class NPScheduler:
def __init__(self, N, policy='SJF'):
self.N = N # number of time steps to schedule
self.running = None
self.clock = 0
self.policy = policy
# instantiate the readyQueue, which may be a FIFO or MinHeap
# you may need additional queues for
# - tasks that have been added but not released yet
# - tasks that have been completed
# - the Gantt chart
self.readyQueue = MinHeap()
self.notReadyQueue = FIFO()
self.doneQueue = list()
self.ganttChart = list()
def addTask(self, task):
# if the release time of the new task is not in the future, then
# put it in ready queue; otherwise, put into not-ready queue.
# you may need to copy the scheduler policy into the task
task.setPriorityScheme(self.policy)
if task.releaseTime() <= self.clock: #release
self.readyQueue.put(task)
else:
self.notReadyQueue.put(task)
def dispatch(self, task):
# dispatch here means assign the chosen task as the one to run
# in the current time step.
# the task should be removed from ready-queue by caller;
# The task may be empty (None).
# This method will make an entry into the Gantt chart and perform
# bookkeeping, including
## - recording the last dispatched time of this task,
# - increment the wait times of those tasks not scheduled
# but in the ready queue
if task is None:
self.ganttChart.append(task)
return
self.ganttChart.append(task)
task.decrRemaining()
task.last_dispatched = self.clock
for task_wait in self.readyQueue:
task_wait.incrWaitTime()
def releaseTasks(self):
'''
this is called at the beginning of scheduling each time step to see
if new tasks became ready to be released to ready queue, when their
release time is no later than the current clock.
'''
while True:
r = self.notReadyQueue.head()
# assuming the notReadyQueue outputs by release time
if r is None or r.releaseTime() > self.clock:
break
r = self.notReadyQueue.get()
r.setPriorityScheme(self.policy)
self.readyQueue.put(r)
def checkTaskCompletion(self):
# if there is a current running task, check if it has just finished.
# (i.e., decrement remaining time and see if it has more work to do. ??
# If so, perform bookkeeping for completing the task, ???
# - move task to done-queue, set its completion time and lastrun time ???
# set the scheduler running task to None, and return True
# (so that a new task may be picked.)
# but if not completed, return False.
# If there is no current running task, also return True.
if self.running is None:
return True
# your code here
task = self.running
if task.done():
task.setCompletionTime(self.clock)
self.doneQueue.append(task)
self.running = None
return True
# for future use
if task is None: return True
return False
def schedule(self):
# scheduler that handles nonpreemptive scheduling.
# the policy such as RR, SJF, or FCFS is handled by the task as it
# defines the attribute to compare (in its __iter__() method)
# first, check if added but unreleased tasks may now be released
# (i.e., added to ready queue)
self.releaseTasks()
if self.checkTaskCompletion() == False: # get task status
# There is a current running task and it is not done yet!
# the same task will continue running to its completion.
# simply redispatch the current running task.
## redispatch the current running task, we have current ruuing task
self.dispatch(self.running)
else:
# task completed or no running task.
# get the next task from priority queue and dispatch it.
# add None
if len(self.readyQueue) == 0:
self.dispatch(None)
# pop finishing
if len(self.readyQueue) > 0:
task = self.readyQueue.get()
# another turn to run
self.running = task
self.dispatch(self.running)
def clockGen(self):
for self.clock in range(self.N):
# now run scheduler here
self.schedule()
yield self.clock
def getSchedule(self):
return '-'.join(map(str, self.ganttChart))
# return self.ganttChart
def getThroughput(self):
# calculate and return throughput as a tuple
numerator = len(self.doneQueue)
denominator = self.doneQueue[-1].completion
return (numerator, denominator)
def getWaitTime(self):
# calculate and return
numerator = sum([task.wait_time for task in self.doneQueue])
denominator = len(self.doneQueue)
return (numerator, denominator)
def getTurnaroundTime(self):
# calculate the turnaround time in terms of a tuple with
# separate turnaround times, #processes
#print([task.turnaroundTime() for task in self.doneQueue])
numerator = sum([task.turnaroundTime() for task in self.doneQueue])
denominator = len(self.doneQueue)
return (numerator, denominator)
class NPScheduler:
def __init__(self, N, policy='SJF'):
self.N = N # number of time steps to schedule
self.running = None
self.clock = 0
self.policy = policy
self.readyQueue = MinHeap()
self.notReadyQueue = FIFO()
self.ganttChart = FIFO()
# instantiate the readyQueue, which may be a FIFO or MinHeap
# you may need additional queues for
# - tasks that have been added but not released yet
# - tasks that have been completed
# - the Gantt chart
self.lastruntime = 0
self.numOfTask = 0
def addTask(self, task):
task.scheme = self.policy
# for statistic
self.numOfTask = self.numOfTask + 1
if task.releaseTime() <= self.clock:
self.readyQueue.put(task)
else:
self.notReadyQueue.put(task)
