Datasette

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 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 by uploading and publishing your own CSV data.

datasette.io is the official project website
Latest Datasette News
Comprehensive documentation: https://docs.datasette.io/
Examples: https://datasette.io/examples
Live demo of current main: https://latest.datasette.io/
Support questions, feedback? Join our GitHub Discussions forum

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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 3.6 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

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

datasette serve options

Usage: datasette serve [OPTIONS] [FILES]...

  Serve up specified SQLite database files with a web UI

Options:
  -i, --immutable PATH      Database files to open in immutable mode
  -h, --host TEXT           Host for server. Defaults to 127.0.0.1 which means
                            only connections from the local machine will be
                            allowed. Use 0.0.0.0 to listen to all IPs and
                            allow access from other machines.
  -p, --port INTEGER        Port for server, defaults to 8001
  --reload                  Automatically reload if code or metadata change
                            detected - useful for development
  --cors                    Enable CORS by serving Access-Control-Allow-
                            Origin: *
  --load-extension PATH     Path to a SQLite extension to load
  --inspect-file TEXT       Path to JSON file created using "datasette
                            inspect"
  -m, --metadata FILENAME   Path to JSON file containing license/source
                            metadata
  --template-dir DIRECTORY  Path to directory containing custom templates
  --plugins-dir DIRECTORY   Path to directory containing custom plugins
  --static STATIC MOUNT     mountpoint:path-to-directory for serving static
                            files
  --memory                  Make /_memory database available
  --config CONFIG           Set config option using configname:value
                            docs.datasette.io/en/stable/config.html
  --version-note TEXT       Additional note to show on /-/versions
  --help-config             Show available config options
  --help                    Show this message and exit.

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.