"""A multi-producer, multi-consumer queue.""" from time import time as _time try: import threading as _threading except ImportError: import dummy_threading as _threading from collections import deque import heapq __all__ = ['Empty', 'Full', 'Queue', 'PriorityQueue', 'LifoQueue'] class Empty(Exception): "Exception raised by Queue.get(block=0)/get_nowait()." pass class Full(Exception): "Exception raised by Queue.put(block=0)/put_nowait()." pass class Queue: """Create a queue object with a given maximum size. If maxsize is <= 0, the queue size is infinite. """ def __init__(self, maxsize=0): self.maxsize = maxsize self._init(maxsize) # mutex must be held whenever the queue is mutating. All methods # that acquire mutex must release it before returning. mutex # is shared between the three conditions, so acquiring and # releasing the conditions also acquires and releases mutex. self.mutex = _threading.Lock() # Notify not_empty whenever an item is added to the queue; a # thread waiting to get is notified then. self.not_empty = _threading.Condition(self.mutex) # Notify not_full whenever an item is removed from the queue; # a thread waiting to put is notified then. self.not_full = _threading.Condition(self.mutex) # Notify all_tasks_done whenever the number of unfinished tasks # drops to zero; thread waiting to join() is notified to resume self.all_tasks_done = _threading.Condition(self.mutex) self.unfinished_tasks = 0 def task_done(self): """Indicate that a formerly enqueued task is complete. Used by Queue consumer threads. For each get() used to fetch a task, a subsequent call to task_done() tells the queue that the processing on the task is complete. If a join() is currently blocking, it will resume when all items have been processed (meaning that a task_done() call was received for every item that had been put() into the queue). Raises a ValueError if called more times than there were items placed in the queue. """ self.all_tasks_done.acquire() try: unfinished = self.unfinished_tasks - 1 if unfinished <= 0: if unfinished < 0: raise ValueError('task_done() called too many times') self.all_tasks_done.notify_all() self.unfinished_tasks = unfinished finally: self.all_tasks_done.release() def join(self): """Blocks until all items in the Queue have been gotten and processed. The count of unfinished tasks goes up whenever an item is added to the queue. The count goes down whenever a consumer thread calls task_done() to indicate the item was retrieved and all work on it is complete. When the count of unfinished tasks drops to zero, join() unblocks. """ self.all_tasks_done.acquire() try: while self.unfinished_tasks: self.all_tasks_done.wait() finally: self.all_tasks_done.release() def qsize(self): """Return the approximate size of the queue (not reliable!).""" self.mutex.acquire() n = self._qsize() self.mutex.release() return n def empty(self): """Return True if the queue is empty, False otherwise (not reliable!).""" self.mutex.acquire() n = not self._qsize() self.mutex.release() return n def full(self): """Return True if the queue is full, False otherwise (not reliable!).""" self.mutex.acquire() n = 0 < self.maxsize == self._qsize() self.mutex.release() return n def put(self, item, block=True, timeout=None): """Put an item into the queue. If optional args 'block' is true and 'timeout' is None (the default), block if necessary until a free slot is available. If 'timeout' is a positive number, it blocks at most 'timeout' seconds and raises the Full exception if no free slot was available within that time. Otherwise ('block' is false), put an item on the queue if a free slot is immediately available, else raise the Full exception ('timeout' is ignored in that case). """ self.not_full.acquire() try: if self.maxsize > 0: if not block: if self._qsize() == self.maxsize: raise Full elif timeout is None: while self._qsize() == self.maxsize: self.not_full.wait() elif timeout < 0: raise ValueError("'timeout' must be a positive number") else: endtime = _time() + timeout while self._qsize() == self.maxsize: remaining = endtime - _time() if remaining <= 0.0: raise Full self.not_full.wait(remaining) self._put(item) self.unfinished_tasks += 1 self.not_empty.notify() finally: self.not_full.release() def put_nowait(self, item): """Put an item into the queue without blocking. Only enqueue the item if a free slot is immediately available. Otherwise raise the Full exception. """ return self.put(item, False) def get(self, block=True, timeout=None): """Remove and return an item from the queue. If optional args 'block' is true and 'timeout' is None (the default), block if necessary until an item is available. If 'timeout' is a positive number, it blocks at most 'timeout' seconds and raises the Empty exception if no item was available within that time. Otherwise ('block' is false), return an item if one is immediately available, else raise the Empty exception ('timeout' is ignored in that case). """ self.not_empty.acquire() try: if not block: if not self._qsize(): raise Empty elif timeout is None: while not self._qsize(): self.not_empty.wait() elif timeout < 0: raise ValueError("'timeout' must be a positive number") else: endtime = _time() + timeout while not self._qsize(): remaining = endtime - _time() if remaining <= 0.0: raise Empty self.not_empty.wait(remaining) item = self._get() self.not_full.notify() return item finally: self.not_empty.release() def get_nowait(self): """Remove and return an item from the queue without blocking. Only get an item if one is immediately available. Otherwise raise the Empty exception. """ return self.get(False) # Override these methods to implement other queue organizations # (e.g. stack or priority queue). # These will only be called with appropriate locks held # Initialize the queue representation def _init(self, maxsize): self.queue = deque() def _qsize(self, len=len): return len(self.queue) # Put a new item in the queue def _put(self, item): self.queue.append(item) # Get an item from the queue def _get(self): return self.queue.popleft() class PriorityQueue(Queue): '''Variant of Queue that retrieves open entries in priority order (lowest first). Entries are typically tuples of the form: (priority number, data). ''' def _init(self, maxsize): self.queue = [] def _qsize(self, len=len): return len(self.queue) def _put(self, item, heappush=heapq.heappush): heappush(self.queue, item) def _get(self, heappop=heapq.heappop): return heappop(self.queue) class LifoQueue(Queue): '''Variant of Queue that retrieves most recently added entries first.''' def _init(self, maxsize): self.queue = [] def _qsize(self, len=len): return len(self.queue) def _put(self, item): self.queue.append(item) def _get(self): return self.queue.pop()