# if the release time of the new task is not in the future, then
# put it in ready queue; otherwise, put into not-ready queue.
# you may need to copy the scheduler policy into the task
def dispatch(self, task):
r = self.readyQueue.head()
if r == None:
self.ganttChart.put(None)
return
self.running = task
self.readyQueue.get().lastDispatchedTime = self.clock
self.ganttChart.put(r)
for i in self.readyQueue:
i.incrWaitTime()
# dispatch here means assign the chosen task as the one to run
# in the current time step.
# the task should be removed from ready-queue by caller;
# The task may be empty (None).
# This method will make an entry into the Gantt chart and perform
# bookkeeping, including
# - recording the last dispatched time of this task,
# - increment the wait times of those tasks not scheduled
# but in the ready queue
def releaseTasks(self):
'''
this is called at the beginning of scheduling each time step to see
if new tasks became ready to be released to ready queue, when their
release time is no later than the current clock.
'''
while True:
r = self.notReadyQueue.head()
# assuming the notReadyQueue outputs by release time
if r is None or r.releaseTime() > self.clock:
break
r = self.notReadyQueue.get()
#r.setPriorityScheme(self.policy) little weird in my opinion
r.scheme = self.policy
if r:
r.fifo_prio = self.clock
self.readyQueue.put(r)
def checkTaskCompletion(self):
# if there is a current running task, check if it has just finished.
# (i.e., decrement remaining time and see if it has more work to do.
# If so, perform bookkeeping for completing the task,
# - move task to done-queue, set its completion time and lastrun time
# set the scheduler running task to None, and return True
# (so that a new task may be picked.)
# but if not completed, return False.
# If there is no current running task, also return True.
if self.running is None:
return True
# your code here
self.running.decrRemaining()
if self.running.done() == True:
self.running.completionTime = self.clock
self.running.lastDispatchedTime = self.clock
#for statistic
self.lastruntime = self.clock
return True
else:
return False
def schedule(self):
# scheduler that handles nonpreemptive scheduling.
# the policy such as RR, SJF, or FCFS is handled by the task as it
# defines the attribute to compare (in its __iter__() method)
# first, check if added but unreleased tasks may now be released
# (i.e., added to ready queue)
self.releaseTasks()
if self.checkTaskCompletion() == False:
self.ganttChart.put(self.running)
for i in self.readyQueue:
i.incrWaitTime()
# There is a current running task and it is not done yet!
# the same task will continue running to its completion.
# simply redispatch the current running task.
else:
self.running = self.readyQueue.head()
self.dispatch(self.readyQueue.head())
# task completed or no running task.
# get the next task from priority queue and dispatch it.
def clockGen(self):
for self.clock in range(self.N):
# now run scheduler here
self.schedule()
yield self.clock
def getSchedule(self):
return '-'.join(map(str, self.ganttChart))
# return self.ganttChart
def getThroughput(self):
return (self.numOfTask, self.lastruntime)
# calculate and return throughput as a tuple
def getWaitTime(self):
# calculate and return
s = set(self.ganttChart)
total_waiting_time = 0
for i in s:
if i:
total_waiting_time = total_waiting_time + i.waitingTime
return (total_waiting_time, self.numOfTask)
def getTurnaroundTime(self):
# calculate the turnaround time in terms of a tuple with
# separate turnaround times, #processes
s = set(self.ganttChart)
total_turnaround_time = 0
for i in s:
if i:
total_turnaround_time = total_turnaround_time + i.completionTime - i.release
return (total_turnaround_time, self.numOfTask)
