https://github.com/dogsheep/github-to-sqlite/actions/runs/4080058087/jobs/7032116511

When running datasette serve with the --reload flag, the serve command is picked up as a file argument:

$ datasette serve --reload test_db Starting monitor for PID 13574. Error: Invalid value for '[FILES]...': Path 'serve' does not exist. Press ENTER or change a file to reload.

If a 'serve' file is created it launches properly (albeit with an empty database called serve):

$ touch serve; datasette serve --reload test_db Starting monitor for PID 13628. INFO: Started server process [13628] INFO: Waiting for application startup. INFO: Application startup complete. INFO: Uvicorn running on http://127.0.0.1:8001 (Press CTRL+C to quit)

Version (running from HEAD on main):

$ datasette --version datasette, version 1.0a2

This issue appears to have existed for awhile as https://github.com/simonw/datasette/issues/1380#issuecomment-953366110 mentions the error in a different context.

I'm happy to debug and land a patch if it's welcome.

There's a ton of tools/languages that compile to SQL, which may be nice in Datasette. Some examples:

• Logica https://logica.dev
• PRQL https://prql-lang.org
• Malloy, but not sure if it works with SQLite? https://github.com/malloydata/malloy

It would be cool if plugins could extend Datasette to use these languages, in both the code editor and API usage.

A few things I'd imagine a datasette-prql or datasette-logica plugin would do:

• prql= instead of sql=
• Code editor support (syntax highlighting, autocomplete)
• Hide/show SQL

The cause of this bug: - https://github.com/simonw/datasette-export-notebook/issues/17

Is that datasette-export-notebook was consulting data["filtered_table_rows_count"] in the render output plugin function in order to show the total number of rows that would be exported.

That field is no longer available by default - the "count" field is only available if ?_extra=count was passed.

It would be useful if plugins like this could access the total count on demand, should they need to.

Given this schema: sql CREATE TABLE departments ( campus_name TEXT NOT NULL, dept_code TEXT NOT NULL, dept_name TEXT, PRIMARY KEY (campus_name, dept_code) ); CREATE TABLE courses ( course_code TEXT PRIMARY KEY, course_name TEXT, campus_name TEXT NOT NULL, dept_code TEXT NOT NULL, FOREIGN KEY (campus_name, dept_code) REFERENCES departments(campus_name, dept_code) ); The output of db["courses"].foreign_keys right now is: [ForeignKey(table='courses', column='campus_name', other_table='departments', other_column='campus_name'), ForeignKey(table='courses', column='dept_code', other_table='departments', other_column='dept_code')] Which suggests two normal foreign keys, not one compound foreign key.

Plugins can then take advantage of this pattern, for example: - https://github.com/simonw/datasette-auth-tokens/pull/8

https://discord.com/channels/823971286308356157/823971286941302908/1120705940728066080

May I add a request to the whole metadata / settings ? Allow to pass --settings path/to/settings.json instead of having to rely exclusively on directory mode to centralize settings (this would reflect the behavior of providing metadata)

Version 3.33

sqlite-utils query library.db 'select asin from audible' --fmt plain --no-headers | head -3 asin 0062804006 0062891421

https://beta.ruff.rs/docs/

Spotted this issue here: https://til.simonwillison.net/datasette/baseline

I had to do this workaround: sql create view baseline as select _key, spec, '' || json_extract(status, '$.is_baseline') as is_baseline, json_extract(status, '$.since') as baseline_since, json_extract(status, '$.support.chrome') as baseline_chrome, json_extract(status, '$.support.edge') as baseline_edge, json_extract(status, '$.support.firefox') as baseline_firefox, json_extract(status, '$.support.safari') as baseline_safari, compat_features, caniuse, usage_stats, status from [index] I think the core issue here is that, against a table, select * from x where integer_column = '1' works correctly, due to some kind of column type conversion mechanism... but this mechanism doesn't work against views.

sqlite supports these, and it would be quite nice to be able to add them with sqlite-utils.

https://www.sqlite.org/foreignkeys.html#fk_actions

I ran against a recent note with this in it:

Or just "Actions ⚙️ "

And got back:

Actions ⚙️

Pasting that into https://ftfy.vercel.app/?s=Actions+%E2%80%9A%C3%B6%C3%B4%C3%94%E2%88%8F%C3%A8+ gives this:

python s = 'Actions â\x80\x9aöôÃ\x94â\x88\x8fè' s = s.encode('latin-1') s = s.decode('utf-8') s = s.encode('macroman') s = s.decode('utf-8') print(s)

Hi @simonw

I hope you find this issue ok, the idea is provide some documentation to other users like me about how to solve this problem and save some time.

