Implement a Priority Queue with `heapq`

import heapq

class PriorityQueue:
    def __init__(self):
        # A list to store items, where the first element is the priority.
        # heapq maintains the min-heap property: item[0] <= item[0] of its children.
        self._queue = []
        # A counter to ensure consistent ordering for items with the same priority
        # and to break ties (lower index means older item).
        self._index = 0

    def push(self, item, priority):
        # Tuples are compared lexicographically, so (priority, index, item) works.
        # The smaller priority comes first. If priorities are equal, the smaller index comes first.
        heapq.heappush(self._queue, (priority, self._index, item))
        self._index += 1

    def pop(self):
        # Removes and returns the smallest item (highest priority)
        if not self._queue:
            raise IndexError("pop from an empty priority queue")
        # We only care about the actual item, not priority or index
        return heapq.heappop(self._queue)[-1]

    def is_empty(self):
        return not self._queue

    def size(self):
        return len(self._queue)

# Usage
pq = PriorityQueue()

pq.push('task A', 3)
pq.push('task B', 1)
pq.push('task C', 2)
pq.push('task D', 1) # Same priority as task B, but inserted later

print(f"Priority Queue size: {pq.size()}")

print(f"Popped item: {pq.pop()}") # Should be 'task B' (priority 1, earlier index)
print(f"Popped item: {pq.pop()}") # Should be 'task D' (priority 1, later index)
print(f"Popped item: {pq.pop()}") # Should be 'task C' (priority 2)
print(f"Popped item: {pq.pop()}") # Should be 'task A' (priority 3)

print(f"Is Priority Queue empty? {pq.is_empty()}")

try:
    pq.pop()
except IndexError as e:
    print(f"Error: {e}")