This project is a Python implementation of the similar PHP tool.
This library contains adapters for use with the Django and Flask web frameworks. However, there are no difficulties with adapting it to other frameworks; you just need to re-implement the OIDCLogin
and MessageLaunch
classes as it is already done in existing adapters.
Django: https://github.com/dmitry-viskov/pylti1.3-django-example
Flask: https://github.com/dmitry-viskov/pylti1.3-flask-example
To configure your own tool, you may use built-in adapters:
from pylti1p3.tool_config import ToolConfJsonFile
tool_conf = ToolConfJsonFile('path/to/json')
from pylti1p3.tool_config import ToolConfDict
settings = {
"<issuer_1>": { }, # one issuer ~ one client-id (outdated and not recommended)
"<issuer_2>": [{ }, { }] # one issuer ~ many client-ids (recommended method)
}
private_key = '...'
public_key = '...'
tool_conf = ToolConfDict(settings)
client_id = '...' # must be set if implementing the "one issuer ~ many client-ids" concept
tool_conf.set_private_key(iss, private_key, client_id=client_id)
tool_conf.set_public_key(iss, public_key, client_id=client_id)
or create your own implementation. The pylti1p3.tool_config.ToolConfAbstract
interface must be fully implemented for this to work.
The concept of one issuer ~ many client-ids
is the recommended way to organize configs and may be useful in the case of integration with Canvas (https://canvas.instructure.com)
or other Cloud LMS-es where the platform doesn't change iss
for each customer.
In the case of the Django Framework, you may use DjangoDbToolConf
(see Configuration using Django Admin UI section below).
Example of a JSON config:
{
"iss1": [{
"default": true,
"client_id": "client_id1",
"auth_login_url": "auth_login_url1",
"auth_token_url": "auth_token_url1",
"auth_audience": null,
"key_set_url": "key_set_url1",
"key_set": null,
"private_key_file": "private.key",
"public_key_file": "public.key",
"deployment_ids": ["deployment_id1", "deployment_id2"]
}, {
"default": false,
"client_id": "client_id2",
"auth_login_url": "auth_login_url2",
"auth_token_url": "auth_token_url2",
"auth_audience": null,
"key_set_url": "key_set_url2",
"key_set": null,
"private_key_file": "private.key",
"public_key_file": "public.key",
"deployment_ids": ["deployment_id3", "deployment_id4"]
}],
"iss2": [ ],
"iss3": { }
}
default (bool)
- this iss config will be used in case if client-id was not passed on the login stepclient_id
- this is the id received in the 'aud' during a launchauth_login_url
- the platform's OIDC login endpointauth_token_url
- the platform's service authorization endpointauth_audience
- the platform's OAuth2 Audience (aud). Is used to get platform's access token. Usually the same as "auth_token_url" and could be skipped but in the common case could be a different urlkey_set_url
- the platform's JWKS endpointkey_set
- in case if platform's JWKS endpoint somehow unavailable you may paste JWKS hereprivate_key_file
- relative path to the tool's private keypublic_key_file
- relative path to the tool's public keydeployment_ids (list)
- The deployment_id passed by the platform during launch# settings.py
INSTALLED_APPS = [
'django.contrib.admin',
...
'pylti1p3.contrib.django.lti1p3_tool_config'
]
# urls.py
urlpatterns = [
...
path('admin/', admin.site.urls),
...
]
# views.py
from pylti1p3.contrib.django import DjangoDbToolConf
tool_conf = DjangoDbToolConf()
LTI 1.3 uses a modified version of the OpenId Connect third party initiate login flow. This means that to do an LTI 1.3 launch, you must first receive a login initialization request and return to the platform.
To handle this request, you must first create a new OIDCLogin
(or DjangoOIDCLogin
) object:
from pylti1p3.contrib.django import DjangoOIDCLogin
oidc_login = DjangoOIDCLogin(request, tool_conf)
You must now configure your login request with a return url (this must be preconfigured and white-listed in the tool).
