Dallinger is a tool to automate experiments that use combinations of automated bots and human subjects recruited on platforms like Mechanical Turk.

Dallinger allows crowd sourced experiments to be abstracted into single function calls that can be inserted into higher-order algorithms. It fully automates the process of recruiting participants, obtaining informed consent, arranging participants into a network, running the experiment, coordinating communication, recording and managing the data, and paying the participants.

The Dallinger technology stack consists of: Python, Redis, Web Sockets, Heroku, AWS, Mechanical Turk, boto, Flask, PostgreSQL, SQLAlchemy, Gunicorn, Pytest and gevent among others.

User Documentation

These documentation topics are intended to assist people who are attempting to launch experiments and analyse their data. They cover the basics of installing and setting up Dallinger, as well as use of the command line tools.

Beginner Documentation

Many Dallinger users may not have lots of programming experience, and might want a bit more information about the inner workings of Dallinger in a beginner-friendly format. Thomas Morgan has started such a project: “Dallinger for Programming Novices”. Every Dallinger user is encouraged to take a look at this guide, which is a nice complement to the documentation presented here.

Beginner Documentation

Dallinger Demos

Several demos demonstrate Dallinger in action:

Dallinger Demos

Experiment Author Documentation

These documentation topics build on the previous set to include help with designing new experiments for others to use.

Core Contribution Documentation

This section covers extra topics relevant to those wishing to contribute to the development of Dallinger itself. This is not needed in order to develop new experiments. Follow the Developer Installation process from the previous section to get started.

General Information