Bots: advanced features

These are advanced features that are mostly unsupported in oTree Studio.

Command line bots

An alternative to running bots in your web browser is to run them in the command line. Command line bots run faster and require less setup.

Run this:

otree test mysession

To test with a specific number of participants (otherwise it will default to num_demo_participants):

otree test mysession 6

To run tests for all session configs:

otree test

Exporting data

Use the --export flag to export the results to a CSV file:

otree test mysession --export

To specify the folder where the data is saved, do:

otree test mysession --export=myfolder

Command-line browser bots

You can launch browser bots from the command line, using otree browser_bots.

  • Make sure Google Chrome is installed, or set BROWSER_COMMAND in settings.py (more info below).

  • Set OTREE_REST_KEY env var as described in REST.

  • Run your server

  • Close all Chrome windows.

  • Run this:

    otree browser_bots mysession
    

This will launch several Chrome tabs and run the bots. When finished, the tabs will close, and you will see a report in your terminal window.

If Chrome doesn’t close windows properly, make sure you closed all Chrome windows prior to launching the command.

Command-line browser bots on a remote server (e.g. Heroku)

If the server is running on a host/port other than the usual http://localhost:8000, you need to pass --server-url. For example, if it’s on Heroku, you would do like this:

otree browser_bots mysession --server-url=https://YOUR-SITE.herokuapp.com

Choosing session configs and sizes

You can specify the number of participants:

otree browser_bots mysession 6

To test all session configs, just run this:

otree browser_bots

Browser bots: misc notes

You can use a browser other than Chrome by setting BROWSER_COMMAND in settings.py. Then, oTree will open the browser by doing something like subprocess.Popen(settings.BROWSER_COMMAND).

Test cases

You can define an attribute cases on your PlayerBot class that lists different test cases. For example, in a public goods game, you may want to test 3 scenarios:

  • All players contribute half their endowment
  • All players contribute nothing
  • All players contribute their entire endowment (100 points)

We can call these 3 test cases “basic”, “min”, and “max”, respectively, and put them in cases. Then, oTree will execute the bot 3 times, once for each test case. Each time, a different value from cases will be assigned to self.case in the bot.

For example:

class PlayerBot(Bot):

    cases = ['basic', 'min', 'max']

    def play_round(self):
        yield (pages.Introduction)

        if self.case == 'basic':
            assert self.player.payoff == None

        if self.case == 'basic':
            if self.player.id_in_group == 1:
                for invalid_contribution in [-1, 101]:
                    yield SubmissionMustFail(pages.Contribute, {'contribution': invalid_contribution})
        contribution = {
            'min': 0,
            'max': 100,
            'basic': 50,
        }[self.case]

        yield (pages.Contribute, {"contribution": contribution})
        yield (pages.Results)

        if self.player.id_in_group == 1:

            if self.case == 'min':
                expected_payoff = 110
            elif self.case == 'max':
                expected_payoff = 190
            else:
                expected_payoff = 150
            assert self.player.payoff == expected_payoff

Note

If you use cases, it’s better to use Command line bots since browser bots will only execute a single case.

cases needs to be a list, but it can contain any data type, such as strings, integers, or even dictionaries. Here is a trust game bot that uses dictionaries as cases.

class PlayerBot(Bot):

    cases = [
        {'offer': 0, 'return': 0, 'p1_payoff': 10, 'p2_payoff': 0},
        {'offer': 5, 'return': 10, 'p1_payoff': 15, 'p2_payoff': 5},
        {'offer': 10, 'return': 30, 'p1_payoff': 30, 'p2_payoff': 0}
    ]

    def play_round(self):
        case = self.case
        if self.player.id_in_group == 1:
            yield (pages.Send, {"sent_amount": case['offer']})

        else:
            for invalid_return in [-1, case['offer'] * C.MULTIPLICATION_FACTOR + 1]:
                yield SubmissionMustFail(pages.SendBack, {'sent_back_amount': invalid_return})
            yield (pages.SendBack, {'sent_back_amount': case['return']})

        yield (pages.Results)


        if self.player.id_in_group == 1:
            expected_payoff = case['p1_payoff']
        else:
            expected_payoff = case['p2_payoff']

        assert self.player.payoff == expected_payoff

error_fields

When using SubmissionMustFail on forms with multiple fields, you can use error_fields for extra thoroughness.

For example, let’s say we a submit a valid age, but an invalid weight and height:

yield SubmissionMustFail(
    pages.Survey,
    dict(
        age=20,
        weight=-1,
        height=-1,
    )
)

What’s missing is that the bot system doesn’t tell us exactly why the submission fails. Is it an invalid weight, height, or both? error_fields can resolve the ambiguity:

yield SubmissionMustFail(
    pages.Survey,
    dict(
        age=20,
        weight=-1,
        height=-1,
    ),
    error_fields=['weight', 'height']
)

This will verify that weight and height contained errors, but age did not.

If error_message returns an error, then error_fields will be ['__all__'].

Misc note

In bots, it is risky to assign player = self.player (or participant = self.participant, etc), even though that kind of code is encouraged elsewhere.

Because if there is a yield in between, the data can be stale:

player = self.player
expect(player.money_left, cu(10))
yield pages.Contribute, dict(contribution=cu(1))
# don't do this!
# "player" variable still has the data from BEFORE pages.Contribute was submitted.
expect(player.money_left, cu(9))

It’s safer to use self.player.money_left directly, because doing self.player gets the most recent data from the database.

Live pages

To test live methods with bots, define call_live_method as a top-level function in tests.py. (Not available in oTree Studio.) This function should simulate the sequence of calls to your live_method. The argument method simulates the live method on your Player model. For example, method(3, 'hello') calls the live method on Player 3 with data set to 'hello'. For example:

def call_live_method(method, **kwargs):
    method(1, {"offer": 50})
    method(2, {"accepted": False})
    method(1, {"offer": 60})
    retval = method(2, {"accepted": True})
    # you can do asserts on retval

kwargs contains at least the following parameters.

  • case as described in Test cases.
  • page_class: the current page class, e.g. pages.MyPage.
  • round_number

call_live_method will be automatically executed when the fastest bot in the group arrives on a page with live_method. (Other bots may be on previous pages at that point, unless you restrict this with a WaitPage.)