DATA.md

Data

Source GTFS Data

• Bengaluru: Vonter/bmtc-gtfs
• Chennai: ungalsoththu/ChennaiGTFS
• Delhi: OTD Delhi
• Goa: KTCL Goa
• Kochi: Jungle Bus
• Pune: croyla/pmpml-gtfs
• Mumbai: croyla/mumbai-gtfs
• Ahmedabad: croyla/amd-gtfs
• Rajkot: croyla/rrl-gtfs
• Hubli-Dharwad: croyla/hdbrts-gtfs
• Indore: Neo2308/aictsl-gtfs
• Telangana: Open Data Telangana
• Andhra Pradesh: Neo2308/apsrtc-gtfs
• Indian Railways: Neo2308/indianrailways-gtfs
• Greyhound: Greyhound, Flixbus
• NYC: MTA

Processing GTFS Data

To process the GTFS data, run the following command:

cd data
./process.py

This will process all the GTFS data and generate the required files for the web app. The following Python scripts are run as part of the process.py script to generate optimized JSON files:

routes.py - Generate routes, services, and stops data

cd data
./routes.py --gtfs-path gtfs.zip --city blr --min-trips 2

This generates:

• stops.min.json - All stops with coordinates and names
• routes.min.json - Route shapes/polylines for map visualization
• services.min.json - Service patterns (stops sequence per route)

schedule.py - Generate per-stop schedule data

cd data
./schedule.py --gtfs-path gtfs.zip --city blr --min-trips 2

This generates data/$city/schedule/$stop_id.json files containing scheduled times for all routes passing through each stop. These files serve as fallback data when live arrival information is unavailable.

firstlast.py - Generate first/last arrival times

cd data
./firstlast.py --city blr

This generates data/$city/firstlast.min.json containing the earliest and latest arrival times for each route at each stop. The format follows the route_no earliest_weekday latest_weekday earliest_saturday latest_saturday earliest_sunday latest_sunday convention where times are in HHMM format.

ranking.py - Generate stop importance rankings

cd data
./ranking.py --gtfs-path gtfs.zip --city blr

This generates data/$city/ranking.min.json containing the importance rankings for each stop.

visualization/build-routes.mjs - Build routes for 3D visualization

cd visualization
node build-routes.mjs --city blr

visualization/build-stops.mjs - Build stops for 3D visualization

cd visualization
node build-stops.mjs --city blr

Processing Rail Data

To process the rail data, run the following command:

cd data
./rail.py --city blr --bbox 15.5,77.0,20.5,82.0

This will fetch the rail network from OpenStreetMap and generate the rail.json used to render the rail network on the map.