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.

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

Summary

When using the API, repeated calls to Table.convert() do not work correctly since all conversions quietly use the callable (function, lambda) from the first call to convert() only. Subsequent invocations with different callables use the callable from the first invocation only.

Example

```python from sqlite_utils import Database

db = Database(memory=True) table = db['table'] col = 'x' table.insert_all([{col: 1}]) print(table.get(1))

table.convert(col, lambda x: x*2) print(table.get(1))

def zeroize(x): return 0

zeroize = lambda x: 0

zeroize.name = 'zeroize'

table.convert(col, zeroize) print(table.get(1)) ```

Output: {'x': 1} {'x': 2} {'x': 4} Expected: {'x': 1} {'x': 2} {'x': 0}

Explanation

This is some relevant documentation.

• Table.convert() takes a Callable to perform data conversion on a column
• The Callable is passed to Database.register_function()
• Database.register_function() uses the callable's __name__ attribute for registration
• (Aside: all lambdas have a __name__ of <lambda>: I thought this was the problem, and it was close, but not quite)
• However convert() first wraps the callable by local function convert_value()
• Consequently register_function() sees name convert_value for all invocations from convert()
• register_function() silently ignores registrations using the same name, retaining only the first such registration

There's a mismatch between the comments and the code: https://github.com/simonw/sqlite-utils/blob/fc221f9b62ed8624b1d2098e564f525c84497969/sqlite_utils/db.py#L404

but actually the existing function is returned/used instead (as the "registering custom sql functions" doc I linked above says too). Seems like this can be rectified to match the comment?

Suggested fix

I think there are four things: 1. The call to register_function() from convert()should have an explicit name= parameter (to continue using convert_value() and the progress bar). 2. For functions, this name can be the real function name. (I understand the sqlite api needs a name, and it's nice if those are recognizable names where possible). For lambdas would 'lambda-{uuid}' or similar be acceptable? 3. register_function() really should throw an error on repeated attempts to register a duplicate (function, arity)-pair. 4. A test? I haven't looked at the test framework here but seems this should be testable.

See also

• 458

https://readthedocs.org/projects/sqlite-utils/builds/20512693/ ``` Running Sphinx v6.2.1

Traceback (most recent call last): File "/home/docs/checkouts/readthedocs.org/user_builds/sqlite-utils/envs/latest/lib/python3.8/site-packages/sphinx/registry.py", line 442, in load_extension mod = import_module(extname) File "/home/docs/checkouts/readthedocs.org/user_builds/sqlite-utils/envs/latest/lib/python3.8/importlib/init.py", line 127, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "<frozen importlib._bootstrap>", line 1014, in _gcd_import File "<frozen importlib._bootstrap>", line 991, in _find_and_load File "<frozen importlib._bootstrap>", line 975, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 671, in _load_unlocked File "<frozen importlib._bootstrap_external>", line 783, in exec_module File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed File "/home/docs/checkouts/readthedocs.org/user_builds/sqlite-utils/envs/latest/lib/python3.8/site-packages/sphinx/builders/linkcheck.py", line 20, in <module> from requests import Response File "/home/docs/checkouts/readthedocs.org/user_builds/sqlite-utils/envs/latest/lib/python3.8/site-packages/requests/init.py", line 43, in <module> import urllib3 File "/home/docs/checkouts/readthedocs.org/user_builds/sqlite-utils/envs/latest/lib/python3.8/site-packages/urllib3/init.py", line 38, in <module> raise ImportError( ImportError: urllib3 v2.0 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with OpenSSL 1.0.2n 7 Dec 2017. See: https://github.com/urllib3/urllib3/issues/2168

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "/home/docs/checkouts/readthedocs.org/user_builds/sqlite-utils/envs/latest/lib/python3.8/site-packages/sphinx/cmd/build.py", line 280, in build_main app = Sphinx(args.sourcedir, args.confdir, args.outputdir, File "/home/docs/checkouts/readthedocs.org/user_builds/sqlite-utils/envs/latest/lib/python3.8/site-packages/sphinx/application.py", line 225, in init self.setup_extension(extension) File "/home/docs/checkouts/readthedocs.org/user_builds/sqlite-utils/envs/latest/lib/python3.8/site-packages/sphinx/application.py", line 404, in setup_extension self.registry.load_extension(self, extname) File "/home/docs/checkouts/readthedocs.org/user_builds/sqlite-utils/envs/latest/lib/python3.8/site-packages/sphinx/registry.py", line 445, in load_extension raise ExtensionError(__('Could not import extension %s') % extname, sphinx.errors.ExtensionError: Could not import extension sphinx.builders.linkcheck (exception: urllib3 v2.0 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with OpenSSL 1.0.2n 7 Dec 2017. See: https://github.com/urllib3/urllib3/issues/2168)

