CourseSpyderweb

Program Instructions

1. (Optional) In the course_scrapper module, uncomment the lines in main body to start scrapping process. It would scrap the data from the webpage and create a dataset named ”CourseData.csv”. However, we already included that dataset in the project.

2. The main block of main.py includes the function call run_example(), which builds a directed graph using NetworkX and displays the graph on a Matplotlib window. In the given example, a graph is built using a student object with courses ’CSC110Y1’ and ’CSC111H1’ completed. The green arrows represent fulfilled prerequisites and the red arrows represent unfulfilled prerequisites. Note: please fullscreen the Matplotlib windows to accurately view each node.

3. For further testing, create your own student object and add courses to academichistory using the following functions:

   • check_eligibility_course: checks if the student is eligible to enroll in an input course based on their academic history.
   • add_course_info: adds a Record object to the student’s academic record. Raises a ValueError if the input course code is not in the dataset.

   Then, call run_example() using this student object.

4. In addition, we have provided a few helper functions which you may find useful:

   • check_eligibility_program and check_eligibility_focus: checks if the student is eligible to complete a computer science major/specialist/focus program based on their academic history.
   • get_requirements: return the student’s missing requirements needed to complete a program/focus.
   • get_FCE_count: calculates the total number of FCEs obtained by the student.