If a redirect url is not given or the registration does not exist, a pylti1p3.exception.OIDC_Exception
will be thrown.
try:
oidc_login.redirect(get_launch_url(request))
except OIDC_Exception:
# display error page
log.error('Error doing OIDC login')
With the redirect, we can now redirect the user back to the tool. There are three ways to do this:
This will add a HTTP 302 location header:
oidc_login.redirect(get_launch_url(request))
This will display some JavaScript to do the redirect instead of using a HTTP 302:
oidc_login.redirect(get_launch_url(request), js_redirect=True)
You can also get the url you need to redirect to, with all of the necessary query parameters (if you would prefer to redirect in a custom way):
redirect_obj = oidc_login.get_redirect_object()
redirect_url = redirect_obj.get_redirect_url()
The redirect is done and we can move on to the launch.
Now that we have done the OIDC log, the platform will launch back to the tool. To handle this request, we first need to create a new MessageLaunch
(or DjangoMessageLaunch
) object.
message_launch = DjangoMessageLaunch(request, tool_conf)
Once we have the message launch, we can validate it. Validation is transparent - it's done once before you try to access the message body:
try:
launch_data = message_launch.get_launch_data()
except LtiException:
log.error('Launch validation failed')
You may do it more explicitly:
try:
launch_data = message_launch.set_auto_validation(enable=False).validate()
except LtiException:
log.error('Launch validation failed')
Now that we know the launch is valid, we can find out more information about the launch.
To check if we have a resource launch or a deep linking launch:
if message_launch.is_resource_launch():
# Resource Launch!
elif message_launch.is_deep_link_launch():
# Deep Linking Launch!
else:
# Unknown launch type
To check which services we have access to:
if message_launch.has_ags():
# Has Assignments and Grades Service
if message_launch.has_nrps():
# Has Names and Roles Service
This is a draft of an API endpoint. Wrap it in a library of your choice.
Create a FlaskRequest
adapter. Then create an instance of FlaskOIDCLogin
. The redirect
method will return an instance of werkzeug.wrappers.Response
that points to the LTI platform if login was successful. Make sure to handle exceptions.
from flask import request, session
from pylti1p3.flask_adapter import (FlaskRequest, FlaskOIDCLogin)
def login(request_params_dict):
tool_conf = ... # See Configuration chapter above
# FlaskRequest by default use flask.request and flask.session
# so in this case you may define request object without any arguments:
request = FlaskRequest()
# in case of using different request object (for example webargs or something like this)
# you may pass your own values:
request = FlaskRequest(
cookies=request.cookies,
session=session,
request_data=request_params_dict,
request_is_secure=request.is_secure
)
oidc_login = FlaskOIDCLogin(
request=request,
tool_config=tool_conf,
session_service=FlaskSessionService(request),
cookie_service=FlaskCookieService(request)
)
return oidc_login.redirect(request.get_param('target_link_uri'))
This is a draft of an API endpoint. Wrap it in a library of your choice.
Create a FlaskRequest
adapter. Then create an instance of FlaskMessageLaunch
. This lets you access data from the LTI launch message if the launch was successful. Make sure to handle exceptions.
from flask import request, session
from werkzeug.utils import redirect
from pylti1p3.flask_adapter import (FlaskRequest, FlaskMessageLaunch)
def launch(request_params_dict):
tool_conf = ... # See Configuration chapter above
request = FlaskRequest()
# or
request = FlaskRequest(
cookies=...,
session=...,
request_data=...,
request_is_secure=...
)
message_launch = FlaskMessageLaunch(
request=request,
tool_config=tool_conf
)
email = message_launch.get_launch_data().get('email')
# Place your user creation/update/login logic
# and redirect to tool content here
It is likely that you will want to refer back to a launch later during subsequent requests. This is done using the launch id to identify a cached request. The launch id can be found using:
launch_id = message_launch.get_launch_id()
Once you have the launch id, you can link it to your session and pass it along as a query parameter.