Extension error: Could not import extension sphinx.builders.linkcheck (exception: urllib3 v2.0 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with OpenSSL 1.0.2n 7 Dec 2017. See: https://github.com/urllib3/urllib3/issues/2168) ```

I wanted to output newline-separated output of the first column of every row in the results - like --row but for more than one line.

Pylance is generally pretty good at figuring out stuff but sqlite-utils has some quirks which make type hinting kinda useless. Maybe you don't care but I thought I would bring it to your attention.

For example:

db["subs"].insert_all(subs, pk="index")

Cannot access member "insert_all" for type "View" Member "insert_all" is unknown

insert_all and all the other methods show up as a type issues because the program can't know whether something is a View or a Table. Fair enough. But that basically throws all type checking out the window.

pk="index" also shows up as a type issue:

Argument of type "Literal['index']" cannot be assigned to parameter "pk" of type "Default" in function "insert_all" "Literal['index']" is incompatible with "Default"

I think this is because DEFAULT is an empty class?

maybe a few small changes could be made to make the library more type-friendly

The interim solution is of course to turn off type hints completely for the line db["subs"].insert_all(subs, pk="index") # type: ignore

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.

generates checkins.db but seems to fail before generating views

note: it worked on an Ubuntu WSL but fails on macOS 12.5.1

later edit: I suspect this is a problem with my local set-up, dogsheep-beta index also throws the same error

full error:

Importing 2591 checkins  [###################################-]   98%  00:00:00
Traceback (most recent call last):
  File "/Users/pax/devbox/envAll/bin/swarm-to-sqlite", line 8, in <module>
    sys.exit(cli())
  File "/Users/pax/devbox/envAll/lib/python3.8/site-packages/click/core.py", line 829, in __call__
    return self.main(*args, **kwargs)
  File "/Users/pax/devbox/envAll/lib/python3.8/site-packages/click/core.py", line 782, in main
    rv = self.invoke(ctx)
  File "/Users/pax/devbox/envAll/lib/python3.8/site-packages/click/core.py", line 1066, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/Users/pax/devbox/envAll/lib/python3.8/site-packages/click/core.py", line 610, in invoke
    return callback(*args, **kwargs)
  File "/Users/pax/devbox/envAll/lib/python3.8/site-packages/swarm_to_sqlite/cli.py", line 77, in cli
    ensure_foreign_keys(db)
  File "/Users/pax/devbox/envAll/lib/python3.8/site-packages/swarm_to_sqlite/utils.py", line 145, in ensure_foreign_keys
    db[fk.table].add_foreign_key(fk.column, fk.other_table, fk.other_column)
  File "/Users/pax/devbox/envAll/lib/python3.8/site-packages/sqlite_utils/db.py", line 2123, in add_foreign_key
    self.db.add_foreign_keys([(self.name, column, other_table, other_column)])
  File "/Users/pax/devbox/envAll/lib/python3.8/site-packages/sqlite_utils/db.py", line 1086, in add_foreign_keys
    cursor.execute(
sqlite3.OperationalError: table sqlite_master may not be modified

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?

https://hachyderm.io/@briandorsey/109468185742876820

I'm fiddling with piping json to insert -ignore I'd love to see the count of records inserted & ignored, but didn't see a way to do that in the help/docs.

Example: xh "https://hachyderm.io/api/v1/timelines/tag/rust?max_id=109443380308326328" | sqlite-utils insert aoc.db aoc - --pk=id --ignore

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.

Reported here: https://github.com/dogsheep/healthkit-to-sqlite/issues/9

It looks like there's a default limit of 999 variables - we need to be smart about that, maybe dynamically lower the batch size based on the number of columns.

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

Failure here: https://github.com/simonw/sqlite-utils/actions/runs/3275786702/jobs/5391063221

I figured out the problem:

