Databench is a Python package that you can install using pip:

$ pip install databench

It provides the executables scaffold-databench and databench, Python modules for the backend and a JavaScript library for the frontend. scaffold-databench helloworld creates an analysis template called helloworld in the current working directory. Running databench creates a local web server which you can access at http://localhost:5000. A good way to start is to jump right into Quickstart.

Some features are shown in the live demos. They do not include examples with matplotlib, parallelization or database interfaces (like asynchronously subscribing to a Redis channel) but those examples are available in the databench_examples repository.

Preview of flowers demo. Preview of bag-of-chars demo. Preview of simplepi demo.

The live demos and databench_examples also show seemless integration with markdown and MathJax as well as with angular.js.


The GitHub page provides a few ways for feedback in terms of Issues and Pull Requests and I am happy to receive and incorporate those. Or you can send me an email.


Databench was written by Sven Kreiss and made available under the MIT license.