Following the instructions from the README.md I've faced this error:

bash (venv) mgreco@pop-os apple-health master* (23:44|0s) $ healthkit-to-sqlite apple_health_export/export.xml healthkit.db --xml Importing from HealthKit [------------------------------------] 0% Traceback (most recent call last): File "/home/mgreco/github/mmngreco/apple-health/venv/bin/healthkit-to-sqlite", line 33, in <module> sys.exit(load_entry_point('healthkit-to-sqlite', 'console_scripts', 'healthkit-to-sqlite')()) File "/home/mgreco/github/mmngreco/apple-health/venv/lib/python3.10/site-packages/click/core.py", line 1130, in __call__ return self.main(*args, **kwargs) File "/home/mgreco/github/mmngreco/apple-health/venv/lib/python3.10/site-packages/click/core.py", line 1055, in main rv = self.invoke(ctx) File "/home/mgreco/github/mmngreco/apple-health/venv/lib/python3.10/site-packages/click/core.py", line 1404, in invoke return ctx.invoke(self.callback, **ctx.params) File "/home/mgreco/github/mmngreco/apple-health/venv/lib/python3.10/site-packages/click/core.py", line 760, in invoke return __callback(*args, **kwargs) File "/home/mgreco/github/mmngreco/apple-health/.deps/healthkit-to-sqlite/healthkit_to_sqlite/cli.py", line 57, in cli convert_xml_to_sqlite(fp, db, progress_callback=bar.update, zipfile=zf) File "/home/mgreco/github/mmngreco/apple-health/.deps/healthkit-to-sqlite/healthkit_to_sqlite/utils.py", line 25, in convert_xml_to_sqlite for tag, el in find_all_tags( File "/home/mgreco/github/mmngreco/apple-health/.deps/healthkit-to-sqlite/healthkit_to_sqlite/utils.py", line 12, in find_all_tags for event, el in parser.read_events(): File "/home/mgreco/github/mmngreco/apple-health/venv/lib/python3.10/xml/etree/ElementTree.py", line 1324, in read_events raise event File "/home/mgreco/github/mmngreco/apple-health/venv/lib/python3.10/xml/etree/ElementTree.py", line 1296, in feed self._parser.feed(data) xml.etree.ElementTree.ParseError: syntax error: line 156, column 0

So, after debugging and searching on internet I found this useful link: https://discussions.apple.com/thread/254202523 (etresoft, the real hero). Which basically says that the xml given by the health app (healthkit version 12) has some bugs but fortunately, they can be solved with a couple of commads:

