Network Analysis in Python

Importing OSM Data

To explore some of the network analysis options in Python, this tutorial will use the road network of Ottawa, Ontario. This can easily be acquired using the OSMnx package, which uses Overpass API. The graph_from_place() function geocodes the area of interest (AOI) query and filters the network to the City of Ottawa's boundaries, while graph_from_polygon works with a custom polygon.

For additional information, check out the OSMnx documentation:

https://osmnx.readthedocs.io/en/stable/user-reference.html

and the example gallery:

https://github.com/gboeing/osmnx-examples/blob/main/notebooks/00-osmnx-features-demo.ipynb

# create query for Smiths Falls
AOI = "Ottawa, Ontario, Canada"

# retrieve road network -> this may take some time
graph = osmnx.graph_from_place(
    AOI,
    network_type="drive" # this selects roads only. Other network options include "bike" and "walk".
)

# visualise the road network
figure, ax = osmnx.plot_graph(graph)

Simple Routing: Shortest Path
1. Distance-Based

2. Time-Based

3. Route Comparison

Generating Simple Directions for a Route
Multiple Shortest Routes
Exporting Routes
Complex Routing: Travelling Salesman Problem