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LTI Consumer XBlock Build Status Coveralls

This XBlock implements the consumer side of the LTI specification enabling integration of third-party LTI provider tools.

Installation

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/base.txt

Addtitionally, to enable LTI 1.3 Launch support, the following FEATURE flag needs to be set in studio.yml:

FEATURES:
    LTI_1P3_ENABLED: true

_Note: only LTI 1.3 launch is supported, and there's no implementation to pass back grades into the platform._

Installing in Docker Devstack

Assuming 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-consumer

Enabling in Studio

You can enable the LTI Consumer XBlock in Studio through the advanced settings.

  1. From the main page of a specific course, navigate to Settings -> Advanced Settings from the top menu.
  2. Check for the advanced_modules policy key, and add "lti_consumer" to the policy value list.
  3. Click the "Save changes" button.

Testing Against an LTI Provider

LTI 1.1

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

  1. 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.
  2. 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".
  3. Click edit and fill in the following fields: LTI ID: "test" LTI URL: "https://lti.tools/saltire/tp"
  4. 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.
  5. Click the "Publish" button.
  6. View the unit in your local LMS. If you get an ImportError: No module named lti_consumer, you should docker-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.

LTI 1.3

IMS Global provides a reference implementation of LTI 1.3 that can be used to test the XBlock.

On LTI 1.3 the authentication mechanism used is OAuth2 using the Client Credentials grant, this means that to configure the tool, the LMS needs to know the Keyset URL or public key of the tool, and the tool needs to know the LMS's one.

Intructions:

1. Set up a local tunnel tunneling the LMS (using ngrok or a similar tool) to get a URL accessible from the internet. 3. Create a new course, and add the lti_consumer block to the advanced modules list. 4. In the course, create a new unit and add the LTI block. 5. In studio, you'll see a few parameters being displayed in the preview: ` Client: f0532860-cb34-47a9-b16c-53deb077d4de Deployment ID: 1 # Note that these are LMS URLS Keyset URL: http://localhost:18000/api/lti_consumer/v1/public_keysets/block-v1:OpenCraft+LTI101+2020_T2+type@lti_consumer+block@efc55c7abb87430883433bfafb83f054 OAuth Token URL: http://localhost:18000/api/lti_consumer/v1/token/block-v1:OpenCraft+LTI101+2020_T2+type@lti_consumer+block@efc55c7abb87430883433bfafb83f054 OIDC Callback URL: http://localhost:18000/api/lti_consumer/v1/launch/ ` 6. Add the tunnel url to the keyset url as it'll need to be accessed by the tool (hosted externally). ` # This is <LMS_URL>/api/lti_consumer/v1/launch/<BLOCK_LOCATION> https://647dd2e1.ngrok.io/api/lti_consumer/v1/public_keysets/block-v1:OpenCraft+LTI101+2020_T2+type@lti_consumer+block@996c72b16070434098bc598bd7d6dbde ` 7. Set up a tool in the IMS Global reference implementation (https://lti-ri.imsglobal.org/lti/tools/).

8. Go back to Studio, and edit the block adding it's settings (you'll find them by scrolling down https://lti-ri.imsglobal.org/lti/tools/ until you find the tool you just created): ` Tool launch URL: https://lti-ri.imsglobal.org/lti/tools/[tool_id]/launches Tool OIDC Login Initiation URL: https://lti-ri.imsglobal.org/lti/tools/[tool_id]/login_initiations Tool public key: Public key from key page. ` 8. Publish block, log into LMS and navigate to the LTI block page. 9. Check that the LTI launch was successful.

Custom LTI Parameters

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.

Defining an LTI Parameter Processors

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.

Configuring the Parameter Processors Settings

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'

Workbench installation and settings

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 install

Running tests

From the xblock-lti-consumer repo root, run the tests with the following command:

$ make test

Running code quality check

From the xblock-lti-consumer repo root, run the quality checks with the following command:

$ make quality

Compiling Sass

This XBlock uses Sass for writing style rules. The Sass is compiled and committed to the git repo using:

$ make compile-sass

Changes to style rules should be made to the Sass files, compiled to CSS, and committed to the git repository.

Package Requirements

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.

Downloading translations from Transifex

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_CN

License

The LTI Consumer XBlock is available under the Apache Version 2.0 License.