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Overview

Expose the Roataway MQTT data stream in a GTFS realtime feed format

Principle of operation

This program subscribes to the route-specific MQTT topic, consumes all incoming payloads and maintains an internal data structure with the latest known info about each vehicle.

The following table illustrates how attributes of the MQTT payloads are mapped to entries in the GTFS FeedMessage:

Source attribute Target attribute Notes
timestamp VehiclePosition.timestamp
latitude VehiclePosition.Position.latitude
longitude VehiclePosition.Position.longitude
speed VehiclePosition.Position.speed
direction VehiclePosition.Position.bearing
board VehicleDescriptor.label Board number, e.g. "3890"
rtu_id VehicleDescriptor.id Tracker ID, e.g. "0000123"
route TripDescriptor.route_id Human-readable route name, e.g. "30"
route (in topic) not exposed route_id_upstream, e.g. 1

Prerequisites

  1. The static GTFS data must be available as a ZIP file.
  2. Ensure you can connect to opendata.dekart.com over MQTT.
  3. Create a virtualenv and install the dependencies from requirements.txt.

Producing the static GTFS feed

TODO

  • figure out where to store it and how to get it, maybe use a git subrepo?
  • document how it was modified to replace _ for - in the names of trips

Usage

Serving the GTFS stream

  1. Run python app.py to start the bridge
  2. Open http://localhost:5000 to view the current state of the worker in textual format

Other endpoints:

  • http://localhost:5000/rt - retrieve the live GTFS feed as ProtoBuf
  • http://localhost:5000/static- retrieve the complete static GTFS data set as an archive

Consuming a GTFS stream

For testing purposes, you might need to consume your own feed to see if it looks right. You can do so by running python consumer.py <GTFS RT feed URL>, e.g., python consumer.py http://localhost:5000/rt. The data will be dumped to stdout.

References