1. Uncompress the zip and move the new folder where export.xml is.

2. Create a patch.txt with the following content

   ```diff --- export.xml 2022-09-18 15:17:09.000000000 -0400 +++ export-fixed.xml 2022-09-18 16:37:08.000000000 -0400 @@ -15,6 +15,7 @@ HKCharacteristicTypeIdentifierBiologicalSex CDATA #REQUIRED HKCharacteristicTypeIdentifierBloodType CDATA #REQUIRED HKCharacteristicTypeIdentifierFitzpatrickSkinType CDATA #REQUIRED + HKCharacteristicTypeIdentifierCardioFitnessMedicationsUse CDATA #IMPLIED

   <!ELEMENT Record ((MetadataEntry|HeartRateVariabilityMetadataList)*)> <!ATTLIST Record @@ -39,7 +40,7 @@ startDate CDATA #REQUIRED endDate CDATA #REQUIRED

   -<!ELEMENT Workout ((MetadataEntry|WorkoutEvent|WorkoutRoute))> +<!ELEMENT Workout ((MetadataEntry|WorkoutEvent|WorkoutRoute|WorkoutStatistics))> <!ATTLIST Workout workoutActivityType CDATA #REQUIRED duration CDATA #IMPLIED @@ -63,7 +64,7 @@ duration CDATA #IMPLIED durationUnit CDATA #IMPLIED

   -<!ELEMENT WorkoutEvent EMPTY> +<!ELEMENT WorkoutEvent (MetadataEntry?)> <!ATTLIST WorkoutEvent type CDATA #REQUIRED date CDATA #REQUIRED @@ -79,6 +80,7 @@ minimum CDATA #IMPLIED maximum CDATA #IMPLIED sum CDATA #IMPLIED + unit CDATA #IMPLIED

   <!ELEMENT WorkoutRoute ((MetadataEntry|FileReference)*)> <!ATTLIST WorkoutRoute @@ -153,6 +155,7 @@ dateIssued CDATA #REQUIRED expirationDate CDATA #REQUIRED brand CDATA #IMPLIED +> <!ELEMENT RightEye EMPTY> <!ATTLIST RightEye sphere CDATA #IMPLIED @@ -203,13 +206,6 @@ diameter CDATA #IMPLIED diameterUnit CDATA #IMPLIED

   • device CDATA #IMPLIED -<!ELEMENT MetadataEntry EMPTY> -<!ATTLIST MetadataEntry
   • key CDATA #IMPLIED
   • value CDATA #IMPLIED -> -> ]> <HealthData> <ExportDate/> ```
   • Apply the path with the command: patch < patch.txt
   • Fix endDates with the command sed 's/startDate/endDate/2' export.xml > export-fixed.xml
   • Try again healthkit-to-sqlite export-fixed.xml healthkit.db --xml

A setting which turns on Jinja strict mode, so any templates that access undefined variables raise a hard error.

Prototype here: diff diff --git a/datasette/app.py b/datasette/app.py index 40416713..1428a3f0 100644 --- a/datasette/app.py +++ b/datasette/app.py @@ -200,6 +200,7 @@ SETTINGS = ( "Allow display of SQL trace debug information with ?_trace=1", ), Setting("base_url", "/", "Datasette URLs should use this base path"), + Setting("strict_templates", False, "Raise errors for undefined template variables"), ) _HASH_URLS_REMOVED = "The hash_urls setting has been removed, try the datasette-hashed-urls plugin instead" OBSOLETE_SETTINGS = { @@ -399,11 +400,14 @@ class Datasette: ), ] ) + env_extras = {} + if self.setting("strict_templates"): + env_extras["undefined"] = StrictUndefined self.jinja_env = Environment( loader=template_loader, autoescape=True, enable_async=True, - undefined=StrictUndefined, + **env_extras, ) self.jinja_env.filters["escape_css_string"] = escape_css_string self.jinja_env.filters["quote_plus"] = urllib.parse.quote_plus Explored this idea a bit in: - #1999

Running this script can take several hours against a large notes database.

Would be neat if it could run against just the notes that have been modified since it last ran. Could pull the max updated date and then keep on looping until it finds one modified before then.

Problem is I don't actually know what order it iterates over the notes in.

For example here:

3 corresponds to "Human Related: Other" - it would be neat to display this in this area of the page somehow.

I just realized that when I ship Datasette 1.0 there may be automated deployments out there which could deploy the 1.0 version by accident, potentially breaking any customizations that aren't compatible with the 1.0 changes.

I can hopefully help avoid that by shipping one last entry in the 0.x series that ensures datasette publish pins to <1.0 when it installs Datasette itself.

Idea came up here: https://discord.com/channels/823971286308356157/823971286941302908/1066026473003159783

I had an instance with this in metadata.yml:

yaml databases: timezones: tables: timezones: sortable_columns: - tzid When I clicked on the "Apply" button here:

It sent me to /timezones/timezones?_sort=id&id__exact=133 with the error message:

500: Cannot sort table by id

Inspired by this tweet: https://twitter.com/willmcgugan/status/1381186384510255104

While I am thinking about faqs. I’d also like to add short URLs to Rich exceptions.

I loath cryptic error messages, and I’ve created a fair few myself. In Rich I’ve tried to make them as plain English as possible. But...

would be great if every error message linked to a page that explains the error in detail and offers fixes.

I'm going to try writing the release notes first, to see if that helps unblock me.

⚠️ Any release notes in this issue are a draft, and should not be treated as the real thing ⚠️

Split from: - #1931 - #1878

This is a bit tricky because the code needs to figure out what the primary keys are for an item, and whether or not rowid should be included.

While working on this issue: - #1896

I realized that Datasette has error classes scattered around a fair bit, including some in the datasette.utils.asgi module for some reason.

I should clean these up.

Compare the following: ``` % curl -I 'https://latest.datasette.io/fixtures' HTTP/1.1 200 OK link: https://latest.datasette.io/fixtures.json; rel="alternate"; type="application/json+datasette" cache-control: max-age=5 referrer-policy: no-referrer access-control-allow-origin: * access-control-allow-headers: Authorization access-control-expose-headers: Link content-type: text/html; charset=utf-8 x-databases: _memory, _internal, fixtures, extra_database Date: Wed, 02 Feb 2022 21:55:49 GMT Server: Google Frontend Transfer-Encoding: chunked

% curl -I 'https://latest.datasette.io/'
HTTP/1.1 200 OK link: https://latest.datasette.io/.json; rel="alternate"; type="application/json+datasette" content-type: text/html; charset=utf-8 x-databases: _memory, _internal, fixtures, extra_database Date: Wed, 02 Feb 2022 21:55:52 GMT Server: Google Frontend Transfer-Encoding: chunked ```

Feedback from Discord:

hello, love the project and came for help and to point out a possible gap in the docs. starting with "getting started" and "installation" every thing looks great, but then there's a giant leap after you have it installed and running. from the user perspective of "i have a csv of set of csvs that i want to turn into a table(s), what do i do next?" --- so something like maybe a page for creating your first project should go after "installation".

• https://docs.datasette.io/en/0.62/getting_started.html
• https://docs.datasette.io/en/0.62/installation.html

I'm trying to figure out a way to get the table.extract() method to complete successfully -- I'm not sure if maybe the cause (and a possible solution) of this on Ubuntu Server 22.04 is to adjust some of the PRAGMA values within SQLite itself ... on another Linux system (PopOS), using this method on this same database appears to work just fine.

Here's the bit that's causing the error, and the resulting error output: ```python

combine these columns into 1 table "bib_properties" :

best_title

bib_level_code

mat_type

material_code

best_author

db["circ_trans"].extract( ["best_title", "bib_level_code", "mat_type", "material_code", "best_author"], table="bib_properties", fk_column="bib_properties_id" )

db["circ_trans"].extract( ["call_number"], table="call_number", fk_column="call_number_id", rename={"call_number": "value"} ) ```