Retrieving a launch using the launch id can be done using:
message_launch = DjangoMessageLaunch.from_cache(launch_id, request, tool_conf)
Once retrieved, you can call any of the methods on the launch object as normal, e.g.
if message_launch.has_ags():
# Has Assignments and Grades Service
If you receive a deep linking launch, it is very likely that you are going to want to respond to the deep linking request with resources for the platform.
To create a deep link response, you will need to get the deep link for the current launch:
deep_link = message_launch.get_deep_link()
We now need to create pylti1p3.deep_link_resource.DeepLinkResource
to return:
resource = DeepLinkResource()
resource.set_url("https://my.tool/launch")\
.set_custom_params({'my_param': my_param})\
.set_title('My Resource')
Everything is now set to return the resource to the platform. There are two methods of doing this.
The following method will output the html for an aut-posting form for you.
deep_link.output_response_form([resource1, resource2])
Alternatively you can just request the signed JWT that will need posting back to the platform by calling.
deep_link.get_response_jwt([resource1, resource2])
Before using names and roles, you should check that you have access to it:
if not message_launch.has_nrps():
raise Exception("Don't have names and roles!")
Once we know we can access it, we can get an instance of the service from the launch.
nrps = message_launch.get_nrps()
From the service we can get a list of all members by calling:
members = nrps.get_members()
To get some specific page with the members:
members, next_page_url = nrps.get_members_page(page_url)
Before using assignments and grades, you should check that you have access to it:
if not launch.has_ags():
raise Exception("Don't have assignments and grades!")
Once we know we can access it, we can get an instance of the service from the launch:
ags = launch.get_ags()
To pass a grade back to the platform, you will need to create a pylti1p3.grade.Grade
object and populate it with the necessary information:
gr = Grade()
gr.set_score_given(earned_score)\
.set_score_maximum(100)\
.set_timestamp(datetime.datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%S+0000'))\
.set_activity_progress('Completed')\
.set_grading_progress('FullyGraded')\
.set_user_id(external_user_id)
To send the grade to the platform we can call:
ags.put_grade(gr)
This will put the grade into the default provided lineitem. If no default lineitem exists it will create one.
If you want to send multiple types of grade back, that can be done by specifying a pylti1p3.lineitem.LineItem
:
line_item = LineItem()
line_item.set_tag('grade')\
.set_score_maximum(100)\
.set_label('Grade')
ags.put_grade(gr, line_item)
If a lineitem with the same tag
exists, that lineitem will be used, otherwise a new lineitem will be created.
Additional methods:
# Get one page with line items
items_lst, next_page = ags.get_lineitems_page()
# Get list of all available line items
items_lst = ags.get_lineitems()
# Find line item by ID
item = ags.find_lineitem_by_id(ln_id)
# Find line item by tag
item = ags.find_lineitem_by_tag(ln_tag)
# Return all grades for the passed line item (across all users enrolled in the line item's context)
grades = ags.get_grades(ln)
Data Privacy Launch is a new optional LTI 1.3 message type that allows LTI-enabled tools to assist administrative users in managing and executing requests related to data privacy.
data_privacy_launch = message_launch.is_data_privacy_launch()
if data_privacy_launch:
user = message_launch.get_data_privacy_launch_user()
Submission review provides a standard way for an instructor or student to launch back from a platform's gradebook to the tool where the interaction took place to display the learner's submission for a particular line item.
if launch.is_submission_review_launch()
user = launch.get_submission_review_user()
ags = launch.get_ags()
lineitem = ags.get_lineitem()
submission_review = lineitem.get_submission_review()
Communicates to the tool the groups available in the course and their respective enrollment.