`diff diff --git a/docs/cli-reference.rst b/docs/cli-reference.rst index b88e38a..82b4b6c 100644 --- a/docs/cli-reference.rst +++ b/docs/cli-reference.rst @@ -112,11 +112,15 @@ See :ref:`cli_query`. --tsv Output TSV --no-headers Omit CSV headers -t, --table Output as a formatted table - --fmt TEXT Table format - one of fancy_grid, fancy_outline, - github, grid, html, jira, latex, latex_booktabs, - latex_longtable, latex_raw, mediawiki, moinmoin, - orgtbl, pipe, plain, presto, pretty, psql, rst, - simple, textile, tsv, unsafehtml, youtrack + --fmt TEXT Table format - one of asciidoc, double_grid, + double_outline, fancy_grid, fancy_outline, github, + grid, heavy_grid, heavy_outline, html, jira, + latex, latex_booktabs, latex_longtable, latex_raw, + mediawiki, mixed_grid, mixed_outline, moinmoin, + orgtbl, outline, pipe, plain, presto, pretty, + psql, rounded_grid, rounded_outline, rst, simple, + simple_grid, simple_outline, textile, tsv, + unsafehtml, youtrack --json-cols Detect JSON cols and output them as JSON, not escaped strings -r, --raw Raw output, first column of first row @@ -176,11 +180,15 @@ See :ref:`cli_memory`. --tsv Output TSV --no-headers Omit CSV headers -t, --table Output as a formatted table - --fmt TEXT Table format - one of fancy_grid, fancy_outline, - github, grid, html, jira, latex, latex_booktabs, - latex_longtable, latex_raw, mediawiki, moinmoin, - orgtbl, pipe, plain, presto, pretty, psql, rst, - simple, textile, tsv, unsafehtml, youtrack + --fmt TEXT Table format - one of asciidoc, double_grid, + double_outline, fancy_grid, fancy_outline, github, + grid, heavy_grid, heavy_outline, html, jira, + latex, latex_booktabs, latex_longtable, latex_raw, + mediawiki, mixed_grid, mixed_outline, moinmoin, + orgtbl, outline, pipe, plain, presto, pretty, + psql, rounded_grid, rounded_outline, rst, simple, + simple_grid, simple_outline, textile, tsv, + unsafehtml, youtrack --json-cols Detect JSON cols and output them as JSON, not escaped strings -r, --raw Raw output, first column of first row @@ -401,11 +409,14 @@ See :ref:`cli_search`. --tsv Output TSV --no-headers Omit CSV headers -t, --table Output as a formatted table - --fmt TEXT Table format - one of fancy_grid, fancy_outline, - github, grid, html, jira, latex, latex_booktabs, - latex_longtable, latex_raw, mediawiki, moinmoin, - orgtbl, pipe, plain, presto, pretty, psql, rst, simple, - textile, tsv, unsafehtml, youtrack + --fmt TEXT Table format - one of asciidoc, double_grid, + double_outline, fancy_grid, fancy_outline, github, + grid, heavy_grid, heavy_outline, html, jira, latex, + latex_booktabs, latex_longtable, latex_raw, mediawiki, + mixed_grid, mixed_outline, moinmoin, orgtbl, outline, + pipe, plain, presto, pretty, psql, rounded_grid, + rounded_outline, rst, simple, simple_grid, + simple_outline, textile, tsv, unsafehtml, youtrack --json-cols Detect JSON cols and output them as JSON, not escaped strings --load-extension TEXT Path to SQLite extension, with optional :entrypoint @@ -651,11 +662,14 @@ See :ref:`cli_tables`. --tsv Output TSV --no-headers Omit CSV headers -t, --table Output as a formatted table - --fmt TEXT Table format - one of fancy_grid, fancy_outline, - github, grid, html, jira, latex, latex_booktabs, - latex_longtable, latex_raw, mediawiki, moinmoin, - orgtbl, pipe, plain, presto, pretty, psql, rst, simple, - textile, tsv, unsafehtml, youtrack + --fmt TEXT Table format - one of asciidoc, double_grid, + double_outline, fancy_grid, fancy_outline, github, + grid, heavy_grid, heavy_outline, html, jira, latex, + latex_booktabs, latex_longtable, latex_raw, mediawiki, + mixed_grid, mixed_outline, moinmoin, orgtbl, outline, + pipe, plain, presto, pretty, psql, rounded_grid, + rounded_outline, rst, simple, simple_grid, + simple_outline, textile, tsv, unsafehtml, youtrack --json-cols Detect JSON cols and output them as JSON, not escaped strings --columns Include list of columns for each table @@ -689,11 +703,14 @@ See :ref:`cli_views`. --tsv Output TSV --no-headers Omit CSV headers -t, --table Output as a formatted table - --fmt TEXT Table format - one of fancy_grid, fancy_outline, - github, grid, html, jira, latex, latex_booktabs, - latex_longtable, latex_raw, mediawiki, moinmoin, - orgtbl, pipe, plain, presto, pretty, psql, rst, simple, - textile, tsv, unsafehtml, youtrack + --fmt TEXT Table format - one of asciidoc, double_grid, + double_outline, fancy_grid, fancy_outline, github, + grid, heavy_grid, heavy_outline, html, jira, latex, + latex_booktabs, latex_longtable, latex_raw, mediawiki, + mixed_grid, mixed_outline, moinmoin, orgtbl, outline, + pipe, plain, presto, pretty, psql, rounded_grid, + rounded_outline, rst, simple, simple_grid, + simple_outline, textile, tsv, unsafehtml, youtrack --json-cols Detect JSON cols and output them as JSON, not escaped strings --columns Include list of columns for each view @@ -732,11 +749,15 @@ See :ref:`cli_rows`. --tsv Output TSV --no-headers Omit CSV headers -t, --table Output as a formatted table - --fmt