

from __future__ import annotations

import pandas as pd
def   a   (    A__			:     list[int]   ,     A__			:     list[int]   ,     A__			:     int  )					->   list[int]:





      """simple docstring"""



      _lowercase			 =[0] * no_of_processes
      _lowercase			 =[0] * no_of_processes
      # Copy the burst time into remaining_time[]
      for i in range(A__  ):
            _lowercase			 =burst_time[i]

      _lowercase			 =0
      _lowercase			 =0
      _lowercase			 =999999999
      _lowercase			 =0
      _lowercase			 =False

      # Process until all processes are completed
      while complete != no_of_processes:
            for j in range(A__  ):
                  if arrival_time[j] <= increment_time and remaining_time[j] > 0:
                        if remaining_time[j] < minm:
                              _lowercase			 =remaining_time[j]
                              _lowercase			 =j
                              _lowercase			 =True

            if not check:
                  increment_time += 1
                  continue
            remaining_time[short] -= 1

            _lowercase			 =remaining_time[short]
            if minm == 0:
                  _lowercase			 =999999999

            if remaining_time[short] == 0:
                  complete += 1
                  _lowercase			 =False

                  # Find finish time of current process
                  _lowercase			 =increment_time + 1

                  # Calculate waiting time
                  _lowercase			 =finish_time - arrival_time[short]
                  _lowercase			 =finar - burst_time[short]

                  if waiting_time[short] < 0:
                        _lowercase			 =0

        # Increment time
            increment_time += 1
      return waiting_time
def   a   (    A__			:     list[int]   ,     A__			:     int   ,     A__			:     list[int]  )					->   list[int]:





      """simple docstring"""



      _lowercase			 =[0] * no_of_processes
      for i in range(A__  ):
            _lowercase			 =burst_time[i] + waiting_time[i]
      return turn_around_time
def   a   (    A__			:     list[int]   ,     A__			:     list[int]   ,     A__			:     int  )					->   None:





      """simple docstring"""



      _lowercase			 =0
      _lowercase			 =0
      for i in range(A__  ):
            _lowercase			 =total_waiting_time + waiting_time[i]
            _lowercase			 =total_turn_around_time + turn_around_time[i]
      print(F'''Average waiting time = {total_waiting_time / no_of_processes:.5f}'''  )
      print('Average turn around time ='   ,     total_turn_around_time / no_of_processes  )


if __name__ == "__main__":
  print('Enter how many process you want to analyze')
  lowercase_             =     int(input())
  lowercase_             =     [0] * no_of_processes
  lowercase_             =     [0] * no_of_processes
  lowercase_             =     list(range(1, no_of_processes + 1))

  for i in range(no_of_processes):
    print('Enter the arrival time and burst time for process:--' + str(i + 1))
    lowercase_       ,		lowercase_             =     map(int, input().split())

  lowercase_             =     calculate_waitingtime(arrival_time, burst_time, no_of_processes)

  lowercase_             =     burst_time
  lowercase_             =     no_of_processes
  lowercase_             =     waiting_time
  lowercase_             =     calculate_turnaroundtime(bt, n, wt)

  calculate_average_times(waiting_time, turn_around_time, no_of_processes)

  lowercase_             =     pd.DataFrame(
      list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
      columns=[
          'Process',
          'BurstTime',
          'ArrivalTime',
          'WaitingTime',
          'TurnAroundTime',
      ],
  )

  # Printing the dataFrame
  pd.set_option('display.max_rows', fcfs.shape[0] + 1)
  print(fcfs)





def   a   (    A__			:     Optional[int]  )					->   Tuple:





      """simple docstring"""



      _lowercase			 =[0] * len(A__  )
      _lowercase			 =[]
      _lowercase			 =[]
      _lowercase			 =0

      for values in graph.values():
            for i in values:
                  indegree[i] += 1

      for i in range(len(A__  )  ):
            if indegree[i] == 0:
                  queue.append(A__  )

      while queue:
            _lowercase			 =queue.pop(0  )
            cnt += 1
            topo.append(A__  )
            for x in graph[vertex]:
                  indegree[x] -= 1
                  if indegree[x] == 0:
                        queue.append(A__  )

      if cnt != len(A__  ):
            print('Cycle exists'  )
      else:
            print(A__  )


# Adjacency List of Graph
lowercase_             =     {0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}







topological_sort(graph)