if launch.has_cgs()
cgs = launch.get_cgs()
# Get all available groups
groups = cgs.get_groups()
# Get groups for some user
user_id = '0ae836b9-7fc9-4060-006f-27b2066ac545'
groups = cgs.get_groups(user_id)
# Get all sets
if cgs.has_sets():
sets = cgs.get_sets()
sets_with_groups = cgs.get_sets(include_groups=True)
user_is_staff = message_launch.check_staff_access()
user_is_student = message_launch.check_student_access())
user_is_teacher = message_launch.check_teacher_access()
user_is_teaching_assistant = message_launch.check_teaching_assistant_access()
user_is_designer = message_launch.check_designer_access()
user_is_observer = message_launch.check_observer_access()
user_is_transient = message_launch.check_transient()
Some browsers may deny requests to save cookies in the iframes. For example, Google Chrome (from ver.80 onwards) denies requests to save all cookies in
the iframes except cookies with the flags Secure
(i.e HTTPS usage) and SameSite=None
. Safari denies requests to save
all third-party cookies by default. The pylti1p3
library contains workarounds for such behaviours:
def login():
...
return oidc_login\
.enable_check_cookies()\
.redirect(target_link_uri)
After this, the special JS code will try to write and then read test cookie instead of redirect. The user will see a special page that will ask them to open the current URL in the new window if cookies are unavailable. If cookies are allowed, the user will be transparently redirected to the next page. All texts are configurable with passing arguments:
oidc_login.enable_check_cookies(main_msg, click_msg, loading_msg)
You may also have troubles with the default framework sessions because the pylti1p3
library can't control your framework
settings connected with the session ID cookie. Without necessary settings, the user's session could be unavailable in the
case of iframe usage. To avoid this, it is recommended to change the default session adapter to the new cache
adapter (with a memcache/redis backend) and as a consequence, allow the library to set its own LTI 1.3 session id cookie
that will be set with all necessary params like Secure
and SameSite=None
.
from pylti1p3.contrib.django import DjangoCacheDataStorage
def login(request):
...
launch_data_storage = DjangoCacheDataStorage(cache_name='default')
oidc_login = DjangoOIDCLogin(request, tool_conf, launch_data_storage=launch_data_storage)
def launch(request):
...
launch_data_storage = DjangoCacheDataStorage(cache_name='default')
message_launch = DjangoMessageLaunch(request, tool_conf, launch_data_storage=launch_data_storage)
def restore_launch(request):
...
launch_data_storage = get_launch_data_storage(cache_name='default')
message_launch = DjangoMessageLaunch.from_cache(launch_id, request, tool_conf,
launch_data_storage=launch_data_storage)
from flask_caching import Cache
from pylti1p3.contrib.flask import FlaskCacheDataStorage
cache = Cache(app)
def login():
...
launch_data_storage = FlaskCacheDataStorage(cache)
oidc_login = DjangoOIDCLogin(request, tool_conf, launch_data_storage=launch_data_storage)
def launch():
...
launch_data_storage = FlaskCacheDataStorage(cache)
message_launch = DjangoMessageLaunch(request, tool_conf, launch_data_storage=launch_data_storage)
def restore_launch():
...
launch_data_storage = FlaskCacheDataStorage(cache)
message_launch = DjangoMessageLaunch.from_cache(launch_id, request, tool_conf,
launch_data_storage=launch_data_storage)
The library will try to fetch the platform's public key every time on the message launch step. This public key may be stored in cache (memcache/redis) to speed-up the launch process:
# Django cache storage:
launch_data_storage = DjangoCacheDataStorage()
# Flask cache storage:
launch_data_storage = FlaskCacheDataStorage(cache)
message_launch.set_public_key_caching(launch_data_storage, cache_lifetime=7200)
You may generate JWKS from a Tool Config object:
tool_conf.set_public_key(iss, public_key, client_id=client_id)
jwks_dict = tool_conf.get_jwks() # {"keys": [{ ... }]}
# or you may specify iss and client_id:
jwks_dict = tool_conf.get_jwks(iss, client_id) # {"keys": [{ ... }]}
Do not forget to set a public key as without it, JWKS cannot be generated. You may also generate JWK for any public key using the construction below:
from pylti1p3.registration import Registration
jwk_dict = Registration.get_jwk(public_key)
# {"e": ..., "kid": ..., "kty": ..., "n": ..., "alg": ..., "use": ...}