copying gs://datasette-222320_cloudbuild/source/1678306859.271661-805303f364144b6094cc9c8532ab5133.tgz#1678306862810483... / [1 files][ 3.9 MiB/ 3.9 MiB]
Operation completed over 1 objects/3.9 MiB. BUILD Already have image (with digest): gcr.io/cloud-builders/docker Sending build context to Docker daemon 14.52MB Step 1/9 : FROM python:3.11.0-slim-bullseye ... Installing collected packages: rfc3986, typing-extensions, sniffio, PyYAML, python-multipart, pluggy, pint, mergedeep, MarkupSafe, itsdangerous, idna, hupper, h11, click, certifi, asgiref, aiofiles, uvicorn, Jinja2, janus, click-default-group-wheel, asgi-csrf, anyio, httpcore, httpx, datasette Successfully installed Jinja2-3.1.2 MarkupSafe-2.1.2 PyYAML-6.0 aiofiles-23.1.0 anyio-3.6.2 asgi-csrf-0.9 asgiref-3.6.0 certifi-2022.12.7 click-8.1.3 click-default-group-wheel-1.2.2 datasette-0.64.1 h11-0.14.0 httpcore-0.16.3 httpx-0.23.3 hupper-1.11 idna-3.4 itsdangerous-2.1.2 janus-1.0.0 mergedeep-1.3.4 pint-0.20.1 pluggy-1.0.0 python-multipart-0.0.6 rfc3986-1.5.0 sniffio-1.3.0 typing-extensions-4.5.0 uvicorn-0.20.0 WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv

[notice] A new release of pip available: 22.3 -> 23.0.1 [notice] To update, run: pip install --upgrade pip Removing intermediate container 8ccebfebebc9 ---> b972c85b38bb ... Successfully built 606b7c286d7f Successfully tagged gcr.io/datasette-222320/datasette-new-service:latest PUSH Pushing gcr.io/datasette-222320/datasette-new-service The push refers to repository [gcr.io/datasette-222320/datasette-new-service] 667b1dc69e5e: Preparing ... d8ddfcff216f: Pushed latest: digest: sha256:452daffb2d3d7a8579c2ab39854be285155252c9428b4c1c50caac6a3a269e3f size: 2004 DONE

ID CREATE_TIME DURATION SOURCE IMAGES STATUS 290f41a4-e29a-443c-a1e5-c54513c6143d 2023-03-08T20:21:03+00:00 39S gs://datasette-222320_cloudbuild/source/1678306859.271661-805303f364144b6094cc9c8532ab5133.tgz gcr.io/datasette-222320/datasette-new-service (+1 more) SUCCESS Deploying container to Cloud Run service [new-service] in project [datasette-222320] region [us-central1] ✓ Deploying new service... Done.
✓ Creating Revision...
✓ Routing traffic...
✓ Setting IAM Policy...
Done.
Service [new-service] revision [new-service-00001-zon] has been deployed and is serving 100 percent of traffic. Service URL: https://new-service-j7hipcg4aq-uc.a.run.app ``` https://new-service-j7hipcg4aq-uc.a.run.app/ was deployed successfully.

I'm going to solve this by using the service name in that image_id instead:

python image_id = f"gcr.io/{project}/{service_name}" This is a nasty bug, so I'm going to backport it to a 0.64.2 release as well.

I think the code at fault is here:

https://github.com/simonw/datasette/blob/1ad92a1d87d79084ebe524ed186c900ff042328c/datasette/publish/cloudrun.py#L176-L182

That name ends up defaulting to datasette - so multiple different projects may end up deploying to the same image_id.

What I think happened in the datasette.io bug is that this workflow: https://github.com/simonw/simonwillisonblog-backup/blob/bfb573e96d8622ab52b22fdcd54724fe6e59fd24/.github/workflows/backup.yml and this workflow: https://github.com/simonw/datasette.io/blob/4676db5bf4a3fc9f792ee270ec0c59eb902cd2c3/.github/workflows/deploy.yml both happened to run at the exact same time.

And so the image that was pushed to gcr.io/datasette-222320/datasette:latest by the simonw/simonwillisonblog-backup action was then deployed by the simonw/datasette.io/ action, which broke the site.

+1, I have been wishing for this feature (also for use with template-sql). It was requested before here #1304.

I'm trying to get http://127.0.0.1:8001/fixtures/compound_three_primary_keys?_next=a,d,v to return the correct results.

Pushed that prototype to a branch: https://github.com/simonw/datasette/commit/0fe844e9adb006a0138e83102ced1329d9155c59 / https://github.com/simonw/datasette/compare/sql-list-parameters

I should consider the existing design of magic parameters here: https://docs.datasette.io/en/stable/sql_queries.html#magic-parameters

• _actor_*
• _header_*
• _cookie_
• _now_epoch
• _now_date_utc
• _now_datetime_utc
• _random_chars_*

Should this new id__list syntax look more like those magic parameters, or is it OK to use name__magic syntax here instead?