TEXT Table format - one of fancy_grid, fancy_outline, - github, grid, html, jira, latex, latex_booktabs, - latex_longtable, latex_raw, mediawiki, moinmoin, - orgtbl, pipe, plain, presto, pretty, psql, rst, - simple, textile, tsv, unsafehtml, youtrack + --fmt TEXT Table format - one of asciidoc, double_grid, + double_outline, fancy_grid, fancy_outline, github, + grid, heavy_grid, heavy_outline, html, jira, + latex, latex_booktabs, latex_longtable, latex_raw, + mediawiki, mixed_grid, mixed_outline, moinmoin, + orgtbl, outline, pipe, plain, presto, pretty, + psql, rounded_grid, rounded_outline, rst, simple, + simple_grid, simple_outline, textile, tsv, + unsafehtml, youtrack --json-cols Detect JSON cols and output them as JSON, not escaped strings --load-extension TEXT Path to SQLite extension, with optional @@ -768,11 +789,14 @@ See :ref:`cli_triggers`. --tsv Output TSV --no-headers Omit CSV headers -t, --table Output as a formatted table - --fmt TEXT Table format - one of fancy_grid, fancy_outline, - github, grid, html, jira, latex, latex_booktabs, - latex_longtable, latex_raw, mediawiki, moinmoin, - orgtbl, pipe, plain, presto, pretty, psql, rst, simple, - textile, tsv, unsafehtml, youtrack + --fmt TEXT Table format - one of asciidoc, double_grid, + double_outline, fancy_grid, fancy_outline, github, + grid, heavy_grid, heavy_outline, html, jira, latex, + latex_booktabs, latex_longtable, latex_raw, mediawiki, + mixed_grid, mixed_outline, moinmoin, orgtbl, outline, + pipe, plain, presto, pretty, psql, rounded_grid, + rounded_outline, rst, simple, simple_grid, + simple_outline, textile, tsv, unsafehtml, youtrack --json-cols Detect JSON cols and output them as JSON, not escaped strings --load-extension TEXT Path to SQLite extension, with optional :entrypoint @@ -804,11 +828,14 @@ See :ref:`cli_indexes`. --tsv Output TSV --no-headers Omit CSV headers -t, --table Output as a formatted table - --fmt TEXT Table format - one of fancy_grid, fancy_outline, - github, grid, html, jira, latex, latex_booktabs, - latex_longtable, latex_raw, mediawiki, moinmoin, - orgtbl, pipe, plain, presto, pretty, psql, rst, simple, - textile, tsv, unsafehtml, youtrack + --fmt TEXT Table format - one of asciidoc, double_grid, + double_outline, fancy_grid, fancy_outline, github, + grid, heavy_grid, heavy_outline, html, jira, latex, + latex_booktabs, latex_longtable, latex_raw, mediawiki, + mixed_grid, mixed_outline, moinmoin, orgtbl, outline, + pipe, plain, presto, pretty, psql, rounded_grid, + rounded_outline, rst, simple, simple_grid, + simple_outline, textile, tsv, unsafehtml, youtrack --json-cols Detect JSON cols and output them as JSON, not escaped strings --load-extension TEXT Path to SQLite extension, with optional :entrypoint diff --git a/docs/cli.rst b/docs/cli.rst index 8bc4176..1d67e88 100644 --- a/docs/cli.rst +++ b/docs/cli.rst @@ -187,10 +187,15 @@ Available--fmtoptions are: cog.out("\n" + "\n".join('-{}``'.format(t) for t in tabulate.tabulate_formats) + "\n\n") .. ]]]

+- asciidoc +- double_grid +- double_outline - fancy_grid - fancy_outline - github - grid +- heavy_grid +- heavy_outline - html - jira - latex @@ -198,15 +203,22 @@ Available --fmt options are: - latex_longtable - latex_raw - mediawiki +- mixed_grid +- mixed_outline - moinmoin - orgtbl +- outline - pipe - plain - presto - pretty - psql +- rounded_grid +- rounded_outline - rst - simple +- simple_grid +- simple_outline - textile - tsv - unsafehtml ```

The --flatten implementation isn't currently available to Python code - people have to roll their own implementation. Feedback from a conversation at DjangoCon.

From #50 - right now it will crash with an error of it hits the rate limit. Since the rate limit information (including reset time) is available in the headers it could automatically sleep and try again instead.

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

I was looking into how to parse application log files that contain multiline text (e.g. Java stack traces) into sqlite. I can see that at the moment --lines helps, but falls short when processing multi-line texts.

I wonder if this functionality would be useful for sqlite-utils. A similar approach to Elastic logstash/filebeat can be adopted: https://www.elastic.co/guide/en/beats/filebeat/current/multiline-examples.html

Potential changes:

• add a --multiline option
• additional properties for
• multiline-pattern (regex expression)
• multiline-negate: true/false
• multiline-what: previous or next

Or if this is achievable in a different way, please share. Thanks!

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.

is there a duplicate table functionality? Otherwise, I'd be happy to submit a PR.

In sqlite3 it would look like:

