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    def size(self) -> int:
        """Traverses the linked list and returns the number of nodes in it"""
        if self.is_empty():
            return 0
        size = 0
        current_node = self.head
        while current_node is not None:
            current_node = current_node.next_node
            size += 1
        return size

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from typing import Any, Union


class Node:
    """A linked list node implementation"""

    def __init__(self, node_data: Any) -> None:
        """Initialize the node with the given data and pointing to None"""
        self._data = node_data
        self._next_node = None

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from typing import Any, Union


class Node:
    """A linked list node implementation"""

    def __init__(self, node_data: Any) -> None:
        """Initialize the node with the given data and pointing to None"""
        self._data = node_data
        self._next_node = None

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import heapq
from typing import Union


class PriorityQueue:
    """A priority queue implementation based on heapq"""

    insertion_count = 0

    def __init__(self) -> None:

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    def is_empty(self) -> bool:
        """Returns True is the priority queue is empty"""
        return not self.pqueue

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    def insert(self, task: str, priority: int) -> None:
        """Add an item to the priority queue"""
        heapq.heappush(self.pqueue, (priority, self.insertion_count, task))
        self.insertion_count += 1

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    def pull(self) -> Union[str, None]:
        """
        Return and remove the task with the highest priority.
        Since Python's heapq is implemented as a min heap, a
        smaller number mean the higher priority, i.e. priority 1
        has a higher priority that priority 2.

        Elements with same priority are pulled in the order of
        insertion.
        """

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    def peek(self) -> Union[str, None]:
        """Return the task with the highest priority"""
        if self.is_empty():
            return None
        return self.pqueue[0][2]

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    def size(self) -> int:
        """Return the number of items in the priority queue"""
        return len(self.pqueue)

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import heapq
from typing import Union


class PriorityQueue:
    """A priority queue implementation based on heapq"""

    insertion_count = 0

    def __init__(self) -> None: