This XBlock implements the consumer side of the LTI specification enabling integration of third-party LTI provider tools.
Install the requirements into the python virtual environment of your
edx-platform installation by running the following command from the
root folder:
$ pip install -r requirements.txtAssuming that your devstack repo lives at ~/code/devstack
and that edx-platform lives right alongside that directory, you'll want
to checkout xblock-lti-consumer and have it live in ~/code/src/xblock-lti-consumer.
This will make it so that you can access it inside an LMS container shell
and easily make modifications for local testing.
Run make lms-shell from your devstack directory to enter a running LMS container.
Once in there, you can do the following to have your devstack pointing at a local development
version of xblock-lti-consumer:
$ pushd /edx/src/xblock-lti-consumer
$ virtualenv venv/
$ source venv/bin/activate
$ make install
$ make test # optional, if you want to see that everything works
$ deactivate
$ pushd # should take you back to /edx/app/edxapp/edx-platform
$ pip uninstall -y lti_consumer_xblock
$ pip install -e /edx/src/xblock-lti-consumerYou can enable the LTI Consumer XBlock in Studio through the advanced settings.
- From the main page of a specific course, navigate to
Settings -> Advanced Settingsfrom the top menu. - Check for the
advanced_modulespolicy key, and add"lti_consumer"to the policy value list. - Click the "Save changes" button.
http://lti.tools/saltire/ provides a "Test Tool Provider" service that allows you to see messages sent by an LTI consumer.
We have some useful documentation on how to set this up here: http://edx.readthedocs.io/projects/open-edx-building-and-running-a-course/en/latest/exercises_tools/lti_component.html#lti-authentication-information
- In Studio Advanced settings, set the value of the "LTI Passports" field to "test:test:secret" - this will set the oauth client key and secret used to send a message to the test LTI provider.
- Create an LTI Consumer problem in a course in studio (after enabling it in "advanced_modules" as seen above). Make a unit, select "Advanced", then "LTI Consumer".
- Click edit and fill in the following fields:
LTI ID: "test"LTI URL: "https://lti.tools/saltire/tp" - Click save. The unit should refresh and you should see "Passed" in the "Verification" field of the message tab in the LTI Tool Provider emulator.
- Click the "Publish" button.
- View the unit in your local LMS. If you get an
ImportError: No module named lti_consumer, you shoulddocker-compose restart lms(since we previously uninstalled the lti_consumer to get the tests for this repo running inside an LMS container). From here, you can see the contents of the messages that we are sending as an LTI Consumer in the "Message Parameters" part of the "Message" tab.
This XBlock sends a number of parameters to the provider including some optional parameters. To keep the XBlock
somewhat minimal, some parameters were omitted like lis_person_name_full among others.
At the same time the XBlock allows passing extra parameters to the LTI provider via parameter processor functions.
The parameter processor is a function that expects an XBlock instance, and returns a dict of
additional parameters for the LTI.
If a processor throws an exception, the exception is logged and suppressed.
If a processor returns None or any falsy value, no parameters will be added.
def team_info(xblock):
course = get_team(xblock.user, lti_params.course.id)
if not course:
return
return {
'custom_course_id': unicode(course.id),
'custom_course_name': course.name,
}A processor can define a list of default parameters lti_xblock_default_params,
which is useful in case the processor had an exception.
It is recommended to define default parameters anyway, because it can simplify the implementation of the processor function. Below is an example:
def dummy_processor(xblock):
course = get_team(xblock.user, lti_params.course.id) # If something went wrong default params will be used
if not course:
return # Will use the default params
return {
'custom_course_id': unicode(course.id),
'custom_course_name': course.name,
}
dummy_processor.lti_xblock_default_params = {
'custom_course_id': '',
'custom_course_name': '',
}If you're looking for a more realistic example, you can check the Tahoe LTI repository at the Appsembler GitHub organization.
Using the standard XBlock settings interface the developer can provide a list of processor functions:
Those parameters are not sent by default. The course author can enable that on per XBlock instance
(aka module) by setting the Send extra parameters to true in Studio.
To configure parameter processors add the following snippet to your Ansible variable files:
EDXAPP_XBLOCK_SETTINGS:
lti_consumer:
parameter_processors:
- 'customer_package.lti_processors:team_and_cohort'
- 'example_package.lti_processors:extra_lti_params'Install to the workbench's virtualenv by running the following command from the xblock-lti-consumer repo root with the workbench's virtualenv activated:
$ make installFrom the xblock-lti-consumer repo root, run the tests with the following command:
$ make testFrom the xblock-lti-consumer repo root, run the quality checks with the following command:
$ make qualityThis XBlock uses Sass for writing style rules. The Sass is compiled and committed to the git repo using:
$ make compile-sassChanges to style rules should be made to the Sass files, compiled to CSS, and committed to the git repository.
setup.py contains a list of package dependencies which are required for this XBlock package. This list is what is used to resolve dependencies when an upstream project is consuming this XBlock package. requirements.txt is used to install the same dependencies when running the tests for this package.
If you want to download translations from Transifex install transifex client and run this command while inside project root directory
$ tx pull -f --mode=reviewed -l en,ar,es_419,fr,he,hi,ko_KR,pt_BR,ru,zh_CNThe LTI Consumer XBlock is available under the Apache Version 2.0 License.