```python import sqlite3 as sl

con = sl.connect('prompt-tune.db')

def db_duplicate_table(table_name, table_name_new, con=con): # Duplicates table table_name to a new table table_name_new. try: cur = con.cursor() cur.execute(f"""CREATE TABLE {table_name_new} AS SELECT * FROM {table_name}""") except Exception as e: print(e) finally: cur.close()

db_duplicate_table('orig_table', 'new_table') ```

Columns duration, totalDistance and totalEnergyBurned should be converted to float.

https://github.com/dogsheep/healthkit-to-sqlite/blob/71e36e1cf034b96de2a8e6652265d782d3fdf63b/healthkit_to_sqlite/utils.py#L50-L57

What is the right way to limit a full text search query to some rows of a table?

For example, I have a table that contains the following columns: title, content, owner (each row represents a document). The owner column is a username. It feels right to store all documents in one table, instead of having one table per owner. In particular because I'd like to full text search all documents, only documents owned by one user and documents owned by a set of users.

I tried to combine .rows_where("owner = ?", "1234") and .search() from the Table class but I don't think that is meant to work. I discovered .search_sql() as a way to generate the FTS SQL statement. By hand I can edit it to add a AND [original].[owner] = :owner to the where clause. This seems to do what I want.

My two questions: 1. is adding a AND ... to the where clause actually the right thing to do or should I be doing something else (my SQL skills are low)? 2. is there a built-in to sqlite-utils way to achieve this?

Right now I am thinking I will make my own version of search_sql() that generates a query that contains an additional owner = :owner for my particular use-case.

Bonus question: is this generally useful/something to add to sqlite-utils or too niche?

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).

Hi

I note that you define _hash() to create a hash_id from non-id column values in a table here.

It would be useful to be able to call a complementary function to generate a corresponding _id from a subset of specified columns when adding items to another table, eg to support the creation of foreign keys.

Or is there a better pattern for doing that?

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.

