Automated-Study-Planner

This structured document outlines the development of an Automated Study Planner, focusing on the journey from identifying student-related productivity gaps to implementing an AI-driven solution.

Features: Dynamic Sorting: Automatically reorders tasks so the most urgent deadlines appear first using tasks.sort(). Live Countdown: Uses the datetime library to calculate exactly how many days remain from "today" until the deadline. Urgency Tagging: Uses logic to auto-label tasks as "OVERDUE", "DO THIS NOW", or "Relax" based on the remaining days. Error Handling: Includes a try-except block to prevent the program from crashing if a user enters an invalid date format. Bulk Entry: Features an infinite loop (while True) allowing users to input multiple subjects at once until they type "done. "Categorized Summary: Generates a clean, prioritized report showing the status of every assignment in one view.

Prerequisites Python 3.x installed on your system. Datetime libraries are required (uses standard Python functionality).

Code Structure import datetime: Provides the classes for manipulating dates and times. Error Handling: Uses a try-except block to prevent the program from crashing if the user types the date incorrectly. Creates an empty list (tasks = []) to act as a temporary database. Uses a "sentinel value" ('done') to allow the user to enter as many items as they want. Uses a Lambda Function (key=lambda x: x['days']) to tell Python exactly how to reorder the list (from smallest number of days to largest). Conditional Logic (if/elif/else): Categorizes each task based on urgency (Overdue, Now, or Relax). run_planner(): The final line that actually starts the program when the file is opened.

Author: [Aryan Raj]
Registration number:25BAI10693