Question

Sorry for such a silly question but Python docs are confusing…

Link 1: Queue Implementation
http://docs.python.org/library/queue.html

It says that Queue has a class for the priority queue. But I could not find how to implement it.

class Queue.PriorityQueue(maxsize=0)

Link 2: Heap Implementation
http://docs.python.org/library/heapq.html

Here they say that we can implement priority queues indirectly using heapq

pq = []                         # list of entries arranged in a heap
entry_finder = {}               # mapping of tasks to entries
REMOVED = '<removed-task>'      # placeholder for a removed task
counter = itertools.count()     # unique sequence count

def add_task(task, priority=0):
    'Add a new task or update the priority of an existing task'
    if task in entry_finder:
        remove_task(task)
    count = next(counter)
    entry = [priority, count, task]
    entry_finder[task] = entry
    heappush(pq, entry)

def remove_task(task):
    'Mark an existing task as REMOVED.  Raise KeyError if not found.'
    entry = entry_finder.pop(task)
    entry[-1] = REMOVED

def pop_task():
    'Remove and return the lowest priority task. Raise KeyError if empty.'
    while pq:
        priority, count, task = heappop(pq)
        if task is not REMOVED:
            del entry_finder[task]
            return task
    raise KeyError('pop from an empty priority queue'

Which is the most efficient priority queue implementation in Python? And how to implement it?

Answer 1

The version in the Queue module is implemented using the heapq module, so they have equal efficiency for the underlying heap operations.

That said, the Queue version is slower because it adds locks, encapsulation, and a nice object oriented API.

The priority queue suggestions shown in the heapq docs are meant to show how to add additional capabilities to a priority queue (such as sort stability and the ability to change the priority of a previously enqueued task). If you don’t need those capabilities, then the basic heappush and heappop functions will give you the fastest performance.