Original title: Add option for adding a new, serial, primary key

sometimes we have tables that don't have primary keys, but ought to have them. we can use rowid for that, but it would often be nicer to have an explicit primary key. using the current value of rowid would be fine.

Is there a reason I've not added --extract as an option for sqlite-utils insert next? There's a extracts= option for the various table.insert() etc methods - last line in this code block:

https://github.com/simonw/sqlite-utils/blob/213a0ff177f23a35f3b235386366ff132eb879f1/sqlite_utils/db.py#L2483-L2495

Here's the traceback if your --convert function doesn't return a dict right now: ``` % sqlite-utils insert /tmp/all.db blah /tmp/log.log --convert 'all.upper()' --all

Traceback (most recent call last): File "/Users/simon/.local/share/virtualenvs/sqlite-utils-C4Ilevlm/bin/sqlite-utils", line 33, in <module> sys.exit(load_entry_point('sqlite-utils', 'console_scripts', 'sqlite-utils')()) File "/Users/simon/.local/share/virtualenvs/sqlite-utils-C4Ilevlm/lib/python3.8/site-packages/click/core.py", line 1137, in call return self.main(args, kwargs) File "/Users/simon/.local/share/virtualenvs/sqlite-utils-C4Ilevlm/lib/python3.8/site-packages/click/core.py", line 1062, in main rv = self.invoke(ctx) File "/Users/simon/.local/share/virtualenvs/sqlite-utils-C4Ilevlm/lib/python3.8/site-packages/click/core.py", line 1668, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/Users/simon/.local/share/virtualenvs/sqlite-utils-C4Ilevlm/lib/python3.8/site-packages/click/core.py", line 1404, in invoke return ctx.invoke(self.callback, ctx.params) File "/Users/simon/.local/share/virtualenvs/sqlite-utils-C4Ilevlm/lib/python3.8/site-packages/click/core.py", line 763, in invoke return __callback(args, **kwargs) File "/Users/simon/Dropbox/Development/sqlite-utils/sqlite_utils/cli.py", line 949, in insert insert_upsert_implementation( File "/Users/simon/Dropbox/Development/sqlite-utils/sqlite_utils/cli.py", line 834, in insert_upsert_implementation db[table].insert_all( File "/Users/simon/Dropbox/Development/sqlite-utils/sqlite_utils/db.py", line 2602, in insert_all first_record = next(records) File "/Users/simon/Dropbox/Development/sqlite-utils/sqlite_utils/db.py", line 3044, in fix_square_braces for record in records: File "/Users/simon/Dropbox/Development/sqlite-utils/sqlite_utils/cli.py", line 831, in <genexpr> docs = (decode_base64_values(doc) for doc in docs) File "/Users/simon/Dropbox/Development/sqlite-utils/sqlite_utils/utils.py", line 86, in decode_base64_values to_fix = [ File "/Users/simon/Dropbox/Development/sqlite-utils/sqlite_utils/utils.py", line 89, in <listcomp> if isinstance(doc[k], dict) TypeError: string indices must be integers ``` It would be nicer if that returned a more useful error message.

Originally posted by @simonw in https://github.com/simonw/sqlite-utils/issues/361#issuecomment-1006295276

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.

Could add support for --batch-size as seen in insert/upsert too - causing it to break the list up into batches and commit for each one.

Originally posted by @simonw in https://github.com/simonw/sqlite-utils/issues/391#issuecomment-1021876055

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.

Can be maintained using cog from #373. Similar in purpose to the API reference page, but this is for the CLI.

Not sure why I didn't implement this.

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 ```

Right now you use conversions= like this:

python db["example"].insert({ "name": "The Bigfoot Discovery Museum" }, conversions={"name": "upper(?)"}) How about if you could optionally provide a Python function (or a lambda) like this? python db["example"].insert({ "name": "The Bigfoot Discovery Museum" }, conversions={"name": lambda s: s.upper()}) This would work by creating a random name for that function, registering it (similar to #162), executing the SQL and then un-registering the custom function at the end.

I think the fix for this is to change the rules about what code is accepted in both the - mode and the literal code string mode: you can pass in a Python expression, OR a fragment that gets turned into a function, OR code that implements its own def convert(value) function. So this would work too: sh sqlite-utils convert my.db mytable col1 ' def convert(value): return value.upper() ' Originally posted by @simonw in https://github.com/simonw/sqlite-utils/issues/353#issuecomment-991381679

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.

