👀 Views: 6229 💬 Answers: 1 📅 Created: 2025-06-03

python algorithm dijkstra graph-theory Python

I'm deploying to production and I'm maintaining legacy code that I'm trying to implement Dijkstra's algorithm in Python to find the shortest path in a weighted graph, but I'm working with inconsistent results when processing certain nodes. I have defined my graph using a dictionary of dictionaries for adjacency representation. The question arises when I attempt to find the shortest path from a source node to a target node; sometimes, the algorithm returns a longer path than expected. Here's a simplified version of my code: ```python import heapq class Graph: def __init__(self): self.edges = {} def add_edge(self, from_node, to_node, weight): if from_node not in self.edges: self.edges[from_node] = {} self.edges[from_node][to_node] = weight def dijkstra(self, start, end): priority_queue = [(0, start)] # (cost, node) distances = {node: float('inf') for node in self.edges} distances[start] = 0 while priority_queue: current_distance, current_node = heapq.heappop(priority_queue) if current_distance > distances[current_node]: continue for neighbor, weight in self.edges.get(current_node, {}).items(): distance = current_distance + weight if distance < distances[neighbor]: distances[neighbor] = distance heapq.heappush(priority_queue, (distance, neighbor)) return distances[end] ``` When I test this algorithm with the following graph: ```python graph = Graph() graph.add_edge('A', 'B', 1) graph.add_edge('A', 'C', 4) graph.add_edge('B', 'C', 2) graph.add_edge('B', 'D', 5) graph.add_edge('C', 'D', 1) ``` Calling `graph.dijkstra('A', 'D')` should return a shortest path cost of 4 (via B and C). However, it sometimes returns 5 if I modify the edge weights slightly, which seems incorrect. I've also verified that the graph does not have negative weights, which should be fine for Dijkstra's. I've tried debugging by printing the distances dictionary at various points and verified that the priority queue is being updated correctly. However, the outputs remain inconsistent. Is there a flaw in my implementation logic, or could it be a specific edge case I'm missing? Any insights would be greatly appreciated! My team is using Python for this application. Am I missing something obvious? I'm using Python LTS in this project. Thanks, I really appreciate it!