An open source multi-tool for exploring and publishing data https://datasette.io
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Claude 5b6cf45568
Add web UI to edit and delete stored queries
Stored query pages now offer Edit and Delete actions in the query
actions menu, gated by the update-query and delete-query permissions.

- New QueryEditView (GET/POST at /<db>/<query>/-/edit) renders a
  pre-filled form for editing a query's title, description, SQL and
  privacy, reusing the create-query analysis UI. Changing the SQL still
  requires execute-sql; metadata-only edits do not.
- QueryDeleteView gains a GET confirmation page and HTML form POST that
  redirects to the query list, while keeping the existing JSON API.
- New default query_actions hook adds the Edit/Delete links for stored
  (non-config, non-trusted) queries the actor is allowed to manage.

Permission semantics (already enforced by default_query_permissions_sql)
are surfaced in the UI: owners can always edit/delete their queries;
non-private queries can be edited/deleted by any actor with the relevant
permission; private queries remain owner-only.

Shared the create-query form styles into _query_form_styles.html so the
edit form can reuse them.

https://claude.ai/code/session_019GU9g3pZAERukLKYNa4uAL
2026-06-01 21:00:04 +00:00
.github Need is_trusted=True for the counters demo 2026-05-26 15:20:29 -07:00
datasette Add web UI to edit and delete stored queries 2026-06-01 21:00:04 +00:00
demos Fixed an unnecessary f-string 2024-02-04 10:15:21 -08:00
docs Add web UI to edit and delete stored queries 2026-06-01 21:00:04 +00:00
tests Add web UI to edit and delete stored queries 2026-06-01 21:00:04 +00:00
.coveragerc Configure code coverage, refs #841, #843 2020-06-13 13:48:23 -07:00
.dockerignore Build Dockerfile with SpatiaLite 5, refs #1249 2021-03-26 21:27:40 -07:00
.git-blame-ignore-revs Ignore Black commits in git blame, refs #1716 2022-04-22 14:58:46 -07:00
.gitattributes New explicit versioning mechanism 2020-10-28 20:38:15 -07:00
.gitignore Fix filter-input and search-input zoom on iOS Safari 2026-01-28 18:41:58 -08:00
.isort.cfg Used isort to re-order my imports 2018-05-14 00:04:23 -03:00
.prettierrc .prettierrc, refs #1166 2020-12-31 13:25:44 -08:00
.readthedocs.yaml dependency-groups and uv (#2611) 2025-12-11 17:32:58 -08:00
CODE_OF_CONDUCT.md Add code of conduct again 2022-03-15 08:38:42 -07:00
codecov.yml codecov should not be blocking 2020-07-02 21:29:32 -07:00
Dockerfile Upgrade Docker images to Python 3.11, closes #1853 2022-10-25 12:04:53 -07:00
Justfile Switch to ruff and fix all lint errors, refs #2630 2026-01-23 20:43:16 -08:00
LICENSE Initial commit 2017-10-22 17:39:03 -07:00
MANIFEST.in Include LICENSE in sdist (#1043) 2020-10-23 13:54:34 -07:00
package-lock.json Bump rollup from 3.29.5 to 3.30.0 (#2651) 2026-03-30 10:54:48 -07:00
package.json Bump rollup from 3.29.5 to 3.30.0 (#2651) 2026-03-30 10:54:48 -07:00
pyproject.toml Bump Black to black==26.3.1 2026-05-20 12:18:01 -07:00
pytest.ini New allowed_resources_sql plugin hook and debug tools (#2505) 2025-10-08 14:27:51 -07:00
README.md Replace Glitch with Codespaces, closes #2488 2025-05-28 19:17:22 -07:00
ruff.toml Use ruff to upgrade Optional[x] to x | None 2025-10-26 10:50:29 -07:00
setup.cfg Switch to ruff and fix all lint errors, refs #2630 2026-01-23 20:43:16 -08:00
test-in-pyodide-with-shot-scraper.sh Introduce new /$DB/-/query endpoint, soft replaces /$DB?sql=... (#2363) 2024-07-15 10:33:51 -07:00

Datasette

PyPI Changelog Python 3.x Tests Documentation Status License docker: datasette discord

An open source multi-tool for exploring and publishing data

Datasette is a tool for exploring and publishing data. It helps people take data of any shape or size and publish that as an interactive, explorable website and accompanying API.

Datasette is aimed at data journalists, museum curators, archivists, local governments, scientists, researchers and anyone else who has data that they wish to share with the world.

Explore a demo, watch a video about the project or try it out on GitHub Codespaces.

Want to stay up-to-date with the project? Subscribe to the Datasette newsletter for tips, tricks and news on what's new in the Datasette ecosystem.

Installation

If you are on a Mac, Homebrew is the easiest way to install Datasette:

brew install datasette

You can also install it using pip or pipx:

pip install datasette

Datasette requires Python 3.8 or higher. We also have detailed installation instructions covering other options such as Docker.

Basic usage

datasette serve path/to/database.db

This will start a web server on port 8001 - visit http://localhost:8001/ to access the web interface.

serve is the default subcommand, you can omit it if you like.

Use Chrome on OS X? You can run datasette against your browser history like so:

 datasette ~/Library/Application\ Support/Google/Chrome/Default/History --nolock

Now visiting http://localhost:8001/History/downloads will show you a web interface to browse your downloads data:

Downloads table rendered by datasette

metadata.json

If you want to include licensing and source information in the generated datasette website you can do so using a JSON file that looks something like this:

{
    "title": "Five Thirty Eight",
    "license": "CC Attribution 4.0 License",
    "license_url": "http://creativecommons.org/licenses/by/4.0/",
    "source": "fivethirtyeight/data on GitHub",
    "source_url": "https://github.com/fivethirtyeight/data"
}

Save this in metadata.json and run Datasette like so:

datasette serve fivethirtyeight.db -m metadata.json

The license and source information will be displayed on the index page and in the footer. They will also be included in the JSON produced by the API.

datasette publish

If you have Heroku or Google Cloud Run configured, Datasette can deploy one or more SQLite databases to the internet with a single command:

datasette publish heroku database.db

Or:

datasette publish cloudrun database.db

This will create a docker image containing both the datasette application and the specified SQLite database files. It will then deploy that image to Heroku or Cloud Run and give you a URL to access the resulting website and API.

See Publishing data in the documentation for more details.

Datasette Lite

Datasette Lite is Datasette packaged using WebAssembly so that it runs entirely in your browser, no Python web application server required. Read more about that in the Datasette Lite documentation.