📅 2024-10-27 — Session: Developed and Optimized Task Scheduling System
🕒 20:20–23:49
🏷️ Labels: Scheduling, Task Management, Python, Automation, Constraints
📂 Project: Business
⭐ Priority: MEDIUM
Session Goal
The primary goal of this session was to develop and optimize a task scheduling system that effectively manages tasks across a 30-day period, focusing on workload balancing and frequency-based assignments.
Key Activities
- Data Transformation: Converted a DataFrame into a dictionary structure suitable for task management.
- CSV Updates: Updated constraints CSV with new task IDs and expanded it to include additional tasks and constraints.
- Error Resolution: Fixed a float value error in task scheduling code by casting variables to integers.
- Morning Routine Scheduling: Implemented and adapted scheduling logic to ensure the ‘Morning Routine’ starts immediately after a designated ‘Sleep’ block.
- Task Distribution Plan: Developed a plan for distributing tasks evenly across a 30-day period using Python.
- Day Balancing: Managed task scheduling by tracking day loads and dynamically assigning tasks to the least occupied days.
- Constraints Implementation: Implemented constraints for task scheduling, including frequency and time requirements.
- Feedback and Evaluation: Provided feedback on the organization and effectiveness of the schedule and constraints file.
Achievements
- Successfully implemented a dynamic scheduling system that adapts to workload and timing constraints.
- Enhanced task assignment process with verbosity for detailed tracking.
- Optimized task scheduling methodology to ensure balanced distribution across days.
Pending Tasks
- Further adjustments may be needed based on feedback to enhance the scheduling system’s flexibility and efficiency.