CourseOfAction

video.mp4

Link to the deployed website:

https://mcsapps.utm.utoronto.ca/coa/app/dashboard

Purpose:

This application can be accessed via any browser on mobile and PC for UofT students to easily track courses, assessments and grades throughout their semester.

Usage & Current Functionality:

You need to have a valid UofT account to use this application as we use SSO for authentication.

API Documentation

If testing on deployed website then:

Base URL = https://mcsapps.utm.utoronto.ca/

Otherwise, if testing on localhost then:

Base URL = http://localhost:8989/

Note: All request headers must contain the Utorid(default behaviour for all MCS apps). The base URL will precede all the routes listed below.

Routes

GET /coa/app/*
Purpose: Serve static files for the frontend app
Expected Data: None
Returns: HTML, CSS and JS files as requested

GET /coa/api/application-start
Purpose: Fetch courses for current user
Expected Data: None
Returns: Courses and User's notification preference

POST /coa/api/update-user-notification
Purpose: Setting notification preference for user
Expected Data: { "notification": 0/1 }
Returns: User data with updated values

POST /coa/api/add-course
Purpose: Creating a new course and add it for current user
Expected Data: Course data as a json object
Returns: {"message": "success/error message"}

POST /coa/api/delete-course
Purpose: Deletes the provided course if it exists for current user
Expected Data: Course code as a json object
Returns: {"message": "success/error message"}

POST /coa/api/update-course
Purpose: Updates data if course exists for current user (ex: familiarity, notification)
Expected Data: Course data as a json object
Returns: {"message": "success/error message"}

POST /coa/api/update-assessments
Purpose: Updates assessments for provided course if it exists for current user
Expected Data: Course data as a json object
Returns: {"message": "success/error message"}

POST /coa/api/parse-syllabus
Purpose: Allows syllabus upload for extracting assessment info
Expected Data: file upload as pdf
Returns: Parsed assessments as json or error message

Install dependencies and run on your local machine

Nodejs and Python should be installed on your machine. Clone the project onto your local machine.

git clone https://github.com/milindvishnoi/CourseOfAction

Install all the python packages and start backend server in development mode. Go into the backend folder and install all pip packages:

cd backend
pip install -r requirements.txt
FLASK_APP=app FLASK_ENV=development flask run -p 8989

For backend deployment

cd backend
pip install -r requirements.txt
flask run -p 8989

To install all the frontend dependencies and run the react application:

cd frontend
npm install
npm start