For the commits table I feel like I want a version of table.lookup() that can be passed additional columns to populate only if the record does not exist yet.

Originally posted by @simonw in https://github.com/simonw/git-history/issues/12#issuecomment-967455017

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. )

~ % gsutil cat gs://ossf-criticality-score/python_top_200.csv | sqlite-utils insert /tmp/crit.db crit - ... File "/usr/local/Cellar/python@3.9/3.9.0_3/Frameworks/Python.framework/Versions/3.9/lib/python3.9/json/decoder.py", line 337, in decode obj, end = self.raw_decode(s, idx=_w(s, 0).end()) File "/usr/local/Cellar/python@3.9/3.9.0_3/Frameworks/Python.framework/Versions/3.9/lib/python3.9/json/decoder.py", line 355, in raw_decode raise JSONDecodeError("Expecting value", s, err.value) from None json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0) A nicer error message here would be one that says the JSON is invalid but suggests that maybe you could try --csv.

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

When I use multiple files with the same name, e.g. in sqlite-utils memory a/bug.csv b/bug.csv, sqlite-utils creates invalid views. Traceback (most recent call last): File "/home/karl/.local/bin/sqlite-utils", line 8, in <module> sys.exit(cli()) File "/home/karl/.local/pipx/venvs/sqlite-utils/lib/python3.9/site-packages/click/core.py", line 1137, in __call__ return self.main(*args, **kwargs) File "/home/karl/.local/pipx/venvs/sqlite-utils/lib/python3.9/site-packages/click/core.py", line 1062, in main rv = self.invoke(ctx) File "/home/karl/.local/pipx/venvs/sqlite-utils/lib/python3.9/site-packages/click/core.py", line 1668, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/home/karl/.local/pipx/venvs/sqlite-utils/lib/python3.9/site-packages/click/core.py", line 1404, in invoke return ctx.invoke(self.callback, **ctx.params) File "/home/karl/.local/pipx/venvs/sqlite-utils/lib/python3.9/site-packages/click/core.py", line 763, in invoke return __callback(*args, **kwargs) File "/home/karl/.local/pipx/venvs/sqlite-utils/lib/python3.9/site-packages/sqlite_utils/cli.py", line 1299, in memory db[csv_table].transform(types=tracker.types) File "/home/karl/.local/pipx/venvs/sqlite-utils/lib/python3.9/site-packages/sqlite_utils/db.py", line 1287, in transform self.db.execute(sql) File "/home/karl/.local/pipx/venvs/sqlite-utils/lib/python3.9/site-packages/sqlite_utils/db.py", line 421, in execute return self.conn.execute(sql) sqlite3.OperationalError: error in view t1: no such table: main.bug

This can be reproduced with ```sh

!/bin/bash

mkdir foo mkdir bar echo -e 'col1,col2\nval1,val2' > foo/bug.csv echo -e 'col3,col4\nval3,val4' > bar/bug.csv sqlite-utils memory */bug.csv 'SELECT 1' ```

Ideally, the tables would get unique names by including the next path segment until the names are unique. But just making the numbered t* aliases work would be good enough.

This problem can of course be worked around by renaming the files, but it would be nice if this case was handled more gracefully.

Thanks a lot for this great tool!

Got this error today: (evernote-to-sqlite) /tmp % evernote-to-sqlite enex evernote.db simonwillison\'s\ notebook.enex Importing from ENEX [######------------------------------] 17% Traceback (most recent call last): File "/Users/simon/.local/bin/evernote-to-sqlite", line 8, in <module> sys.exit(cli()) File "/Users/simon/.local/pipx/venvs/evernote-to-sqlite/lib/python3.9/site-packages/click/core.py", line 1137, in __call__ return self.main(*args, **kwargs) File "/Users/simon/.local/pipx/venvs/evernote-to-sqlite/lib/python3.9/site-packages/click/core.py", line 1062, in main rv = self.invoke(ctx) File "/Users/simon/.local/pipx/venvs/evernote-to-sqlite/lib/python3.9/site-packages/click/core.py", line 1668, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/Users/simon/.local/pipx/venvs/evernote-to-sqlite/lib/python3.9/site-packages/click/core.py", line 1404, in invoke return ctx.invoke(self.callback, **ctx.params) File "/Users/simon/.local/pipx/venvs/evernote-to-sqlite/lib/python3.9/site-packages/click/core.py", line 763, in invoke return __callback(*args, **kwargs) File "/Users/simon/.local/pipx/venvs/evernote-to-sqlite/lib/python3.9/site-packages/evernote_to_sqlite/cli.py", line 31, in enex save_note(db, note) File "/Users/simon/.local/pipx/venvs/evernote-to-sqlite/lib/python3.9/site-packages/evernote_to_sqlite/utils.py", line 36, in save_note content = ET.tostring(ET.fromstring(content_xml)).decode("utf-8") File "/usr/local/Cellar/python@3.9/3.9.6/Frameworks/Python.framework/Versions/3.9/lib/python3.9/xml/etree/ElementTree.py", line 1347, in XML parser.feed(text) xml.etree.ElementTree.ParseError: not well-formed (invalid token): line 2, column 132

