[2] | 1 | """A generally useful event scheduler class.
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| 2 |
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| 3 | Each instance of this class manages its own queue.
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| 4 | No multi-threading is implied; you are supposed to hack that
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| 5 | yourself, or use a single instance per application.
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| 6 |
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| 7 | Each instance is parametrized with two functions, one that is
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| 8 | supposed to return the current time, one that is supposed to
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| 9 | implement a delay. You can implement real-time scheduling by
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| 10 | substituting time and sleep from built-in module time, or you can
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| 11 | implement simulated time by writing your own functions. This can
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| 12 | also be used to integrate scheduling with STDWIN events; the delay
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| 13 | function is allowed to modify the queue. Time can be expressed as
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| 14 | integers or floating point numbers, as long as it is consistent.
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| 15 |
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| 16 | Events are specified by tuples (time, priority, action, argument).
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| 17 | As in UNIX, lower priority numbers mean higher priority; in this
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| 18 | way the queue can be maintained as a priority queue. Execution of the
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| 19 | event means calling the action function, passing it the argument
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| 20 | sequence in "argument" (remember that in Python, multiple function
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| 21 | arguments are be packed in a sequence).
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| 22 | The action function may be an instance method so it
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| 23 | has another way to reference private data (besides global variables).
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| 24 | """
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| 25 |
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| 26 | # XXX The timefunc and delayfunc should have been defined as methods
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| 27 | # XXX so you can define new kinds of schedulers using subclassing
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| 28 | # XXX instead of having to define a module or class just to hold
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| 29 | # XXX the global state of your particular time and delay functions.
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| 30 |
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| 31 | import heapq
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| 32 | from collections import namedtuple
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| 33 |
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| 34 | __all__ = ["scheduler"]
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| 35 |
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| 36 | Event = namedtuple('Event', 'time, priority, action, argument')
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| 37 |
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| 38 | class scheduler:
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| 39 | def __init__(self, timefunc, delayfunc):
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| 40 | """Initialize a new instance, passing the time and delay
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| 41 | functions"""
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| 42 | self._queue = []
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| 43 | self.timefunc = timefunc
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| 44 | self.delayfunc = delayfunc
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| 45 |
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| 46 | def enterabs(self, time, priority, action, argument):
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| 47 | """Enter a new event in the queue at an absolute time.
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| 48 |
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| 49 | Returns an ID for the event which can be used to remove it,
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| 50 | if necessary.
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| 51 |
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| 52 | """
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| 53 | event = Event(time, priority, action, argument)
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| 54 | heapq.heappush(self._queue, event)
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| 55 | return event # The ID
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| 56 |
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| 57 | def enter(self, delay, priority, action, argument):
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| 58 | """A variant that specifies the time as a relative time.
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| 59 |
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| 60 | This is actually the more commonly used interface.
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| 61 |
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| 62 | """
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| 63 | time = self.timefunc() + delay
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| 64 | return self.enterabs(time, priority, action, argument)
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| 65 |
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| 66 | def cancel(self, event):
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| 67 | """Remove an event from the queue.
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| 68 |
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| 69 | This must be presented the ID as returned by enter().
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| 70 | If the event is not in the queue, this raises ValueError.
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| 71 |
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| 72 | """
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| 73 | self._queue.remove(event)
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| 74 | heapq.heapify(self._queue)
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| 75 |
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| 76 | def empty(self):
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| 77 | """Check whether the queue is empty."""
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| 78 | return not self._queue
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| 79 |
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| 80 | def run(self):
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| 81 | """Execute events until the queue is empty.
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| 82 |
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| 83 | When there is a positive delay until the first event, the
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| 84 | delay function is called and the event is left in the queue;
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| 85 | otherwise, the event is removed from the queue and executed
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| 86 | (its action function is called, passing it the argument). If
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| 87 | the delay function returns prematurely, it is simply
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| 88 | restarted.
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| 89 |
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| 90 | It is legal for both the delay function and the action
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[391] | 91 | function to modify the queue or to raise an exception;
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[2] | 92 | exceptions are not caught but the scheduler's state remains
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| 93 | well-defined so run() may be called again.
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| 94 |
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| 95 | A questionable hack is added to allow other threads to run:
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| 96 | just after an event is executed, a delay of 0 is executed, to
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| 97 | avoid monopolizing the CPU when other threads are also
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| 98 | runnable.
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| 99 |
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| 100 | """
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| 101 | # localize variable access to minimize overhead
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| 102 | # and to improve thread safety
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| 103 | q = self._queue
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| 104 | delayfunc = self.delayfunc
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| 105 | timefunc = self.timefunc
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| 106 | pop = heapq.heappop
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| 107 | while q:
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| 108 | time, priority, action, argument = checked_event = q[0]
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| 109 | now = timefunc()
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| 110 | if now < time:
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| 111 | delayfunc(time - now)
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| 112 | else:
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| 113 | event = pop(q)
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| 114 | # Verify that the event was not removed or altered
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| 115 | # by another thread after we last looked at q[0].
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| 116 | if event is checked_event:
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| 117 | action(*argument)
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| 118 | delayfunc(0) # Let other threads run
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| 119 | else:
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| 120 | heapq.heappush(q, event)
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| 121 |
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| 122 | @property
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| 123 | def queue(self):
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| 124 | """An ordered list of upcoming events.
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| 125 |
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| 126 | Events are named tuples with fields for:
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| 127 | time, priority, action, arguments
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| 128 |
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| 129 | """
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| 130 | # Use heapq to sort the queue rather than using 'sorted(self._queue)'.
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| 131 | # With heapq, two events scheduled at the same time will show in
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| 132 | # the actual order they would be retrieved.
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| 133 | events = self._queue[:]
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| 134 | return map(heapq.heappop, [events]*len(events))
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