```python

OperationalError Traceback (most recent call last) Input In [17], in <cell line: 7>() 1 # combine these columns into 1 table "bib_properties" : 2 # best_title 3 # bib_level_code 4 # mat_type 5 # material_code 6 # best_author ----> 7 db["circ_trans"].extract( 8 ["best_title", "bib_level_code", "mat_type", "material_code", "best_author"], 9 table="bib_properties", 10 fk_column="bib_properties_id" 11 ) 13 db["circ_trans"].extract( 14 ["call_number"], 15 table="call_number", 16 fk_column="call_number_id", 17 rename={"call_number": "value"} 18 )

File ~/jupyter/venv/lib/python3.10/site-packages/sqlite_utils/db.py:1764, in Table.extract(self, columns, table, fk_column, rename) 1761 column_order.append(c.name) 1763 # Drop the unnecessary columns and rename lookup column -> 1764 self.transform( 1765 drop=set(columns), 1766 rename={magic_lookup_column: fk_column}, 1767 column_order=column_order, 1768 ) 1770 # And add the foreign key constraint 1771 self.add_foreign_key(fk_column, table, "id")

File ~/jupyter/venv/lib/python3.10/site-packages/sqlite_utils/db.py:1526, in Table.transform(self, types, rename, drop, pk, not_null, defaults, drop_foreign_keys, column_order) 1524 with self.db.conn: 1525 for sql in sqls: -> 1526 self.db.execute(sql) 1527 # Run the foreign_key_check before we commit 1528 if pragma_foreign_keys_was_on:

File ~/jupyter/venv/lib/python3.10/site-packages/sqlite_utils/db.py:465, in Database.execute(self, sql, parameters) 463 return self.conn.execute(sql, parameters) 464 else: --> 465 return self.conn.execute(sql)

OperationalError: database or disk is full ```

This database is about 17G in total size, so I'm assuming the error is coming from the vacuum ... where i'm assuming it's maybe trying to do the temp storage in a location that doesn't have sufficient room. The disk space is more than ample on the host in question (1.8T is free in the directory where the sqlite db resides) The /tmp directory however is limited on a smaller disk associated with the OS

I'm trying to think if there's a way to set the PRAGMA temp_store or maybe if it's temp_store_directory that I'm after ... to use the same local directory of where the file is located (maybe this is a property of the version of sqlite on the system?)

```python

SET the temp file store to be a file ...

print(db.execute('PRAGMA temp_store').fetchall()) print(db.execute('PRAGMA temp_store=FILE').fetchall())

print(db.execute('PRAGMA temp_store').fetchall())

the users home directory ...

print(db.execute("PRAGMA temp_store_directory='/home/plchuser/'").fetchall()) print(db.execute("PRAGMA sqlite3_temp_directory='/home/plchuser/'").fetchall())

print(db.execute("PRAGMA temp_store_directory").fetchall()) print(db.execute("PRAGMA sqlite3_temp_directory").fetchall()) text [(1,)] [] [(1,)] [] [] [('/home/plchuser/',)] [] ```

Here's the docs on the Temporary File Storage Locations https://www.sqlite.org/tempfiles.html

I have a page templates/filer/{filer_id}.html. It uses filer_id in a sql() call to fetch data. With 0.61.1 this no longer works because the spaces in IDs isn't preserved. Instead, the escaped version is passed into the template and the id isn't present in my db.

Datasette should unescape the url component before passing them into the template.

When i hit "Apply" button to search with "_exact" for a column syntax the URL prefix is removed from the url.

And the result is:

If I add the marked row to url_builder.py it seams to work:

Motivation

• The build system for my new plugin has two output JS files, one for browsers that support ES modules, one for browsers that don't. At present, I'm only passing one of them into Datasette.
• I'd like to specify the non-es-module script as a fallback for older browsers. I don't want to load it by default, because browsers will only need one, and it's heavy, so for now I'm only supporting modern browsers.

To be able to support legacy browsers without slowing down users with modern browsers, I would like to be able to set additional HTML attributes on the tag fallback script, nomodule and defer. My injected scripts should look something like this:

