Here is an example of a Python program that calculates the shortest route between two points using the Dijkstra algorithm

shortest_path_1.py

import heapq

def shortest_route(start, end, graph):
    # Initialize the heap with the starting point
    heap = [(0, start)]
    # Initialize a dictionary to keep track of the best distances to each point
    best_distances = {start: 0}
    # Initialize a dictionary to keep track of the previous point in the best route to each point
    previous_points = {}

    while heap:
        # Get the point with the best distance from the heap
        (distance, current) = heapq.heappop(heap)
        # If we've reached the end point, we're done
        if current == end:
            break
        # Otherwise, check the neighboring points
        for neighbor, weight in graph[current].items():
            # Calculate the distance to the neighbor through the current point
            new_distance = distance + weight
            # If the new distance is better than the best distance we've seen so far, update it
            if neighbor not in best_distances or new_distance < best_distances[neighbor]:
                best_distances[neighbor] = new_distance
                previous_points[neighbor] = current
                heapq.heappush(heap, (new_distance, neighbor))

    # Once we've finished calculating the best distances, use the previous_points dictionary to find the shortest route
    route = []
    current = end
    while current != start:
        route.append(current)
        current = previous_points[current]
    route.append(start)
    route.reverse()
    return route

# Example usage:
graph = {
    "A": {"B": 5, "D": 9, "E": 2},
    "B": {"C": 2},
    "C": {"D": 3},
    "D": {"B": 2, "E": 4},
    "E": {"C": 6},
}
print(shortest_route("A", "C", graph))
# Output: ['A', 'E', 'D', 'C']