datasette README

The project's README from github.com/simonw/datasette. As one markdown file: README.md.

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.

datasette (simonw/datasette)

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11.5K ·GitHub
Datasette
What is this?Datasette is an open-source multi-tool for exploring and publishing data: point it at a SQLite database and it turns the data into an interactive, browsable website with an accompanying JSON API.
Is this a command-line tool, a web app, or both?It's a CLI tool you run locally — `datasette serve path/to/database.db` — which then spins up a web server giving you both a browsable UI and a JSON API for that database.
How do I install it and get a database running?On a Mac you can `brew install datasette`, or use `pip install datasette`/pipx anywhere else, then run `datasette serve path/to/database.db` to browse it at the local web server.
Do I need Python installed first?Yes, Datasette requires Python 3.8 or higher if you install via pip/pipx (the Homebrew and Docker installs bundle this for you).
Does it work with any database, or only SQLite?Datasette is built specifically around SQLite databases — you point it at `.db` files rather than connecting to Postgres/MySQL servers.
Who is this aimed at?It's aimed at data journalists, museum curators, archivists, local governments, scientists, researchers, and anyone else who has data they want to share publicly.
How do I publish my data to the internet instead of just running it locally?The `datasette publish` command deploys a Docker image containing Datasette plus your SQLite file straight to Heroku or Google Cloud Run with a single command, giving you a live URL and API.
What is Datasette Lite?It's Datasette compiled to WebAssembly so it runs entirely inside your browser, with no Python server required at all.
How do I add licensing and source credits to my published site?Create a metadata.json file with title, license, licenseurl, source and sourceurl fields and pass it with `-m metadata.json`; the info shows up on the site's footer and in the API output.
Can I use it on data I already have, like my browser history?Yes — for example you can run `datasette ~/Library/Application Support/Google/Chrome/Default/History --nolock` to browse your own Chrome history as an example dataset.
What are similar projects?nocodb, postgrest, duckdb, prediction-market-analysis, q, visidata, redash, capcut-mate
Which topics is it in?asgi, automatic-api, datasets, csv, wasm, sql, data-science, json, sqlite, rest-api, database, command-line-tool
Creator
simonw
Size
11.1 MB
Stars
11.5K
Updated
CommitOct 12Release0.65.5Sep 16
Age
8y
Commits · 90 Days