```html

```

Proposal

To achieve this, I propose additional optional properties to the API accepted by the extra_js_urls hook and custom JS field the metadata.json described here.

Under this API, I'd write something like this to get the above HTML rendered in Datasette.

json { "extra_js_urls": [ { "url": "/index.my-es-module-bundle.js", "module": true, }, { "url": "/index.my-legacy-fallback-bundle.js", "nomodule": "", "defer": true } ] }

Resources

• MDN on the script tag
• There may be other properties that could be added that are potentially valuable, like async or referrerpolicy, but I don't have an immediate need for those.

Spotted this on a page with COUNTY__exact=Lee in the URL:

With COUNTY=Lee you get this instead:

I just wrote this code in a plugin and it felt like it could benefit from an abstraction: https://github.com/simonw/datasette-auth0/blob/152e6eb21e96e9b73bd9c205f9749a1297d0ef0b/datasette_auth0/init.py#L79-L92

python redirect_response = Response.redirect("/") expires_at = int(time.time()) + (24 * 60 * 60) redirect_response.set_cookie( "ds_actor", datasette.sign( { "a": profile_response.json(), "e": baseconv.base62.encode(expires_at), }, "actor", ), ) return redirect_response

Note that Datasette does already have special logic to convert parameters to integers for numeric comparisons like >:

https://github.com/simonw/datasette/blob/c4c9dbd0386e46d2bf199f0ed34e4895c98cb78c/datasette/filters.py#L203-L212

Though... it looks like there's a bug in that? It doesn't account for float values - "3.5".isdigit() return False - probably for the best, because int(3.5) would break that value anyway.

Originally posted by @simonw in https://github.com/simonw/datasette/issues/1671#issuecomment-1075432283

It would be great if you could use datasette --get to run queries that return streaming CSV data without running out of RAM.

Current implementation looks like it loads the entire result into memory first: https://github.com/simonw/datasette/blob/f78ebdc04537a6102316d6dbbf6c887565806078/datasette/cli.py#L546-L552

https://github.com/simonw/datasette/blob/40885ef24e32d91502b6b8bbad1c7376f50f2830/datasette/app.py#L297-L328

Discussed in https://github.com/simonw/datasette/discussions/1652

This is a bit of an oxymoron.

I am serving a log.txt file for a background process using the Datasette --static CLI. This is useful as I can observe a background process from the web UI to see any errors that occur (instead of spelunking the logs via docker exec/ssh etc).

I get this error, which I think is because Datasette assumes that the size of the content does not change (but appending new log lines means the content length changes).

python Traceback (most recent call last): File "/usr/local/lib/python3.9/site-packages/datasette/app.py", line 1181, in route_path response = await view(request, send) File "/usr/local/lib/python3.9/site-packages/datasette/utils/asgi.py", line 305, in inner_static await asgi_send_file(send, full_path, chunk_size=chunk_size) File "/usr/local/lib/python3.9/site-packages/datasette/utils/asgi.py", line 280, in asgi_send_file await send( File "/usr/local/lib/python3.9/site-packages/asgi_csrf.py", line 104, in wrapped_send await send(event) File "/usr/local/lib/python3.9/site-packages/uvicorn/protocols/http/h11_impl.py", line 460, in send output = self.conn.send(event) File "/usr/local/lib/python3.9/site-packages/h11/_connection.py", line 468, in send data_list = self.send_with_data_passthrough(event) File "/usr/local/lib/python3.9/site-packages/h11/_connection.py", line 501, in send_with_data_passthrough writer(event, data_list.append) File "/usr/local/lib/python3.9/site-packages/h11/_writers.py", line 58, in __call__ self.send_data(event.data, write) File "/usr/local/lib/python3.9/site-packages/h11/_writers.py", line 78, in send_data raise LocalProtocolError("Too much data for declared Content-Length") h11._util.LocalProtocolError: Too much data for declared Content-Length ERROR: Exception in ASGI application Traceback (most recent call last): File "/usr/local/lib/python3.9/site-packages/datasette/app.py", line 1181, in route_path response = await view(request, send) File "/usr/local/lib/python3.9/site-packages/datasette/utils/asgi.py", line 305, in inner_static await asgi_send_file(send, full_path, chunk_size=chunk_size) File "/usr/local/lib/python3.9/site-packages/datasette/utils/asgi.py", line 280, in asgi_send_file await send( File "/usr/local/lib/python3.9/site-packages/asgi_csrf.py", line 104, in wrapped_send await send(event) File "/usr/local/lib/python3.9/site-packages/uvicorn/protocols/http/h11_impl.py", line 460, in send output = self.conn.send(event) File "/usr/local/lib/python3.9/site-packages/h11/_connection.py", line 468, in send data_list = self.send_with_data_passthrough(event) File "/usr/local/lib/python3.9/site-packages/h11/_connection.py", line 501, in send_with_data_passthrough writer(event, data_list.append) File "/usr/local/lib/python3.9/site-packages/h11/_writers.py", line 58, in __call__ self.send_data(event.data, write) File "/usr/local/lib/python3.9/site-packages/h11/_writers.py", line 78, in send_data raise LocalProtocolError("Too much data for declared Content-Length") h11._util.LocalProtocolError: Too much data for declared Content-Length

Thanks, I am finding Datasette very useful.

The datasette-write plugin provides this at the moment https://github.com/simonw/datasette-write - but it feels like it should be a built-in capability, protected by a default permission.

UI concept: if you have write permission then the existing SQL editor gets an "execute write" checkbox underneath it.

