👀 Views: 53 💬 Answers: 1 📅 Created: 2025-06-11

python algorithms dijkstra graphs Python

I'm currently implementing Dijkstra's algorithm in Python using the `heapq` module for priority queue management, but I'm running into an issue with cases where multiple edges have equal weights. Specifically, I am observing inconsistent path results when two paths have the same total cost. 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)) def dijkstra(self, start): queue = [(0, start)] distances = {vertex: float('infinity') for vertex in self.edges} distances[start] = 0 while queue: current_distance, current_vertex = heapq.heappop(queue) if current_distance > distances[current_vertex]: continue for neighbor, weight in self.edges[current_vertex]: distance = current_distance + weight if distance < distances[neighbor]: distances[neighbor] = distance heapq.heappush(queue, (distance, neighbor)) return distances g = Graph() g.add_edge('A', 'B', 1) g.add_edge('A', 'C', 1) g.add_edge('B', 'D', 1) g.add_edge('C', 'D', 1) print(g.dijkstra('A')) ``` When I run this code, I expect that both paths from 'A' to 'D' (through 'B' and 'C') would yield the same distance of 2. However, the behavior seems to be unpredictable based on the order of edge insertion. For example, if I add the edge 'C' to 'D' before 'B' to 'D', I sometimes get: ``` {'A': 0, 'B': 1, 'C': 1, 'D': 2} ``` And other times I see: ``` {'A': 0, 'B': 2, 'C': 1, 'D': 1} ``` Have I missed something in the implementation? Shouldn't Dijkstra's algorithm return the shortest path consistently regardless of edge insertion order? Any insights on why this is happening would be greatly appreciated!