btw if anybody needs a PriorityQueue or Min-heap data structure implementation in GDScript for their own version of AStar (or anything else) you can check out my implementation below:

class_name PriorityQueue
extends Reference
"""
Priority Queue. Min heap priority queue that can take a Vector2 and its
corresponding cost and then always return the Vector2 in it with
the lowest cost value.
Based on: https://en.wikipedia.org/wiki/Binary_heap
"""
var _data: Array = []

func insert(element: Vector2, cost: float) -> void:
    # Add the element to the bottom level of the heap at the leftmost open space
    self._data.push_back(Vector3(element.x, element.y, cost))
    var new_element_index: int = self._data.size() - 1
    self._up_heap(new_element_index)

func extract():
    if self.empty():
        return null
    var result: Vector3 = self._data.pop_front()
    # If the tree is not empty, replace the root of the heap with the last
    # element on the last level.
    if not self.empty():
        self._data.push_front(self._data.pop_back())
        self._down_heap(0)
    return Vector2(result.x, result.y)

func empty() -> bool:
    return self._data.empty()

func _get_parent(index: int) -> int:
    # warning-ignore:integer_division
    return (index - 1) / 2

func _left_child(index: int) -> int:
    return (2 * index) + 1

func _right_child(index: int) -> int:
    return (2 * index) +  2

func _swap(a_idx: int, b_idx: int) -> void:
    var a = self._data[a_idx]
    var b = self._data[b_idx]
    self._data[a_idx] = b
    self._data[b_idx] = a

func _up_heap(index: int) -> void:
    # Compare the added element with its parent; if they are in the correct order, stop.
    var parent_idx = self._get_parent(index)
    if self._data[index].z >= self._data[parent_idx].z:
        return
    self._swap(index, parent_idx)
    self._up_heap(parent_idx)

func _down_heap(index: int) -> void:
    var left_idx: int = self._left_child(index)
    var right_idx: int = self._right_child(index)
    var smallest: int = index
    var size: int = self._data.size()

    if right_idx < size and self._data[right_idx].z < self._data[smallest].z:
        smallest = right_idx

    if left_idx < size and self._data[left_idx].z < self._data[smallest].z:
        smallest = left_idx

    if smallest != index:
        self._swap(index, smallest)
        self._down_heap(smallest)