JavaScript can spot if you appear to be trying to execute an UPDATE or INSERT or DELETE query and check that checkbox for you.

If you link to a query page with a non-SELECT then that query will be displayed in the box ready for you to POST submit it. The page will also then get "cannot be embedded" headers to protect against clickjacking.

Inspired by thinking about #1549 - returning ALL rows from an arbitrary query is a lot easier if you just run that query and keep iterating over the cursor.

I've avoided doing that in the past because it could tie up a connection for a long time - but in private instances this wouldn't be such a problem.

Thanks for this tremendous package, @simonw!

In the description_html for a database, I have an unordered list.

However, on the database page on the deployed site, it is not rendering this as a bulleted list.

Page here: https://labordata-warehouse.herokuapp.com/nlrb-9da4ae5

The documentation gives an example of using an unordered list in a description_html, so I expected this will work.

I have two connected sites: http://www.SaferOrToxic.org (a Hugo website) and: http://disinfectants.SaferOrToxic.org/disinfectants/listN (a datasette table page)

The latter is linked as "The List" in the former's menu. (I'd love a prettier URL, but that's what I've got.)

On: http://disinfectants.SaferOrToxic.org/disinfectants/listN ... all the other menu links should point back to: https://www.SaferOrToxic.org And they do!

But the logo, for some reason--though it has an href pointing to: https://www.SaferOrToxic.org Keeps going to this instead: https://disinfectants.saferortoxic.org/disinfectants/undefined

What is causing that? How can I fix it?

In #1284 back in March, I was doing battle with the index.html template, in a still unresolved issue. (I wanted only a single table page at the root.)

But I thought, well, if I can't resolve that, at least I could just point the main website to the datasette page ("The List,") and then have the List point back to the home website.

The menu hrefs to https://www.SaferOrToxic.org work just fine, exactly as they should, from the datasette page. Even the Home link works properly.

But the logo link keeps rewriting to: https://disinfectants.saferortoxic.org/disinfectants/undefined

This is the HTML: <a class="text-3xl font-bold leading-none" href="https://www.saferortoxic.org"><img src="https://www.saferortoxic.org/images/logo_hu26e4dce8d5931af1ea33526b28fc8383_9734_c52a4f1635ef88bda858373270551ed2.webp" class="custom-logo" alt="Logo: Safer or Toxic?" width="300px"></a>

Is this somehow related to cloudflare? Or something in the datasette code?

I'm starting to think it's a cloudflare issue.

Can I at least rule out it being a datasette issue?

My repository is here: https://github.com/mroswell/list-N

(BTW, I couldn't figure out how to reference a local image, either, on the datasette side, which is why I'm using the image from the www home page.)

To spot duplicate images (where the file content differs such that the sha256 is no longer a match) it would be useful to calculate and store perceptual hashes of some sort.

Sorting that by date makes sense for seeing most recent points, and my DB has 2.5m points in so it's an expensive sort!

Would it be worthwhile for the sqlite-utils command-line tool to grow features to efficiently directly interact with gzipped CSV data?

Maybe add --gz options to both insert and to the various commands that output query results.

It defaults to 100 per page, but you can increase that to 1000 per page using ?_size=max (or higher if max_returned_rows is set higher than that).

But... that's only available to people who know how to hack URLs.

Solution: add a link that sets that option to the pagination block at the bottom of the table:

Can show people how to open this up in Binder.

To clarify: the core problem here is that an error is thrown any time you call os.getcwd() but the directory you are currently in has been deleted.

runner.isolated_filesystem() assumes that the current directory in has not been deleted. But the various temporary directory utilities in pytest work by creating directories and then deleting them.

Maybe there's a larger problem here that I play a bit fast and loose with os.chdir() in both the test suite and in various lines of code in Datasette itself (in particular in the publish commands)?

Originally posted by @simonw in https://github.com/simonw/datasette/issues/1406#issuecomment-890390198

it would be very nice if the twitter, slack, and other social media could make rich cards when people post a link to a datasette instance

https://sqlite.org/mmap.html - SQLite supports memory-mapped I/O but it's disabled by default. The PRAGMA mmap_size=N option can be used to enable it.

It would be very interesting to understand the impact this could have on Datasette performance for various different shapes of data.

There's no link to download the CSV file - the table page has that as an advanced export option, but this is missing from the query page.

That seems to have fixed it. I'd love to get rid of this restore_working_directory hack entirely.

Originally posted by @simonw in https://github.com/simonw/datasette/issues/1361#issuecomment-855308811

Issue #1276 happened because I didn't run tests against a SQLite version prior to 3.16.0 (released 2017-01-02).

Glitch is a deployment target and runs SQLite 3.11.0 from 2016-02-15.

If CI ran against that version of SQLite this bug could have been avoided.

It would be less geeky and more user friendly if the display strings in the filter menu and possibly other parts could be localized.

