Use a negative priority instead, no need to subtract from sys.maxint.
queue.put((-priority, item))
An item with priority -10 will be returned before items with priority -5, for example.
Answer from Martijn Pieters on Stack OverflowPython
docs.python.org › 3 › library › heapq.html
heapq — Heap queue algorithm
def running_median(iterable): "Yields the cumulative median of values seen so far." lo = [] # max-heap hi = [] # min-heap (same size as or one smaller than lo) for x in iterable: if len(lo) == len(hi): heappush_max(lo, heappushpop(hi, x)) yield lo[0] else: heappush(hi, heappushpop_max(lo, x)) yield (lo[0] + hi[0]) / 2 · For example: >>> list(running_median([5.0, 9.0, 4.0, 12.0, 8.0, 9.0])) [5.0, 7.0, 5.0, 7.0, 8.0, 8.5] A priority queue is common use for a heap, and it presents several implementation challenges: Sort stability: how do you get two tasks with equal priorities to be returned in the order they were originally added?
Top answer 1 of 2
47
Use a negative priority instead, no need to subtract from sys.maxint.
queue.put((-priority, item))
An item with priority -10 will be returned before items with priority -5, for example.
2 of 2
10
You can extend the Priority Queue to keep the logic unchanged:
from Queue import PriorityQueue
class DualPriorityQueue(PriorityQueue):
def __init__(self, maxPQ=False):
PriorityQueue.__init__(self)
self.reverse = -1 if maxPQ else 1
def put(self, priority, data):
PriorityQueue.put(self, (self.reverse * priority, data))
def get(self, *args, **kwargs):
priority, data = PriorityQueue.get(self, *args, **kwargs)
return self.reverse * priority, data
minQ = DualPriorityQueue()
maxQ = DualPriorityQueue(maxPQ=True)
minQ.put(10, 'A')
minQ.put(100, 'A')
maxQ.put(10, 'A')
maxQ.put(100,'A')
print "Min DQ: {}".format(minQ.get())
print "Max DQ: {}".format(maxQ.get())
Output:
Min DQ: (10, 'A')
Max DQ: (100, 'A')
Videos
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DSA in Python - Introduction to Priority Queues using Binary Heaps ...
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Heaps & Priority Queues - Heapify, Heap Sort, Heapq Library - DSA ...
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Heaps & Priority Queues in Python - YouTube
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Heaps & Priority Queues in Python
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Maximize Efficiency with this Priority Queue Class in Python - YouTube
GeeksforGeeks
geeksforgeeks.org › python › priority-queue-in-python
Priority Queue in Python - GeeksforGeeks
April 26, 2025 - Let's understand the different ... associated priority. There are two main types: Max Priority Queue: The element with the highest priority is dequeued first....
GitHub
gist.github.com › pavlin-policar › 63e237b5e0b9c8dc1b47b0e4f780a88f
Python implementation of max heap/priority queue · GitHub
Python implementation of max heap/priority queue. GitHub Gist: instantly share code, notes, and snippets.
DigitalOcean
digitalocean.com › community › tutorials › priority-queue-python
How to Use a Priority Queue in Python | DigitalOcean
July 11, 2025 - This tutorial has covered the implementation of a priority queue in Python using both heapq and queue.PriorityQueue. Additionally, it has explored the creation of a max-heap using these modules.
Built In
builtin.com › data-science › priority-queues-in-python
Introduction to Priority Queues in Python | Built In
We can also use the heapq module in Python to implement our priority queue. This implementation has O(log n) time complexity for insertion and extraction of the smallest element. Note that heapq only has a min heap implementation, but there are other ways to use a max heap that we won’t cover ...
Medium
medium.com › @huawei.zhu › built-in-stack-queue-and-priority-queue-in-python-e44a6cbf3771
Built-in stack, queue and priority queue in Python | by Huawei Zhu | Medium
September 2, 2025 - Using queue.PriorityQueue: This approach supports concurrent processes and it’s a class interface. The 2nd one — heapq, is preferred. ... import heapq # also a built-in module in python, and this is min-heap. # To create a max-heap, # just make every item the opposite sign when you push them into the heap #======================== # Test 1: heapify a list #======================== a = [3, 5, 1, 2, 6, 8, 7] heapq.heapify(a) # this turns the list to a priority queue print("a =", a) # note the difference between a and a after heapify() #======================== # Test 2: initialize with an em
Akamai
akamai.com › cloud › guides › python-priority-queue
What is the Python Priority Queue? | Linode Docs
June 17, 2022 - In a max heap, the value of the parent node is greater than the value stored in any of its children. Heaps make it easy to access the highest-priority item, and even insertions are relatively efficient with a logarithmic time complexity.
