from __future__ import print_function
from ortools.linear_solver import pywraplp
import sys

def main():

    # days
    days = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']

    # hours
    hours = [
        '00',
        '01',
        '02',
        '03',
        '04',
        '05',
        '06',
        '07',
        '08',
        '09',
        '10',
        '11',
        '12',
        '13',
        '14',
        '15',
        '16',
        '17',
        '18',
        '19',
        '20',
        '21',
        '22',
        '23']

    # initialize required hours - req_hours[days][hours]
    req_hours = [[0 for x in range(len(hours))] for y in range(len(days))]

    # get arguments
    # there will be 8 arguments, monday to sunday schedule and the shift selected
    # sample argument: 
    # 0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0 0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0 0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0 0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0 0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0 0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0 0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0 24_7
    for day_index in range(0, len(days)):
        hours_string = sys.argv[day_index + 1]
        hours_data = hours_string.split('-')
        for hour_index in range(0, len(hours)):
            req_hours[day_index][hour_index] = int(hours_data[hour_index])

    argv_index = day_index + 2
    # number of days is fixed at 7 so the number of shifts will be in index 8
    num_shifts = sys.argv[argv_index]

    hour_shifts = []
    for shift_ctr in range(0, int(num_shifts)):
        # form list within the list
        hour_shift_item = []

        shift = sys.argv[argv_index+1]

        # append to list
        hour_shift_item.append(shift)

        # append the list to the list
        hour_shifts.append(hour_shift_item)
        argv_index+=1

    # all possible days riders come in
    day_shifts = [
        ['Mon - Sat', 0, 1, 2, 3, 4, 5], # Mon - Sat
        ['Tue - Sun', 1, 2, 3, 4, 5, 6], # Tue - Sun
        ['Wed - Mon', 2, 3, 4, 5, 6, 0], # Wed - Mon
        ['Thu - Tue', 3, 4, 5, 6, 0, 1], # Thu - Tue
        ['Fri - Wed', 4, 5, 6, 0, 1, 2], # Fri - Wed
        ['Sat - Thu', 5, 6, 0, 1, 2, 3], # Sat - Thu
        ['Sun - Fri', 6, 0, 1, 2, 3, 4]] # Sun - Fri

    # build shift lookup index


    # instantiate glop solver
    solver = pywraplp.Solver('SolveSchedule', pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)

    # solver variables
    solv_shifts = [[0 for x in range(len(hour_shifts))] for y in range(len(day_shifts))]

    # objective
    objective = solver.Objective()

    # variables for shifts
    for day_index in range(0, len(day_shifts)):
        for hour_index in range(0, len(hour_shifts)):
            solv_shifts[day_index][hour_index] = solver.IntVar(0, solver.infinity(), day_shifts[day_index][0] + ' ' + hour_shifts[hour_index][0])
            # objective is to minimize number of shifts
            objective.SetCoefficient(solv_shifts[day_index][hour_index], 1)
    objective.SetMinimization()

    # set constraints
    constraints = [[0 for x in range(len(hours))] for y in range(len(days))]
    # go through all days
    for day_index in range(0, len(days)):
        # go through all hours
        for hour_index in range(0, len(hours)):
            # hour personnel should be equal or less than shift personnel that covers those hours
            # set the required manpower for that day + hour combo
            # print('setting constraint for', day_index, '-', hour_index, '=', req_hours[day_index][hour_index])
            constraints[day_index][hour_index] = solver.Constraint(req_hours[day_index][hour_index], solver.infinity())
            # go through all day shifts
            for shift_day in range(0, len(day_shifts)):
                # go through days inside day shift
                for shift_day_index in range(1, len(day_shifts[shift_day])):
                    # is day shift part of that day?
                    if day_index == day_shifts[shift_day][shift_day_index]:
                        # go through all hour shifts
                        for shift_hour in range(0, len(hour_shifts)):
                            # go through all hours inside hour shift
                            for shift_hour_index in range(1, len(hour_shifts[shift_hour])):
                                # is hour shift part of the hour
                                if hour_index == hour_shifts[shift_hour][shift_hour_index]:
                                    # print(day_index, ' - ', hour_index, ' vs ', day_shifts[shift_day][shift_day_index], ' - ', hour_shifts[shift_hour][shift_hour_index])
                                    # add it to constraint
                                    constraints[day_index][hour_index].SetCoefficient(solv_shifts[shift_day][shift_hour], 1)

    # solve it!
    status = solver.Solve()
    #print('Number of variables =', solver.NumVariables())
    #print('Number of constraints =', solver.NumConstraints())

    if status == solver.OPTIMAL:
        #print('Optimal solution found!')
        for day_index in range(0, len(day_shifts)):
            for hour_index in range(0, len(hour_shifts)):
                result = solv_shifts[day_index][hour_index].solution_value()
                if result > 0:
                    print(day_index, hour_index, int(solv_shifts[day_index][hour_index].solution_value()), sep='-')
                    #print(day_shifts[day_index][0], ' ', hour_shifts[hour_index][0], ' = ', int(solv_shifts[day_index][hour_index].solution_value()), sep='')
    else:
        if status == solver.FEASIBLE:
            print('Feasible solution found!')
        else:
            print('Could not solve problem.')

if __name__ == '__main__':
  main()