I am trying to publish a db to vercel. But while issuing the below command throwing Access Denied error which is leading to RecursionError: maximum recursion depth exceeded while calling a Python object.

I am using PyCharm and Python 3.9. I have reinstalled both and launched PyCharm as Admin in Windows 10. But still the issue persists.

Issued command datasette publish vercel jmeter.db --project jmeter --install datasette-vega

PS: localhost is working fine.

System info:

Windows 10 Datasette 0.55 installed via pip Python 3.8.5 in a conda environment

I'm getting the message These facets timed out on any faceting operation. However, when I apply a filter, the facets appear in the filtered view. The error returns when the filter is removed. My data only has 38,450 rows.

Hi Simon.

It seems that datasette currently has wildcard-searches disabled by default (along with the boolean search-options, NEAR-queries and more, and despite the docs). If I try out the search-url provided in the docs (https://fara.datasettes.com/fara/FARA_All_ShortForms?_search=manafort), it does not handle wildcard-searches, and I'm unable to make it work on my datasette-instance.

I would argue that wildcard-searches is such a standard query, that it should be enabled by default. Requiring "_searchmode=raw" when using prefix-searches seems unnecessary. Plus: What happens to non-ascii searches when using "_searchmode=raw"? Is the "escape_fts"-function from datasette.utils ignored?

Thanks!

/Claus

https://latest.datasette.io/fixtures?sql=select+*+from+compound_three_primary_keys&_size=10 - _size=10 does not do anything at the moment. It would be useful if it did.

Would also be good if it persisted in a hidden form field.

https://github.com/emeryberger/scalene looks like an interesting profiling tool.

Here's the error I get when running pip install pocket-to-sqlite:

Could not fetch URL https://pypi.python.org/simple/pocket-to-sqlite/: There was a problem confirming the ssl certificate: [SSL: TLSV1_ALERT_PROTOCOL_VERSION] tlsv1 alert protocol version (_ssl.c:661) - skipping Could not find a version that satisfies the requirement pocket-to-sqlite (from versions: ) No matching distribution found for pocket-to-sqlite

Does this require python 3?

sqlite-utils 3.2 now has a mechanism for creating a _counts table with triggers to maintain counts for individual tables. Datasette could look for this table and use it for counts, dramatically speeding up places that currently suffer from slow counts. Refs #859.

https://sqlite-utils.datasette.io/en/stable/python-api.html#cached-table-counts-using-triggers

While building https://github.com/simonw/datasette-export-notebook I thought it would be nice to be able to show a count of exported records on the page "This will stream 10,422 records to your notebook".

None of the documented arguments on https://docs.datasette.io/en/0.53/plugin_hooks.html#register-output-renderer-datasette expose the count. The closest is sql which could be executed as select count(*) from ({sql}) but that's a bit inelegant.

So, idea: if your defined render function takes a total argument, the caller runs a count(*) query and passes you that total.

To implement this I would need to teach the call_with_supported_arguments that some arguments are lazy - they should execute a function (or an async function) but only if they are needed.

I got this for a database I was playing with:

I think this is because of these three tables:

memory seems to grow unbounded and is oom-killed after about 20GB memory usage.

this is happening while loading a ~1GB uncompressed location history.

Initial idea: TODO list, as a tutorial for #698 writable canned queries.

For any number greater than 200, favorites --stop_after stops after getting 200 tweets, e.g. $ twitter-to-sqlite favorites tweets.db --stop_after=300 Importing favorites [####################################] 199 $ I don't think this is a limitation of the API (if you omit --stop_after you get some very large number, possibly all of them), so I think this is a bug.

I had to build a custom _actorornull prefix for datasette-saved-queries: ```python def actorornull(key, request): if request.actor is None: return None return request.actor.get(key)

@hookimpl def register_magic_parameters(): return [ ("actorornull", actorornull), ] `` Maybe theactor` magic in Datasette core should do that out of the box?

https://github.com/simonw/datasette/blob/f1f581b7ffcd5d8f3ae6c1c654d813a6641410eb/datasette/default_magic_parameters.py#L14-L17

I lost a bunch of time yesterday trying to figure out why a Datasette instance wasn't starting up - it turned out it was because I had a facets: reference that mentioned a column that did not exist.

Catching these on startup would be good.

As tables get bigger reindexing everything on a schedule (essentially recreating the entire index from scratch) will start to become a performance bottleneck.

Here's why: https://github.com/dogsheep/dogsheep-beta/blob/24f7898d41a39218058f174c75ba62f7c0fcfff6/dogsheep_beta/utils.py#L44-L53

That should probably do DELETE FROM index1.search_index WHERE [table] = ? first.

I'm getting this error when running:

sqlite-utils enable-wal beta.db

OperationalError: cannot change into wal mode from within a transaction

I'm worried that maybe that's because of this new code from #152:

https://github.com/simonw/sqlite-utils/blob/deb2eb013ff85bbc828ebc244a9654f0d9c3139e/sqlite_utils/db.py#L128-L129

The unit tests for plugins could benefit from reusing code from Datasette's own testing fixtures, e.g.:

I may need to borrow this function from Datasette for the tests: https://github.com/simonw/datasette/blob/1f6a134369e6a7efaae9db469f15b1dd2b7f3709/tests/fixtures.py#L836-L851

