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A tool for exploring and publishing data
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PyPI Python 3.x Travis CI Documentation Status License Code style: black docker: datasette

A 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.



pip3 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:

Downloads table rendered by datasette

datasette serve options

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

  Serve up specified SQLite database files with a web UI

  -i, --immutable PATH      Database files to open in immutable mode
  -h, --host TEXT           Host for server. Defaults to which means
                            only connections from the local machine will be
                            allowed. Use to listen to all IPs and
                            allow access from other machines.
  -p, --port INTEGER        Port for server, defaults to 8001
  --debug                   Enable debug mode - useful for development
  --reload                  Automatically reload if database or code 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
  -m, --metadata FILENAME   Path to JSON file containing license/source
  --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
  --memory                  Make :memory: database available
  --config CONFIG           Set config option using configname:value
  --version-note TEXT       Additional note to show on /-/versions
  --help-config             Show available config options
  --help                    Show this message and exit.


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": "",
    "source": "fivethirtyeight/data on GitHub",
    "source_url": ""

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, Google Cloud Run or Zeit Now v1 configured, Datasette can deploy one or more SQLite databases to the internet with a single command:

datasette publish heroku database.db


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.

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