Thanks for the excellent library, it's very nice to use!

I've been building some in memory search functionality for a data annotation tool i'm making, and I got tripped up a little bit with escaping the full text search queries. First I tried using db.quote(q), which doesn't work, because sqlite FTS has it's own (separate) query syntax. You can see this happening here also:

http://search-24ways.herokuapp.com/24ways-f8f455f/articles?_search=acces%2A

I got around this by aggressively escaping quotes inside the query string like this:

```python quoted = q.replace('"', '""') quoted = f'"{quoted}"' print(quoted) results = db["data"].search(quoted, columns=["id"]) return [x["id"] for x in results]

```

This works in the sense it doesn't crash, but it also removes access to the search query syntax. Given the well specified definition, it might be possible for sqlite-utils to provide a db.quote_query(q) which would intelligently escape a query whilst leaving the syntax intact. This would be very nice!

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.

Using https://www.sphinx-doc.org/en/master/usage/extensions/autodoc.html

I'm not a big fan of this kind of documentation because it so often comes in place of narrative documentation - but the library has great narrative documentation now, so the reference documentation can link to it in places.

This will also encourage me to add good docstrings everywhere, useful for IDEs and suchlike.

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.

I want to be able to fetch every item for a domain, e.g. https://news.ycombinator.com/from?site=simonwillison.net

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!

Hi,

fantastic framework for working with Sqlite3 databases!!!

I tried to update spezific rows in a table and used

for row in db[tablename]: newValue = row["counter"] * row["prize"]
row.update({"Fieldname": newValue}) print(row)

This updates the value in the printet row, but not in the database. So I switched to

db[tablename].update(id, {"Filedname": newValue})

This works fine. But row.update would be nicer, because no need for the id (its that row), no need for the tablename and the db (all defined in the for row ... loop).

Thx

I've touched on this before in #179 - but now that I've added sqlite-utils memory this is much more important - because unlike with sqlite-utils insert the in-memory command doesn't give you the opportunity to fix any types you imported from CSV, so queries like select * from stdin where age > 3 are never going to work correctly against these temporary in-memory tables.

Teaching sqlite-utils insert to detect types for columns in a CSV file would be a backwards-compatibility breaking change. Teaching sqlite-utils memory that trick would not be, since it hasn't been included in a release yet.

It's a little inconsistent, but I'm going to have sqlite-utils memory default to detecting types while sqlite-utils insert does not. In each case this can be controlled by a new command-line option:

cat file.csv | sqlite-utils memory - --no-detect-types

To opt-in for sqlite-utils insert:

cat file.csv | sqlite-utils insert blah.db blah - --detect-types

I'll have short options for these too: -n for --no-detect-types and -d for --detect-types.

Idea from https://github.com/simonw/datasette-edit-tables/issues/13 - provide Python utility methods and accompanying CLI options for detecting the likely types of TEXT columns.

So if you have a text column that actually contained exclusively integer string values, it can let you know and let you run transform against it.

It would be great if the column type could be set to JSON. That would not be different from handling a regular string. It would be something like repr(value) and it would work with both JSON and CSV inputs, no matter if value is a real list or just a string representing a list.

table.schema returns the schema for a table. db.schema should return the schema for the whole databes.

Can do this using select sql from sqlite_master where sql is not null:

https://latest.datasette.io/fixtures?sql=select+sql+from+sqlite_master+where+sql+is+not+null

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 ```

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.