March 2021, Markus Konrad [email protected] / [email protected] / Berlin Social Science Center
This project is currently not maintained.
This repository contains the package otreeutils
. It features a set of common helper / utility functions and classes often needed when developing experiments with oTree. So far, this covers the following use cases:
- Easier creation of surveys:
- define all survey questions in a single data structure, let
otreeutils
create the requiredPlayer
fields - create a table of Likert scale inputs ("Likert matrix")
- create single Likert scale fields from given labels
- easy survey forms styling via CSS due to cleanly structured HTML output
- make survey forms with conditional inputs
- define all survey questions in a single data structure, let
- Extensions to oTree's admin interface for using custom data models, which include:
- Live session data view shows data from custom models
- Export page allows download of complete data with data from custom models
- Export page allows download in nested JSON format
- Displaying and validating understanding questions
- Displaying warnings to participants when a timeout occurs on a page (no automatic form submission after timeout)
- More convenient development process by optional automatic fill-in of forms (saves you from clicking through many inputs during development)
- Setting custom URLs for pages (instead of default: the page's class name)
This screenshot shows an example survey page with a Likert matrix:
The package is available on PyPI and can be installed via pip install otreeutils
.
Compatibility note: This package is compatible with oTree v3.3.x. If you have an older oTree version, check out the CHANGES file to see which version is compatible with your oTree version. You can install the exact version then with pip install otreeutils==x.y.z
where x.y.z
denotes an otreeutils version number.
If you used otreeutils in your published research, please cite it as follows:
The repository contains three example apps which show the respective features and how they can be used in own experiments:
otreeutils_example1
-- Understanding questions and timeout warningsotreeutils_example2
-- Surveysotreeutils_example3_market
-- Market: An example showing custom data models to collect a dynamically determined data quantity. Shows how otreeutils' admin extensions allow live data view and data export for these requirements. Companion code for Konrad 2018. See its dedicated README page.
The admin interface extensions have still a limitation: Data export with all data from custom models is only possible with per app download option, not with the "all apps" option.
This package requires oTree v3.3.x and optionally pandas. The requirements will be installed along with otreeutils when using pip
(see below).
In order to use otreeutils in your experiment implementation, you only need to do the following things:
- Either install the package from PyPI via pip (
pip install otreeutils
) or download/clone this github repository and copy theotreeutils
folder to your oTree experiment directory. - Edit your
settings.py
so that you add "otreeutils" to yourINSTALLED_APPS
list. Don't forget this, otherwise the required templates and static files cannot be loaded correctly!
It's best to have a look at the (documented) examples to see how to use the API.
A common page extension to oTree's default Page
class.
All other page classes in otreeutils
extend this class. Allows to define a custom page URL via custom_name_in_url
, timeout warnings, a page title and provides a template variable debug
with which you can toggle debug code in your templates / JavaScript parts.
The template variable debug
(integer – 0 or 1) is toggled using an additional APPS_DEBUG
variable in settings.py
. See the settings.py
of this repository. This is quite useful for example in order to fill in the correct questions on a page with understanding questions automatically in a debug session (so that it is easier to click through the pages).
There is also a page variable debug_fill_forms_randomly
, which can be set for any page derived from the ExtendedPage
class (i.e. also for survey pages -- see below). If you set this variable to True
, then all form inputs on the page are automatically filled in with random values once you visit the page. This happens when you run the experiment in "debug mode", i.e. when APPS_DEBUG
is set to True
. By default, debug_fill_forms_randomly
is set to False
. You can enable this feature for a given page like this:
from otreeutils.pages import ExtendedPage
class MyPage(ExtendedPage):
debug_fill_forms_randomly = True
This saves time when you click through an experiment with many complex forms.
Base class to implement understanding questions. A participant must complete all questions in order to proceed. You can display hints. Use it as follows:
from otreeutils.pages import UnderstandingQuestionsPage
class SomeUnderstandingQuestions(UnderstandingQuestionsPage):
page_title = 'Set a page title'
questions = [
{
'question': 'What is π?',
'options': [1.2345, 3.14159],
'correct': 3.14159,
'hint': 'You can have a look at Wikipedia!' # this is optional
},
# ...
]
By default, the performance of the participant is not recorded, but you can optionally provide a form_model
and set a field in form_field_n_wrong_attempts
which defines in which field the number of wrong attempts is written.
If you set APPS_DEBUG
to True
, the correct answers will already be filled in order to skip swiftly through pages during development.
This function allows to dynamically create a Player
model class for a survey. It can be used as follows in models.py
.
