An open source multi-tool for exploring and publishing data https://datasette.io
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Claude 0679e04bd3
Unify JSON error responses into one canonical shape
All JSON error responses now use a single format built by the new
datasette.utils.error_body() helper:

    {"ok": false, "error": "...", "errors": ["..."], "status": 400}

- error is all messages joined with '; ', errors is the full list,
  status always matches the HTTP status code
- The exception handler no longer emits the legacy title key in JSON
  (it is still available to the HTML error template)
- The permission debug endpoints (/-/allowed, /-/rules, /-/check,
  POST /-/permissions) no longer return bare {"error": ...} objects
- JSON renderer SQL errors keep their rows/truncated context keys but
  now include the canonical keys as well
- _shape=object misuse (queries or tables without primary keys) now
  returns HTTP 400 instead of 200 with an error body
- Method-not-allowed 405 responses use the canonical shape

Adds tests/test_error_shape.py covering all four previous shape
producers, updates affected tests, and documents the format in a new
'Error responses' section of docs/json_api.rst.

Implements section 1 of stable-api-recommendations.md.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01GrHZSypDfMnym1tM5XJAFZ
2026-07-04 03:12:15 +00:00
.github Stop matrix testing against sqlite-utils 4.0rc1 2026-06-22 09:06:00 -07:00
datasette Unify JSON error responses into one canonical shape 2026-07-04 03:12:15 +00:00
demos Fixed an unnecessary f-string 2024-02-04 10:15:21 -08:00
docs Unify JSON error responses into one canonical shape 2026-07-04 03:12:15 +00:00
tests Unify JSON error responses into one canonical shape 2026-07-04 03:12:15 +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 Ignore ignored/ directory 2026-06-25 21:20:29 -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
existing-api.md Unify JSON error responses into one canonical shape 2026-07-04 03:12:15 +00:00
Justfile Just recipes for running Playwright tests 2026-06-16 13:35:17 -07:00
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 sqlite-utils>=3.30,<4.0 2026-06-22 11:03:49 -07:00
pytest.ini Initial Playwright setup plus first test 2026-06-14 16:39:55 -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
stable-api-recommendations.md Unify JSON error responses into one canonical shape 2026-07-04 03:12:15 +00:00
test-in-pyodide-with-shot-scraper.sh Test against pyodide/v314.0.0 2026-06-22 10:11:56 -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.