An open source multi-tool for exploring and publishing data https://datasette.io
  • Python 84.1%
  • HTML 7.2%
  • JavaScript 6.6%
  • CSS 1.8%
  • Shell 0.2%
Find a file
Simon Willison f1af216852
Insert/edit/delete UI in Datasette core, plus makeColumnField() plugin hook
PR #2781

- A new `/db/table/-/autocomplete?q=term` JSON API for fast autocomplete search against foreign key tables - it searches against their label column or their primary key and switches to just a prefix search against the first primary key (for speed) if the label column check takes more than 500ms. A new `/-/debug/autocomplete` page lets you try this out.
- A `<datasette-autocomplete>` Web Component that uses that API.
- Table pages now get an insert button above the table, and little edit and delete icons next to each row. All three trigger custom modal dialogs. The edit/insert dialog is a full form - the delete one is just confirmation.
- A new `/<database>/<table>/-/fragment?_row=` endpoint which returns a rendered fragment of HTML for the specified row. This is used by the insert/edit code to partially update the table to reflect those changes. Uses a new `data-row="{{ row.row_path }}"` attribute on the `<tr>` to enable the replacement.
- A new default column type called `textarea` which users can use to specify a multi-line textarea for a column
- A new JavaScript plugin hook, [makeColumnField()](3f7d389caf/docs/javascript_plugins.rst (makecolumnfieldcontext)), which plugins can use to add custom form fields to the edit form. Datasette [uses this itself](3f7d389caf/datasette/static/table.js (L1181-L1209)) for the JSON field to add client-side JSON validation. I iterated a *lot* on this one, including spinning up a `datasette-prosemirror` plugin and a branch of `datasette-files` to fully exercise it.

Closes #2780

Video demo: https://github.com/user-attachments/assets/2c18b8a4-975f-4c7b-9573-ec6040fe8223
2026-06-14 16:14:14 -07:00
.github Need is_trusted=True for the counters demo 2026-05-26 15:20:29 -07:00
datasette Ran prettier 2026-06-14 16:06:36 -07:00
demos Fixed an unnecessary f-string 2024-02-04 10:15:21 -08:00
docs Support for <button> items in action menus 2026-06-14 15:58:37 -07:00
tests Refactor edit/delete tools to work on row pages too 2026-06-14 16:05:42 -07:00
.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 Ignore .playwright-mcp 2026-06-14 14:21:04 -07:00
.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 Use asyncinject 0.7 results= seeding for per-request extras context 2026-06-11 06:42:08 -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.