Heap sort and priority queue implementation in Python

Algorithms/heap_sort.py

@@ -0,0 +1,26 @@
+def heapify_max(arr, size, index):
+    left = 2*index + 1
+    right = 2*index + 2
+    highest = index
+
+    if left < size and arr[highest] < arr[left]:
+        highest = left
+    if right < size and arr[highest] < arr[right]:
+        highest = right
+
+    if highest != index:
+        arr[highest], arr[index] = arr[index], arr[highest]
+        heapify_max(arr, size, highest)
+
+def heap_sort(arr):
+    n = len(arr)
+    for i in range(n//2 - 1, -1, -1):
+        heapify_max(arr, n, i)
+    for i in range(n - 1, 0, -1):
+        arr[0], arr[i] = arr[i], arr[0]
+        heapify_max(arr, i, 0)
+
+arr = [35, 33, 42, 10, 14, 19, 27, 44, 26, 31]
+# heapify_max(arr, len(arr), 0)
+# heap_sort(arr)
+# print(arr)

Algorithms/priority_queue.py

@@ -0,0 +1,39 @@
+# Priority queue implementation using heap
+
+import heapq
+
+class PriorityQueue:
+    def __init__ (self):
+        self.pq = []
+
+    def enqueue(self, priority, item):
+        self.pq.append(((priority, item)))
+        heapq._heapify_max(self.pq)
+
+    def dequeue(self):
+        if self.is_empty():
+            return "Can't dequeue from an empty priority queue!"
+        return f"Dequeued: {heapq._heappop_max(self.pq)[1]}"
+
+    def is_empty (self):
+        return len(self.pq) == 0
+
+    def peek (self):
+        return "Priority queue empty!" if self.is_empty() else f"Top element: {self.pq[0][1]}"
+
+    def print_queue (self):
+        return f"Priority Queue: {self.pq}"
+
+pq = PriorityQueue()
+print(pq.dequeue())
+pq.enqueue(3, 45)
+pq.enqueue(7, 23)
+pq.enqueue(1, 25)
+pq.enqueue(5, 15)
+pq.enqueue(4, 35)
+print(pq.peek())
+print(pq.print_queue())
+print(pq.dequeue())
+print(pq.print_queue())
+print(pq.dequeue())
+print(pq.print_queue())