APXML
apxml.com › courses › advanced-python-programming-ml › chapter-4-advanced-data-structures-algorithms-ml › priority-queues-heaps
Python Priority Queues & Heaps in ML
In some filter-based feature selection methods, features are assigned scores based on criteria like mutual information or correlation with the target variable. A priority queue (e.g., a max-heap implemented using heapq.nlargest) can be used to efficiently find the top
NamasteDev
namastedev.com › home › technology & development › algorithms › priority queues introduction
Priority Queues Introduction - NamasteDev Blogs
October 15, 2025 - Max Priority Queue: Where the element with the highest value has the highest priority and is served before all other elements.
Top answer 1 of 5
7
PriorityQueue by default only support minheaps.
One way to implement max_heaps with it, could be,
from queue import PriorityQueue
# Max Heap
class MaxHeapElement:
def __init__(self, x):
self.x = x
def __lt__(self, other):
return self.x > other.x
def __str__(self):
return str(self.x)
max_heap = PriorityQueue()
max_heap.put(MaxHeapElement(10))
max_heap.put(MaxHeapElement(20))
max_heap.put(MaxHeapElement(15))
max_heap.put(MaxHeapElement(12))
max_heap.put(MaxHeapElement(27))
while not max_heap.empty():
print(max_heap.get())
2 of 5
2
Based on the comments, the simplest way to get maxHeap is to insert negative of the element.
from queue import PriorityQueue
max_heap = PriorityQueue()
max_heap.put(MaxHeapElement(-10))
max_heap.put(MaxHeapElement(-20))
max_heap.put(MaxHeapElement(-15))
max_heap.put(MaxHeapElement(-12))
max_heap.put(MaxHeapElement(-27))
while not max_heap.empty():
print(-1*max_heap.get())
Stackify
stackify.com › a-guide-to-python-priority-queue
A Guide to Python Priority Queue - Stackify
February 18, 2025 - Producer: Adds tasks (e.g., Task 0, Task 1, etc.) to the queue. If the queue reaches its maximum size (2), the put method blocks until a consumer retrieves an item, making room for new entries. Consumer: Processes tasks based on priority.
VisuAlgo
visualgo.net › en › heap
Binary Heap (Priority Queue) - VisuAlgo
C++ STL priority_queue (the default is a Max Priority Queue) and · Java PriorityQueue (the default is a Min Priority Queue). However, the built-in implementation may not be suitable to do some PQ extended operations efficiently (details omitted for pedagogical reason in a certain NUS course). Python heapq exists but its performance is rather slow.
Medium
varun-verma.medium.com › priority-queue-heap-in-python-ef98d5042602
Priority Queue/Heap in Python. Priority Queues are an efficient way to… | by Verma Varun | Medium
October 26, 2024 - Priority Queues are an efficient way to get the min or max element from a list with O(1) time v/s using a min() function that loops through the entire list and gets the min or max element in O(n) time.
Python
docs.python.org › 3 › library › multiprocessing.html
multiprocessing — Process-based parallelism
If this method is used when the associated process is using a pipe or queue then the pipe or queue is liable to become corrupted and may become unusable by other process. Similarly, if the process has acquired a lock or semaphore etc.
Real Python
realpython.com › queue-in-python
Python Stacks, Queues, and Priority Queues in Practice – Real Python
December 1, 2023 - Alternatively, you could ignore the element order until removing one with the highest priority, which you could find using the linear search algorithm. Looking up an element in an unordered list has O(n) time complexity. Sorting the entire queue would be even more expensive, especially when exercised often. Python’s list.sort() method employs an algorithm called Timsort, which has O(n log(n)) worst-case time complexity.
Faun
faun.pub › priority-queue-using-heapq-9d8fccc49d51
Priority Queue — Python
April 28, 2025 - Since we know that we are interested in the middle elements to find the median. We create two heaps. One heap as min-heap and another one as max-heap. This way we are able to keep track of the middle elements in sorted order.
Squash
squash.io › python-priority-queue-a-practical-guide
Python Priority Queue Tutorial
September 13, 2024 - In a max heap, for every node i other than the root, the value of heap[i] is greater than or equal to the values of its children. In a min heap, the value of heap[i] is less than or equal to the values of its children. Binary heaps are an efficient data structure for implementing priority queues because they allow for efficient insertion and removal of elements based on their priority.
HowToDoInJava
howtodoinjava.com › home › python datatypes › python priority queue using queue, heapq and bisect modules
Python Priority Queue using queue, heapq and bisect Modules
March 6, 2024 - The heapq module provides an implementation of the heap queue algorithm, also known as the priority queue algorithm. Heaps are binary trees for which every parent node has a value less than or equal to any of its children, the smallest element is always the root, heap[0]. We use the following methods to push and pop the queue elements: heappush(): pushes the value item onto the heap, maintaining the heap invariant. heappop(): pops and returns the smallest item from the heap, maintaining the heap invariant. The following Python program uses the heapq module to implement a simple priority queue:
Spark By {Examples}
sparkbyexamples.com › home › python › python queue.priorityqueue methods
Python queue.priorityqueue Methods - Spark By {Examples}
May 31, 2024 - We can implement the Priority queue using Python queue.priorityqueue methods. Priorityqueue is similar to Queue but it will remove items from it based on