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	* Improve algorithm -- no more O(n) steps except sched.cancel(). * Improve thread safety of sched.run() and sched.empty() (other threads could alter the queue between the time the queue was first checked and when the lead event was deleted). * Localize variable access in sched.run() to minimize overhead.
		
			
				
	
	
		
			117 lines
		
	
	
	
		
			4.4 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			117 lines
		
	
	
	
		
			4.4 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
"""A generally useful event scheduler class.
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Each instance of this class manages its own queue.
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No multi-threading is implied; you are supposed to hack that
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yourself, or use a single instance per application.
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Each instance is parametrized with two functions, one that is
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supposed to return the current time, one that is supposed to
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implement a delay.  You can implement real-time scheduling by
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substituting time and sleep from built-in module time, or you can
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implement simulated time by writing your own functions.  This can
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also be used to integrate scheduling with STDWIN events; the delay
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function is allowed to modify the queue.  Time can be expressed as
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integers or floating point numbers, as long as it is consistent.
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Events are specified by tuples (time, priority, action, argument).
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As in UNIX, lower priority numbers mean higher priority; in this
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way the queue can be maintained as a priority queue.  Execution of the
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event means calling the action function, passing it the argument.
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Remember that in Python, multiple function arguments can be packed
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in a tuple.   The action function may be an instance method so it
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has another way to reference private data (besides global variables).
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Parameterless functions or methods cannot be used, however.
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"""
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# XXX The timefunc and delayfunc should have been defined as methods
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# XXX so you can define new kinds of schedulers using subclassing
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# XXX instead of having to define a module or class just to hold
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# XXX the global state of your particular time and delay functions.
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import heapq
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__all__ = ["scheduler"]
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class scheduler:
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    def __init__(self, timefunc, delayfunc):
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        """Initialize a new instance, passing the time and delay
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        functions"""
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        self.queue = []
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        self.timefunc = timefunc
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        self.delayfunc = delayfunc
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    def enterabs(self, time, priority, action, argument):
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        """Enter a new event in the queue at an absolute time.
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        Returns an ID for the event which can be used to remove it,
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        if necessary.
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        """
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        event = time, priority, action, argument
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        heapq.heappush(self.queue, event)
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        return event # The ID
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    def enter(self, delay, priority, action, argument):
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        """A variant that specifies the time as a relative time.
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        This is actually the more commonly used interface.
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        """
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        time = self.timefunc() + delay
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        return self.enterabs(time, priority, action, argument)
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    def cancel(self, event):
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        """Remove an event from the queue.
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        This must be presented the ID as returned by enter().
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        If the event is not in the queue, this raises RuntimeError.
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        """
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        self.queue.remove(event)
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        heapq.heapify(self.queue)
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    def empty(self):
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        """Check whether the queue is empty."""
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        return not not self.queue
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    def run(self):
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        """Execute events until the queue is empty.
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        When there is a positive delay until the first event, the
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        delay function is called and the event is left in the queue;
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        otherwise, the event is removed from the queue and executed
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        (its action function is called, passing it the argument).  If
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        the delay function returns prematurely, it is simply
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        restarted.
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        It is legal for both the delay function and the action
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        function to to modify the queue or to raise an exception;
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        exceptions are not caught but the scheduler's state remains
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        well-defined so run() may be called again.
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        A questionably hack is added to allow other threads to run:
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        just after an event is executed, a delay of 0 is executed, to
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        avoid monopolizing the CPU when other threads are also
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        runnable.
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        """
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        # localize variable access to minimize overhead
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        # and to improve thread safety
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        q = self.queue
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        delayfunc = self.delayfunc
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        timefunc = self.timefunc
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        pop = heapq.heappop
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        while q:
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            time, priority, action, argument = checked_event = q[0]
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            now = timefunc()
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            if now < time:
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                delayfunc(time - now)
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            else:
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                event = pop(q)
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                # Verify that the event was not removed or altered
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                # by another thread after we last looked at q[0].
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                if event is checked_event:
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                    void = action(*argument)
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                    delayfunc(0)   # Let other threads run
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                else:
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                    heapq.heappush(event)
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