Writing bots

When you run an experiment using the bot recruiter, it will look for a class named Bot in your experiment.py module.

The Bot class should typically be a subclass of either BotBase (for bots that interact with the experiment by controlling a real browser using selenium) or HighPerformanceBotBase (for bots that interact with the experiment server directly via HTTP or websockets).

The interaction of the base bots with the experiment takes place in several phases:

  1. Signup (including creating a Participant)
  2. Participation in the experiment
  3. Signoff (including completing the questionnaire)
  4. Recording completion (complete or failed)

To build a bot, you will definitely need to implement the participate method which will be called once the bot has navigated to the main experiment page. If the structure of your ad, consent, instructions or questionnaire pages differs significantly from the demo experiments, you may need to override other methods too.

High-performance bots

The HighPerformanceBotBase can be used as a basis for a bot that interacts with the experiment server directly over HTTP rather than using a real browser. This scales better than using Selenium bots, but requires expressing the bot’s behavior in terms of HTTP requests rather than in terms of DOM interactions.

For a guide to Dallinger’s web API, see Web API.

For an example of a high-performance bot implementation, see the Griduniverse bots. These bots interact primarily via websockets rather than HTTP.

API documentation

class dallinger.bots.HighPerformanceBotBase(URL, assignment_id='', worker_id='', participant_id='', hit_id='')[source]

A base class for bots that do not interact using a real browser.

Instead, this kind of bot makes requests directly to the experiment server.


Record worker completion status to the experiment server.

This is done using a GET request to the /worker_complete or /worker_failed endpoints.


Runs the phases of interacting with the experiment including signup, participation, signoff, and recording completion.


Submit questionnaire and finish.

This is done using a POST request to the /question/ endpoint.


Signs up a participant for the experiment.

This is done using a POST request to the /participant/ endpoint.

Selenium bots

The BotBase provides a basis for a bot that interacts with an experiment using Selenium, which means that a separate, real browser session is controlled by each bot. This approach does not scale very well because there is a lot of overhead to running a browser, but it does allow for interacting with the experiment in a way similar to real participants.

By default, Selenium will try to run PhantomJS, a headless browser meant for scripting. However, it also supports using Firefox and Chrome through configuration variables.

webdriver_type = firefox

We recommend using Firefox when writing bots, as it allows you to visually see its output and allows you to attach the development console directly to the bot’s browser session.

For an example of a selenium bot implementation, see the Bartlett1932 bots.

For documentation of the Python Selenium WebDriver API, see Selenium with Python.

API documentation

class dallinger.bots.BotBase(URL, assignment_id='', worker_id='', participant_id='', hit_id='')[source]

A base class for bots that works with the built-in demos.

This kind of bot uses Selenium to interact with the experiment using a real browser.


Sends worker status (‘worker_complete’ or ‘worker_failed’) to the experiment server.


Complete the standard debriefing form.

This does nothing unless overridden by a subclass.


Returns a Selenium WebDriver instance of the type requested in the configuration.


Participate in the experiment.

This method must be implemented by subclasses of BotBase.


Sign up, run the participate method, then sign off and close the driver.


Submit questionnaire and finish.

This uses Selenium to click the submit button on the questionnaire and return to the original window.


Accept HIT, give consent and start experiment.

This uses Selenium to click through buttons on the ad, consent, and instruction pages.

Scaling Selenium bots

For example you may want to run a dedicated computer on your lab network to host bots, without slowing down experimenter computers. It is recommended that you run Selenium in a hub configuration, as a single Selenium instance will limit the number of concurrent sessions.

You can also provide a URL to a Selenium WebDriver instance using the webdriver_url configuration setting. This is required if you’re running Selenium in a hub configuration. The hub does not need to be on the same computer as Dallinger, but it does need to be able to access the computer running Dallinger directly by its IP address.

On Apple macOS, we recommend using Homebrew to install and run selenium, using:

brew install selenium-server-standalone
selenium-server -port 4444

On other platforms, download the latest selenium-server-standalone.jar file from SeleniumHQ and run a hub using:

java -jar selenium-server-standalone-3.3.1.jar -role hub

and attach multiple nodes by running:

java -jar selenium-server-standalone-3.3.1.jar -role node -hub http://hubcomputer.example.com:4444/grid/register

These nodes may be on other computers on the local network or on the same host machine. If they are on the same host you will need to add -port 4446 (for some port number) such that each Selenium node on the same server is listening on a different port.

You will also need to set up the browser interfaces on each computer that’s running a node. This requires being able to run the browser and having the correct driver available in the system path, so the Selenium server can run it.

We recommend using Chrome when running large numbers of bots, as it is more feature-complete than PhantomJS but with better performance at scale than Firefox. It is best to run at most three Firefox sessions on commodity hardware, so for best results 16 bots should be run over 6 Selenium servers. This will depend on how processor intensive your experiment is. It may be possible to run more sessions without performance degradation.