Minimum effort path assignment complete.

graphs/minimum_effort_path.py

@@ -1,3 +1,5 @@
+import heapq
+
 def min_effort_path(heights):
     """ Given a 2D array of heights, write a function to return
         the path with minimum effort.
@@ -15,4 +17,31 @@ def min_effort_path(heights):
         int
             minimum effort required to navigate the path from (0, 0) to heights[rows - 1][columns - 1]
     """
-    pass
+    # Implement a guard clause/validate the input
+    if not heights:
+        return 0
+
+    rows = len(heights)
+    columns = len(heights[0])
+    # Initialize the effort matrix with maximum possible effort
+    effort = [[float('inf') for _ in range(columns)] for _ in range(rows)]
+    effort[0][0] = 0
+    # Initialize the priority queue
+    queue = [(0, 0, 0)]
+    while queue:
+        current_effort, x, y = heapq.heappop(queue)
+        # Check if the currentent cell is already visited
+        if effort[x][y] < current_effort:
+            continue
+        # Check the neighbors of the currentent cell
+        for dx, dy in [(0, 1), (1, 0), (0, -1), (-1, 0)]:
+            new_x, new_y = x + dx, y + dy
+            # Check if the new cell is within the grid
+            if 0 <= new_x < rows and 0 <= new_y < columns:
+                new_effort = max(current_effort, abs(heights[new_x][new_y] - heights[x][y]))
+                # Check if the new effort is less than the previous effort
+                if new_effort < effort[new_x][new_y]:
+                    effort[new_x][new_y] = new_effort
+                    heapq.heappush(queue, (new_effort, new_x, new_y))
+    return effort[rows-1][columns-1]
+