Unexpected Behavior when Implementing Dijkstra's Algorithm with a Priority Queue in Python
I'm working on a personal project and I'm testing a new approach and I'm sure I'm missing something obvious here, but I'm confused about I'm sure I'm missing something obvious here, but I'm trying to implement Dijkstra's algorithm to find the shortest path in a weighted graph using Python's `heapq` for the priority queue. However, I keep getting incorrect results for certain paths, particularly when the graph has multiple paths with the same weight. Here's a simplified version of my code: ```python import heapq from collections import defaultdict class Graph: def __init__(self): self.edges = defaultdict(list) def add_edge(self, u, v, weight): self.edges[u].append((v, weight)) self.edges[v].append((u, weight)) # for undirected graph def dijkstra(self, start): min_heap = [(0, start)] # (cost, vertex) distances = {vertex: float('infinity') for vertex in self.edges} distances[start] = 0 visited = set() while min_heap: current_distance, current_vertex = heapq.heappop(min_heap) if current_vertex in visited: continue visited.add(current_vertex) for neighbor, weight in self.edges[current_vertex]: distance = current_distance + weight if distance < distances[neighbor]: distances[neighbor] = distance heapq.heappush(min_heap, (distance, neighbor)) return distances # Usage graph = Graph() graph.add_edge('A', 'B', 1) graph.add_edge('A', 'C', 1) graph.add_edge('B', 'C', 1) graph.add_edge('B', 'D', 5) graph.add_edge('C', 'D', 1) shortest_paths = graph.dijkstra('A') print(shortest_paths) ``` When I run the code, I see that the output for the shortest distance to 'D' from 'A' is 2, which is correct. However, if I add an edge between 'B' and 'C' with a weight of 3 instead of 1, the output for 'D' becomes `5` instead of `3`. It's like the algorithm is not recalculating the distance correctly when multiple paths to the same node exist with different weights. I have checked my implementation against a few algorithms online, and it seems to follow the basic structure. I am using Python 3.9. I suspect it might be related to how I'm managing the priority queue or perhaps the handling of edges with the same weight. Any insights or suggestions on what I might be missing? For context: I'm using Python on Windows. What are your experiences with this? This is my first time working with Python LTS. This is for a desktop app running on Linux. Is there a simpler solution I'm overlooking? This issue appeared after updating to Python latest.