mirror of
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00e279ea44
* Fix mypy errors for scheduling/first_come_first_served * Fix mypy errors for scheduling/round_robin.py * Fix mypy errors for scheduling/shortest_job_first.py * Fix isort errors
152 lines
4.6 KiB
Python
152 lines
4.6 KiB
Python
"""
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Shortest job remaining first
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Please note arrival time and burst
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Please use spaces to separate times entered.
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"""
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from typing import List
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import pandas as pd
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def calculate_waitingtime(
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arrival_time: List[int], burst_time: List[int], no_of_processes: int
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) -> List[int]:
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"""
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Calculate the waiting time of each processes
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Return: List of waiting times.
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>>> calculate_waitingtime([1,2,3,4],[3,3,5,1],4)
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[0, 3, 5, 0]
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>>> calculate_waitingtime([1,2,3],[2,5,1],3)
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[0, 2, 0]
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>>> calculate_waitingtime([2,3],[5,1],2)
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[1, 0]
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"""
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remaining_time = [0] * no_of_processes
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waiting_time = [0] * no_of_processes
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# Copy the burst time into remaining_time[]
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for i in range(no_of_processes):
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remaining_time[i] = burst_time[i]
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complete = 0
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increment_time = 0
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minm = 999999999
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short = 0
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check = False
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# Process until all processes are completed
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while complete != no_of_processes:
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for j in range(no_of_processes):
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if arrival_time[j] <= increment_time:
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if remaining_time[j] > 0:
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if remaining_time[j] < minm:
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minm = remaining_time[j]
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short = j
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check = True
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if not check:
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increment_time += 1
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continue
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remaining_time[short] -= 1
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minm = remaining_time[short]
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if minm == 0:
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minm = 999999999
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if remaining_time[short] == 0:
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complete += 1
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check = False
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# Find finish time of current process
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finish_time = increment_time + 1
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# Calculate waiting time
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finar = finish_time - arrival_time[short]
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waiting_time[short] = finar - burst_time[short]
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if waiting_time[short] < 0:
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waiting_time[short] = 0
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# Increment time
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increment_time += 1
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return waiting_time
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def calculate_turnaroundtime(
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burst_time: List[int], no_of_processes: int, waiting_time: List[int]
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) -> List[int]:
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"""
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Calculate the turn around time of each Processes
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Return: list of turn around times.
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>>> calculate_turnaroundtime([3,3,5,1], 4, [0,3,5,0])
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[3, 6, 10, 1]
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>>> calculate_turnaroundtime([3,3], 2, [0,3])
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[3, 6]
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>>> calculate_turnaroundtime([8,10,1], 3, [1,0,3])
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[9, 10, 4]
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"""
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turn_around_time = [0] * no_of_processes
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for i in range(no_of_processes):
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turn_around_time[i] = burst_time[i] + waiting_time[i]
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return turn_around_time
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def calculate_average_times(
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waiting_time: List[int], turn_around_time: List[int], no_of_processes: int
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) -> None:
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"""
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This function calculates the average of the waiting & turnaround times
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Prints: Average Waiting time & Average Turn Around Time
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>>> calculate_average_times([0,3,5,0],[3,6,10,1],4)
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Average waiting time = 2.00000
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Average turn around time = 5.0
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>>> calculate_average_times([2,3],[3,6],2)
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Average waiting time = 2.50000
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Average turn around time = 4.5
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>>> calculate_average_times([10,4,3],[2,7,6],3)
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Average waiting time = 5.66667
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Average turn around time = 5.0
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"""
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total_waiting_time = 0
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total_turn_around_time = 0
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for i in range(no_of_processes):
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total_waiting_time = total_waiting_time + waiting_time[i]
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total_turn_around_time = total_turn_around_time + turn_around_time[i]
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print("Average waiting time = %.5f" % (total_waiting_time / no_of_processes))
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print("Average turn around time =", total_turn_around_time / no_of_processes)
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if __name__ == "__main__":
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print("Enter how many process you want to analyze")
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no_of_processes = int(input())
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burst_time = [0] * no_of_processes
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arrival_time = [0] * no_of_processes
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processes = list(range(1, no_of_processes + 1))
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for i in range(no_of_processes):
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print("Enter the arrival time and brust time for process:--" + str(i + 1))
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arrival_time[i], burst_time[i] = map(int, input().split())
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waiting_time = calculate_waitingtime(arrival_time, burst_time, no_of_processes)
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bt = burst_time
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n = no_of_processes
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wt = waiting_time
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turn_around_time = calculate_turnaroundtime(bt, n, wt)
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calculate_average_times(waiting_time, turn_around_time, no_of_processes)
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fcfs = pd.DataFrame(
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list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
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columns=[
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"Process",
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"BurstTime",
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"ArrivalTime",
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"WaitingTime",
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"TurnAroundTime",
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],
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)
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# Printing the dataFrame
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pd.set_option("display.max_rows", fcfs.shape[0] + 1)
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print(fcfs)
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