The Academic Outcome Predictor is a simple Python University Project designed to calculate progression outcomes of students. It determines the academic standing based on the total credits earned in different categories.
-
Functions and Local Variables:
- Modularization of code through functions (
horizontalSeparator
,get_input
,horizontal_histogram
,vertical_histogram
,main
). - Functions are utilized for better organization, readability, and reusability.
- Local variables within functions store temporary data, avoiding the use of unnecessary global variables.
- Modularization of code through functions (
-
Conditional Statements:
- Conditional statements (
if
,elif
,else
) are employed to determine progression outcomes based on input marks. - Logical operators (
&
,>=
,in
,range
) are utilized in conditions.
- Conditional statements (
-
Data Storage (Python Lists):
- Lists (
lst
) are employed to store and manage multiple sets of data. - Lists are utilized for storing progression outcome details.
- Lists (
-
Loops:
while
loops are used to control the flow of the program until certain conditions are met.- Nested loops handle input validation and user interaction.
-
Exception Handling:
- Exceptions are handled using
try
andexcept
for input validation. - Ensuring the user enters valid integers for input.
- Exceptions are handled using
This project emphasizes the importance of modular programming, effective use of functions, and proper data organization to enhance code maintainability and readability.