How can I optimize Dijkstra's algorithm in Python for better performance?

How can I optimize Dijkstra's algorithm in Python for better performance?

To optimize Dijkstra's algorithm, consider using a priority queue implemented with a binary heap or Fibonacci heap.

What data structures work best with Dijkstra's algorithm?

Using a min-heap or priority queue can significantly improve the performance of Dijkstra's algorithm.

Are there any libraries in Python that can help with this?

Yes, libraries like heapq for priority queues and networkx for graph operations can be very helpful.

Can you provide a code example?

Sure! Here's a simple implementation using heapq:

import heapq

def dijkstra(graph, start):
    queue = [(0, start)]
    distances = {node: float('infinity') for node in graph}
    distances[start] = 0

    while queue:
        current_distance, current_node = heapq.heappop(queue)

        if current_distance > distances[current_node]:
            continue

        for neighbor, weight in graph[current_node].items():
            distance = current_distance + weight

            if distance < distances[neighbor]:
                distances[neighbor] = distance
                heapq.heappush(queue, (distance, neighbor))

    return distances