At first you define your questions per page in a survey definitions data structure, for example like this:
from otreeutils.surveys import create_player_model_for_survey
GENDER_CHOICES = (
('female', 'Female'),
('male', 'Male'),
('no_answer', 'Prefer not to answer'),
)
SURVEY_DEFINITIONS = {
'SurveyPage1': {
'page_title': 'Survey Questions - Page 1',
'survey_fields': [
('q1_a', { # field name (which will also end up in your "Player" class and hence in your output data)
'text': 'How old are you?', # survey question
'field': models.PositiveIntegerField(min=18, max=100), # the same as in normal oTree model field definitions
}),
('q1_b', {
'text': 'Please tell us your gender.',
'field': models.CharField(choices=GENDER_CHOICES),
}),
# ... more questions
]
},
# ... more pages
}
Note how SURVEY_DEFINITIONS
is a dictionary which maps pages to the survey questions that should appear on each page. We will later create a SurveyPage1
page class in pages.py
.
Now you create the Player
class by passing the name of the module for which it will be created. This should be the models
module of your app, so in your case this is 'survey.models'
if your app is named survey
. The second parameter is the survey definitions that we just created:
Player = create_player_model_for_survey('otreeutils_example2.models', SURVEY_DEFINITIONS)
The attributes (model fields, etc.) will be automatically created. When you run otree resetdb
, you will see that the fields q1_a
, q1_b
, etc. will be generated in the database.
You may also add extra (non-survey) fields to your Player
class, by passing a dict to the optional other_fields
parameter:
Player = create_player_model_for_survey('otreeutils_example2.models', SURVEY_DEFINITIONS, other_fields={
'treatment': models.IntegerField()
})
The function generate_likert_field
allows you to easily generate fields for a given Likert scale and can be used inside a survey definitions data structure:
from otreeutils.surveys import generate_likert_field
likert_5_labels = (
'Strongly disagree', # value: 1
'Disagree', # value: 2
'Neither agree nor disagree', # ...
'Agree',
'Strongly agree' # value: 5
)
likert_5point_field = generate_likert_field(likert_5_labels)
The object likert_5point_field
is now a function to generate new fields of the specified Likert scale:
# ...
SURVEY_DEFINITIONS = {
'SurveyPage2': {
'page_title': 'A Likert 5-point scale example',
'survey_fields': [
('q_otree_surveys', { # most of the time, you'd add a "help_text" for a Likert scale question. You can use HTML:
'help_text': """
<p>Consider this quote:</p>
<blockquote>
"oTree is great to make surveys, too."
</blockquote>
<p>What do you think?</p>
""",
'field': likert_5point_field(), # don't forget the parentheses at the end!
}),
('q_just_likert', {
'label': 'Another Likert scale input:', # optional, no HTML
'field': likert_5point_field(), # don't forget the parentheses at the end!
}),
]
},
# ... more pages
}
The function generate_likert_table
allows you to easily generate a table of Likert scale inputs like a matrix with the Likert scale increments in the columns and your questions in the rows:
# ...
SURVEY_DEFINITIONS = {
'SurveyPage3': {
'page_title': 'A Likert scale table example',
'survey_fields': [
# create a table of Likert scale choices
# we use the same 5-point scale a before and specify four rows for the table,
# each with a tuple (field name, label)
generate_likert_table(likert_5_labels,
[
('q_pizza_tasty', 'Tasty'),
('q_pizza_spicy', 'Spicy'),
('q_pizza_cold', 'Too cold'),
('q_pizza_satiable', 'Satiable'),
],
form_help_initial='<p>How was your latest Pizza?</p>', # HTML to be placed on top of form
form_help_final='<p>Thank you!</p>' # HTML to be placed below form
)
]
},
# ... more pages
}
There are several additional parameters that you can pass to generate_likert_table()
which will control the display and behavior of the table:
table_repeat_header_each_n_rows=<integer>
: set to integer N > 0 to repeat the table header after every N rowstable_cols_equal_width=<True/False>
: adjust form columns so that they have equal widthtable_row_header_width_pct=<number>
: if form columns should have equal width, this specifies the width of the first column (the table row header) in percent (default: 25)table_rows_equal_height=<True/False>
: adjust form rows so that they have equal heighttable_rows_alternate=<True/False>
: alternate form rows between "odd" and "even" CSS classes (alternates background colors)table_rows_randomize=<True/False>
: randomize form rowstable_rows_highlight=<True/False>
: highlight form rows on mouse-overtable_cells_highlight=<True/False>
: highlight form cells on mouse-overtable_cells_clickable=<True/False>
: make form cells clickable for selection (otherwise only the small radio buttons can be clicked)
To implement advanced features such as conditional input display, have a look at the example app otreeutils_example2
.
