This project is a Python implementation of the similar PHP tool.
Library contains adapters for usage from Django and Flask web frameworks but there is no difficulty to adapt it to other frameworks: you should just re-implement 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": { }, # one issuer ~ one client-id (outdated and not recommended way)
"<issuer_2>": [{ }, { }] # one issuer ~ many client-ids (preferable way)
}
private_key = '...'
public_key = '...'
tool_conf = ToolConfDict(settings)
client_id = '...' # must be set in case of "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.
Concept of one issuer ~ many client-ids
is a preferable way to organize configs and may be useful in case of integration with Canvas (https://canvas.instructure.com)
or other Cloud LMS-es where platform doesn't change iss
for each customer.
In case of Django Framework you may use DjangoDbToolConf
(see Configuration using Django Admin UI section below)
Example of 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)
Now you must configure your login request with a return url (this must be preconfigured and white-listed on the tool).
If a redirect url is not given or the registration does not exist an 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 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()
Redirect is done, we can move onto the launch.
Now that we have done the OIDC log the platform will launch back to the tool. To handle this request, first we 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 we know the launch is valid we can find out more information about the launch.
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
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
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()
Now we 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 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 list of all members by calling:
members = nrps.get_members()
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.
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()
This is draft of API endpoint. Wrap it in library of your choice.
Create FlaskRequest
adapter. Then create instance of FlaskOIDCLogin
. redirect
method will return instance of werkzeug.wrappers.Response
that points to LTI platform if login was successful. 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 draft of API endpoint. Wrap it in library of your choice.
Create FlaskRequest
adapter. Then create instance of FlaskMessageLaunch
. It lets you access data from LTI launch message if launch was successful. 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
Some browsers may deny to save cookies in the iframes. For example Google Chrome from ver.80 deny to save all cookies in
the iframes except cookies with flags Secure
(i.e HTTPS usage) and SameSite=None
. Safari deny to save
all third-party cookies by default. pylti1p3
library contains workaround for such behaviour:
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. User will see special page with asking to open current URL in the new window in case if cookies are unavailable. In case if cookies are allowed 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)
Also you may have troubles with default framework sessions (because pylti1p3
library can't control your framework
settings connected with the session ID cookie). So without necessary settings user's session could be unavailable in
case of iframe usage. To avoid this troubles it is recommended to change default session adapter to the new cache
adapter (with memcache/redis backend) and as a consequence allow library to set it's own LTI1.3 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)
Library try to fetch platform's public key everytime on the message launch step. This public key may be stored in cache (memcache/redis) to speed-up 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 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": [{ ... }]}
Don't forget to set public key because without it JWKS can't be generated. Also you may generate JWK for any public key using construction below:
from pylti1p3.registration import Registration
jwk_dict = Registration.get_jwk(public_key)
# {"e": ..., "kid": ..., "kty": ..., "n": ..., "alg": ..., "use": ...}