It's not importable (it lives in fixtures.py and not in the datasette package that gets packaged for PyPI) - maybe I should fix that in Datasette by adding a from datasette.utils.testing module. Originally posted by @simonw in https://github.com/simonw/datasette-update-api/issues/4#issuecomment-660419182

Could be useful for debugging plugins: https://pluggy.readthedocs.io/en/latest/#call-tracing

I tried this out by adding these two lines in plugins.py: ```python pm = pluggy.PluginManager("datasette") pm.add_hookspecs(hookspecs)

Added these:

pm.trace.root.setwriter(print) pm.enable_tracing() Output looked something like this: INFO: 127.0.0.1:52724 - "GET /-/-/static/app.css HTTP/1.1" 404 Not Found actor_from_request [hook] datasette: <datasette.app.Datasette object at 0x106277ad0> request: <datasette.utils.asgi.Request object at 0x106550a50>

finish actor_from_request --> [] [hook]

extra_body_script [hook] template: show_json.html database: None table: None view_name: json_data datasette: <datasette.app.Datasette object at 0x106277ad0>

finish extra_body_script --> [] [hook]

extra_template_vars [hook] template: show_json.html database: None table: None view_name: json_data request: <datasette.utils.asgi.Request object at 0x1065504d0> datasette: <datasette.app.Datasette object at 0x106277ad0>

finish extra_template_vars --> [] [hook]

extra_css_urls [hook] template: show_json.html database: None table: None datasette: <datasette.app.Datasette object at 0x106277ad0>

finish extra_css_urls --> [] [hook]

extra_js_urls [hook] template: show_json.html database: None table: None datasette: <datasette.app.Datasette object at 0x106277ad0>

finish extra_js_urls --> [] [hook]

INFO: 127.0.0.1:52724 - "GET /-/actor HTTP/1.1" 200 OK actor_from_request [hook] datasette: <datasette.app.Datasette object at 0x106277ad0> request: <datasette.utils.asgi.Request object at 0x1065500d0>

finish actor_from_request --> [] [hook] ```

At the moment the page returning a custom SQL query shows the JSON and CSV APIs, but not the multiple JSON shapes. However, adding the _shape parameter to the JSON API URL manually still works, so perhaps there should be consistency in the interface by having the same "Advanced Export" box for custom SQL queries.

The upload command currently only handles static images:

https://github.com/dogsheep/photos-to-sqlite/blob/d939455af00e07866686457ee2fcb9b2d1b7194e/photos_to_sqlite/utils.py#L26-L33

Need to cover movies taken by my phone and DSLR too.

Hi! I did not find any mention on the library about ON DELETE and ON UPDATE actions for foreign keys. Are those expected to be implemented? If not, it would be a nice thing to include!

Simon,

I'm trying to use the app.css (in static folder) as style sheet but the datasette on Heroku simply ignore it! I read everything about customization here and on readthedocs but still can't.

Is this possible?

Thanks!

Per the issue described in issue #588, it was determined queries are not supported at the table level. Per my last comment in the issue, I'd like to request support for this as it would help eliminate errors in the event certain tables are not present in the database.

Could use https://github.com/scottbedard/svelte-heatmap

See this thread on Twitter: https://twitter.com/simonw/status/952637152797458432

I've a radical feature idea (possible first as an extension in order to experiment?):

I'd like to link to a remote table from a remote database, e.g. with a function "linked_datasette()". So one could do following query: SELECT foo.id, foo.a, remote_party.b FROM foo JOIN linked_datasette("https://parlgov.datasettes.com/parlgov-b42a2f2") AS remote_party ON foo.id=remote_party.id This is inspired by SPARQL's SERVICE keyword for remote RDF "endpoints".

There's a foundation in the SQL Standard called SQL/MED (https://rhaas.blogspot.com/2011/01/why-sqlmed-is-cool.html ).

And here's an implementation from me in Postgres FDW to connect another Postgres "endpoint": https://pastebin.com/Fz2v64Cz .

It would be useful to document how to pass Heroku CLI options on datasette publish, e.g. --region eu.

Right now deploying a new version of datasette doesn't invalidate existing URLs, so users may still see a cached copy of the old templates.

We can fix this by including the current datasette version in the input to the hash function (which currently just the database file contents).

Datasette limits the number of rows returned to 1,000 and limits the time spent executing a SQL query to 1000ms - and both of these limits can be customized.

It does not have a limit on the size of the response returned. It's possible to compose maliciously large SQL responses in a small number of rows using mechanisms like the group_concat() aggregate function. It would be good to avoid malicious SQL creating 100MB+ responses and potentially crashing the server.

I think the easiest place to implement that is here:

https://github.com/simonw/datasette/blob/f3f42957128c1e7ece584d45d9167f2ac003a3b8/datasette/app.py#L175-L190

Currently we use cursor.fetchmany() to fetch up to 1,001 rows at once. Instead, we could switch to iterating through cursor.fetchone() (or just using for row in cursor) and keeping a running tally of the size of the response as we go - maybe just using rough_response_size += len(str(row)). If that goes above a certain threshold we can terminate the response with an error, like we do with timelimits.

The bigger challenge here is understanding how well this approach works and what impact it will have on overall Datasette performance. I think I need #33 for this.