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](https://fivethirtyeight.datasettes.com/fivethirtyeight), watch [a video about the project](https://www.youtube.com/watch?v=pTr1uLQTJNE) or try it out by [uploading and publishing your own CSV data](https://simonwillison.net/2019/Apr/23/datasette-glitch/).
* 21st May 2019: The anonymized raw data from [the Stack Overflow Developer Survey 2019](https://stackoverflow.blog/2019/05/21/public-data-release-of-stack-overflows-2019-developer-survey/) has been [published in partnership with Glitch](https://glitch.com/culture/discover-insights-explore-developer-survey-results-2019/), powered by Datasette.
* 19th May 2019: [Datasette 0.28](https://datasette.readthedocs.io/en/stable/changelog.html#v0-28) - a salmagundi of new features!
* No longer immutable! Datasette now supports [databases that change](https://datasette.readthedocs.io/en/stable/changelog.html#supporting-databases-that-change).
* [Faceting improvements](https://datasette.readthedocs.io/en/stable/changelog.html#faceting-improvements-and-faceting-plugins) including facet-by-JSON-array and the ability to define custom faceting using plugins.
* [datasette publish cloudrun](https://datasette.readthedocs.io/en/stable/changelog.html#datasette-publish-cloudrun) lets you publish databases to Google's new Cloud Run hosting service.
* New [register_output_renderer](https://datasette.readthedocs.io/en/stable/changelog.html#register-output-renderer-plugins) plugin hook for adding custom output extensions to Datasette in addition to the default `.json` and `.csv`.
* Dozens of other smaller features and tweaks - see [the release notes](https://datasette.readthedocs.io/en/stable/changelog.html#v0-28) for full details.
* Read more about this release here: [Datasette 0.28—and why master should always be releasable](https://simonwillison.net/2019/May/19/datasette-0-28/)
sqlite-utils: a Python library and CLI tool for building SQLite databases](https://simonwillison.net/2019/Feb/25/sqlite-utils/) - a partner tool for easily creating SQLite databases for use with Datasette.
* 2nd January 2019: [Datasette 0.26](http://datasette.readthedocs.io/en/latest/changelog.html#v0-26) - minor bug fixes, `datasette publish now --alias` argument.
* 18th December 2018: [Fast Autocomplete Search for Your Website](https://24ways.org/2018/fast-autocomplete-search-for-your-website/) - a new tutorial on using Datasette to build a JavaScript autocomplete search engine.
* 3rd October 2018: [The interesting ideas in Datasette](https://simonwillison.net/2018/Oct/4/datasette-ideas/) - a write-up of some of the less obvious interesting ideas embedded in the Datasette project.
* 19th September 2018: [Datasette 0.25](http://datasette.readthedocs.io/en/latest/changelog.html#v0-25) - New plugin hooks, improved database view support and an easier way to use more recent versions of SQLite.
* 18th June 2018: [Datasette 0.23: CSV, SpatiaLite and more](http://datasette.readthedocs.io/en/latest/changelog.html#v0-23) - CSV export, foreign key expansion in JSON and CSV, new config options, improved support for SpatiaLite and a bunch of other improvements
* 23rd May 2018: [Datasette 0.22.1 bugfix](https://github.com/simonw/datasette/releases/tag/0.22.1) plus we now use [versioneer](https://github.com/warner/python-versioneer)
* 25th April 2018: [Exploring the UK Register of Members Interests with SQL and Datasette](https://simonwillison.net/2018/Apr/25/register-members-interests/) - a tutorial describing how [register-of-members-interests.datasettes.com](https://register-of-members-interests.datasettes.com/) was built ([source code here](https://github.com/simonw/register-of-members-interests))
* 20th April 2018: [Datasette plugins, and building a clustered map visualization](https://simonwillison.net/2018/Apr/20/datasette-plugins/) - introducing Datasette's new plugin system and [datasette-cluster-map](https://pypi.org/project/datasette-cluster-map/), a plugin for visualizing data on a map
* 28th March 2018: [Baltimore Sun Public Salary Records](https://simonwillison.net/2018/Mar/28/datasette-in-the-wild/) - a data journalism project from the Baltimore Sun powered by Datasette - source code [is available here](https://github.com/baltimore-sun-data/salaries-datasette)
* 27th March 2018: [Cloud-first: Rapid webapp deployment using containers](https://wwwf.imperial.ac.uk/blog/research-software-engineering/2018/03/27/cloud-first-rapid-webapp-deployment-using-containers/) - a tutorial covering deploying Datasette using Microsoft Azure by the Research Software Engineering team at Imperial College London
* 28th January 2018: [Analyzing my Twitter followers with Datasette](https://simonwillison.net/2018/Jan/28/analyzing-my-twitter-followers/) - a tutorial on using Datasette to analyze follower data pulled from the Twitter API
* 17th January 2018: [Datasette Publish: a web app for publishing CSV files as an online database](https://simonwillison.net/2018/Jan/17/datasette-publish/)
* 12th December 2017: [Building a location to time zone API with SpatiaLite, OpenStreetMap and Datasette](https://simonwillison.net/2017/Dec/12/building-a-location-time-zone-api/)
Datasette requires Python 3.5 or higher. We also have [detailed installation instructions](https://datasette.readthedocs.io/en/stable/installation.html) covering other options such as Docker.
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:
If you have [Heroku](https://heroku.com/), [Google Cloud Run](https://cloud.google.com/run/) or [Zeit Now v1](https://zeit.co/now) configured, Datasette can deploy one or more SQLite databases to the internet with a single command:
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.