使用OSMnx包时遇ValueError：图无边缘的路由代码问题

问题背景 #

参考路由查找文章调整代码后，运行时触发ValueError: graph contains no edges错误，代码及错误信息如下：

运行代码 #

import osmnx as ox
import networkx as nx
ox.config(log_console=True, use_cache=True)
# define the start and end locations in latlng
start_latlng = (37.78497,-122.43327)
end_latlng = (37.78071,-122.41445)
# location where you want to find your route
place     = 'San Francisco, California, United States'
# find shortest route based on the mode of travel
mode      = 'walk'        # 'drive', 'bike', 'walk'
# find shortest path based on distance or time
optimizer = 'time'        # 'length','time'
# create graph from OSM within the boundaries of some 
# geocodable place(s)
graph = ox.graph_from_place(place, network_type = mode)
# find the nearest node to the start location
orig_node = ox.distance.nearest_nodes(graph,37.78497,-122.43327 )
# find the nearest node to the end location
dest_node = ox.distance.nearest_nodes(graph,37.78071,-122.41445)
#  find the shortest path
shortest_route = nx.shortest_path(graph,
                                  orig_node,
                                  dest_node,
                                  weight=optimizer)
shortest_route_map = ox.plot_route_folium(graph, shortest_route)
shortest_route_map

错误信息 #

ValueError: graph contains no edges

错误原因及解决方案 #

1. 核心原因：路网数据未成功获取 #

graph_from_place依赖地理编码返回的区域边界，若边界匹配异常（如范围过大/过小、地理编码歧义），会导致无法获取有效路网；此外缓存机制可能加载旧的空数据。

2. 针对性解决步骤 #

• 禁用缓存，重新获取数据
  将ox.config(use_cache=True)改为use_cache=False，或手动删除OSMnx缓存目录（默认路径~/.osmnx/cache），避免加载旧的空缓存。

• 替换区域定义方式，使用包围盒确保覆盖目标点
  放弃graph_from_place，改用graph_from_bbox基于起点终点的经纬度生成精准包围盒，确保路网覆盖目标区域：

  # 计算包围盒，添加0.01度缓冲确保覆盖起点终点
  north = max(start_latlng[0], end_latlng[0]) + 0.01
  south = min(start_latlng[0], end_latlng[0]) - 0.01
  east = max(start_latlng[1], end_latlng[1]) + 0.01
  west = min(start_latlng[1], end_latlng[1]) - 0.01
  # 从包围盒获取路网
  graph = ox.graph_from_bbox(north, south, east, west, network_type=mode)
  

• 修正nearest_nodes参数顺序
  原代码中nearest_nodes的参数顺序错误，该函数要求经度在前，纬度在后，正确调用方式：

  orig_node = ox.distance.nearest_nodes(graph, start_latlng[1], start_latlng[0])
  dest_node = ox.distance.nearest_nodes(graph, end_latlng[1], end_latlng[0])
  

• 验证路网数据有效性
  获取图后，添加以下代码检查节点和边数量，确认路网加载成功：

  print(f"节点数: {len(graph.nodes)}, 边数: {len(graph.edges)}")
  

3. 修正后的完整代码 #

import osmnx as ox
import networkx as nx

# 禁用缓存，避免加载旧的空数据
ox.config(log_console=True, use_cache=False)

# 起点终点坐标（纬度, 经度）
start_latlng = (37.78497, -122.43327)
end_latlng = (37.78071, -122.41445)

# 生成覆盖目标点的包围盒
north = max(start_latlng[0], end_latlng[0]) + 0.01
south = min(start_latlng[0], end_latlng[0]) - 0.01
east = max(start_latlng[1], end_latlng[1]) + 0.01
west = min(start_latlng[1], end_latlng[1]) - 0.01

mode = 'walk'
optimizer = 'time'

# 从包围盒获取步行路网
graph = ox.graph_from_bbox(north, south, east, west, network_type=mode)

# 验证路网加载状态
print(f"节点数: {len(graph.nodes)}, 边数: {len(graph.edges)}")

# 获取起点终点对应的最近路网节点（注意参数顺序：经度, 纬度）
orig_node = ox.distance.nearest_nodes(graph, start_latlng[1], start_latlng[0])
dest_node = ox.distance.nearest_nodes(graph, end_latlng[1], end_latlng[0])

# 查找时间最优的最短路径
shortest_route = nx.shortest_path(graph, orig_node, dest_node, weight=optimizer)

# 生成交互式路径地图
shortest_route_map = ox.plot_route_folium(graph, shortest_route)
shortest_route_map

内容的提问来源于stack exchange，提问作者RandoM123