To implement this properly need to do the following: - Get the page to display multiple id: [ text input here ] fields such that re-submission works - Figure out how this should work for canned queries and for writable canned queries - Tests that cover queries, canned queries, writable canned queries

And a bonus feature: what if the Datasette UI layer spotted :id__list parameters and used them to add a bit of JavaScript that allowed users to click a + button next to an id form field to add another one?

Also, when a page is re-displayed for on of these queries it could potentially add an extra form field allowing people to add another value.

Though this has an annoying problem: how to tell the difference between an additional id input field that the user chose not to populate, v.s. one that is supposed to represent an empty string?

Maybe only support multiple id fields for users with JavaScript in order to avoid this problem.

Got a prototype working: ```diff diff --git a/datasette/views/database.py b/datasette/views/database.py index 8d289105..6f9d8a44 100644 --- a/datasette/views/database.py +++ b/datasette/views/database.py @@ -226,6 +226,12 @@ class QueryView(DataView): ): db = await self.ds.resolve_database(request) database = db.name + # Disallow x__list query string parameters + invalid_params = [k for k in request.args if k.endswith("__list")] + if invalid_params: + raise DatasetteError( + "Invalid query string parameters: {}".format(", ".join(invalid_params)) + ) params = {key: request.args.get(key) for key in request.args} if "sql" in params: params.pop("sql") @@ -258,6 +264,11 @@ class QueryView(DataView): for named_parameter in named_parameters if not named_parameter.startswith("_") } + # Handle any __list parameters + for named_parameter in named_parameters: + if named_parameter.endswith("__list"): + list_values = request.args.getlist(named_parameter[:-6]) + params[named_parameter] = json.dumps(list_values)

     # Set to blank string if missing from params
     for named_parameter in named_parameters:

`` This isn't yet doing the right thing on form re-submission: it breaks because it attempts to pass through the?id__list=` invalid parameter. But I did manage to get it to do this through careful editing of the URL:

That was this URL: http://127.0.0.1:8034/content?sql=select+%3Aid__list%2C*+from+releases+where+id+in+(select+value+from+json_each(%3Aid__list))&id=62642726&id=18402901&id=38714866

Also: datasette-explain may need to be updated to understand how to handle this:

ERROR: conn=<sqlite3.Connection object at 0x102834940>, sql = 'explain select * from releases where id in (select id from json_each(:id__list))', params = None: You did not supply a value for binding parameter :id__list.

Trickiest part of the implementation here is that it needs to know to output three id HTML form fields on the page, such that their values are persisted when the form is submitted a second time.

Since we are pre-1.0 it's still OK to implement a feature that disallows ?id__list= in the URL, but allows :id__list in SQL queries to reference the JSON list of parameters.

So I'm going to prototype this as the :id__list feature and see how it feels.

I'm pretty sold on this as a feature now. The main question I have is which of these options to implement:

1. ?id=1&?id=2 results in :id in the query being ["1", "2"] - no additional syntax required
2. :id in the query continues to reference just the first of those parameters - but :id__list (or some other custom syntax) instead gets ["1", "2"] - or, if the URL is ?id=1 - gets ["1"]

Actually on writing these out I realize that option 2 is the ONLY valid option. It's no good building a query that works against a JSON list if the user might pass just a single ID, ?id=1, resulting in their query breaking.

https://github.com/rclement/datasette-dashboards/issues/54 makes the excellent point that the <select multiple> default HTML widget produces this exact format of query string:

```html

`` Submitting that form with the middle two options selected navigates to:https://www.example.com/?id=32&id=15`

One variant on this idea: maybe you have to specify in your query that you want it to be the JSON list version, not the single item (first ?id= parameter version)? Maybe with syntax like this:

where id in (select value from json_each(:id__list))

Datasette would automatically pass {"id": "11", "id__list": '["11", "32", "62"]'} as arguments to the db.execute() method, if the page was called with ?id=11&id=32&id=62.

This is more explicit, though the syntax is a bit uglier (maybe there's a nicer design for this?). I also worry about ?id__list= conflicting with this, but I think that's a risk I can take - tell people not to do that, or even block ?id__list= style parameters entirely.

My current preferred solution is to lean into SQLite's JSON support.

What if the query page spotted ?id=11&id=32&id=62 and turned that into a JSON string called :id: with a value of ["11", "32", "62"]?

Note that this is still a string, not a list. This avoids a nasty problem that occurred in PHP world, where ?id[]=1&id[]=2 would result in an actual PHP array object, which often broke underlying code that had expected $_GET["id"] to be a string, not an array.

So in a query you'd be able to do this:

where id in (select value from json_each(:id))

And then call it with ?id=11&id=32&id=62.

One way to do this would be to dynamically generate the where id in (?, ?, ?) with the correct number of question marks, then feed in a list from request.args.getlist("id") - but that would require rewriting the SQL query text to add those question marks.

I managed to make it work by using nginx's 'exact match' (=) combined with 'prefix match'; that is, match explicitly on /, and redirect to /<db>/<table>, and then have the normal ProxyPath for the unadorned (prefix-matching) /.

location = / { return 302 /<db>/<table>; } location / { proxy_pass http://127.0.0.1:8001/; proxy_set_header Host $host; }