You can then create the survey pages which will contain the questions for the respective pages as defined before in SURVEY_DEFINITIONS
:
# (in pages.py)
from otreeutils.surveys import SurveyPage, setup_survey_pages
# Create the survey page classes; their names must correspond to the names used in the survey definition
class SurveyPage1(SurveyPage):
pass
class SurveyPage2(SurveyPage):
pass
# more pages ...
# Create a list of survey pages.
survey_pages = [
SurveyPage1,
SurveyPage2,
# more pages ...
]
Since each SurveyPage
is derived from the ExtendedPage
class, you can also enable the automatic fill-in feature. This means that all form inputs on the page are automatically filled in with random values once you visit the page. That happens when you run the experiment in "debug mode", i.e. when APPS_DEBUG
is set to True
. By default, debug_fill_forms_randomly
is set to False
. You can enable this feature for a given survey page like this:
class SurveyPage3(SurveyPage):
debug_fill_forms_randomly = True
This saves time when you click through an experiment with many survey fields.
Now all survey pages need to be set up. The Player
class will be passed to all survey pages and the questions for each page will be set according to their order.
# Common setup for all pages (will set the questions per page)
setup_survey_pages(models.Player, survey_pages)
Finally, we can set the page_sequence
in order to use our survey pages:
page_sequence = [
SurveyIntro, # define some pages that come before the survey
# ...
]
# add the survey pages to the page sequence list
page_sequence.extend(survey_pages)
# we could add more pages after the survey here
# ...
Have a look into the example implementations provided as otreeutils_example1
(understanding questions, simple page extensions), otreeutils_example2
(surveys) and otreeutils_example3_market
(custom data models).
This module allows creating scripts that interface with oTree from the command line. Importing otreeutils.scripts
makes sure that everything is correctly set up and the settings are loaded. An example might be a script which exports data from the current sessions for specific apps as JSON file:
import sys
from otreeutils import scripts # this is the most import line and must be included at the beginning
if len(sys.argv) != 2:
print('call this script with a single argument: python %s <output.json>' % sys.argv[0])
exit(1)
output_file = sys.argv[1]
apps = ['intro',
'my_app',
'outro']
print('loading data...')
# get the data as hierarchical data structure. this is esp. useful if you use
# custom data models
combined = scripts.get_hierarchical_data_for_apps(apps)
print('writing data to file', output_file)
scripts.save_data_as_json_file(combined, output_file, indent=2)
print('done.')
If you implement custom data models and want to use otreeutils' admin extensions you additionally need to follow these steps:
Make sure that you install otreeutils with extra dependencies via pip install otreeutils[admin]
.
For each of the custom models that you want to include in the live data view or extended data export, you have to define a subclass called CustomModelConf
like this:
from otree.db.models import Model, ForeignKey # import base Model class and ForeignKey
# ...
class FruitOffer(Model):
amount = models.IntegerField(label='Amount', min=0, initial=0)
# ... more fields here ...
seller = ForeignKey(Player)
class CustomModelConf:
"""
Configuration for otreeutils admin extensions.
"""
data_view = { # define this attribute if you want to include this model in the live data view
'exclude_fields': ['seller'],
'link_with': 'seller'
}
export_data = { # define this attribute if you want to include this model in the data export
'exclude_fields': ['seller_id'],
'link_with': 'seller'
}
In your experiment app, add a file urls.py
and simply include the custom URL patters from otreeutils as follows:
from otreeutils.admin_extensions.urls import urlpatterns
# add more custom URL rules here if necessary
# ...
In your experiment app, add the following line to models.py
:
from otreeutils.admin_extensions import custom_export
This makes sure that the data from the custom data models can be exported via oTree's admin interface.
Add this line to your settings.py
:
ROOT_URLCONF = '<APP_PACKAGE>.urls'
Instead of <APP_PACKAGE>
write your app's package name (e.g. "market" if your app is named "market").
And don't forget to edit your settings.py so that you add "otreeutils" to your INSTALLED_APPS list!
That's it! When you visit the admin pages, they won't really look different, however, the live data view will now support your custom models and in the data export view you can download the data including the custom models' data with the "custom" link. So far, the "all-apps" download option will not include the custom models' data.
Apache License 2.0. See LICENSE file.