A Python script that uses D-Wave's quantum annealing to optimally schedule tasks over several days. The script takes into account task duration, deadline, priority, unavailable hours, and favorite hours (preferred working hours).
python task_scheduler.py <tasks_file> <num_days> [--unavailable_hours_file <unavailable_hours_file>] [--favorite_hours_file <favorite_hours_file>]
<tasks_file>: Path to the CSV file containing the tasks. The CSV file should have the following columns: task, duration, deadline, and priority.<num_days>: Number of days to schedule tasks.<unavailable_hours_file>(optional): Path to the file containing space-separated list of hours during which the person does not want to work.<favorite_hours_file>(optional): Path to the file containing space-separated list of hours during which the person prefers to work.
python test.py task.csv 1 --unavailable_hours_file unavailable_hours --favorite_hours_file favorite_hours