Community Transit API

Overview

Community Transit, established in 1976, serves as the public transportation provider for Snohomish County, Washington. Its developer portal offers direct access to its General Transit Feed Specification (GTFS) data. This standardized format, widely adopted across the public transit industry, provides a common structure for transit schedule and real-time information, facilitating interoperability among various transit applications and services. Developers can utilize this data to create mobile applications that help riders plan journeys, track bus locations, and receive service alerts specific to Snohomish County routes. The GTFS standard itself is maintained by Google and used by transit agencies worldwide, as detailed in the Google GTFS reference documentation.

The Community Transit GTFS data is particularly valuable for academic researchers studying public transit usage patterns, urban planning, and transportation efficiency within the region. By analyzing historical and real-time data, researchers can gain insights into ridership trends, route performance, and the impact of service changes. Furthermore, businesses or service providers operating within Snohomish County can integrate this transit data into their own platforms, offering enhanced functionality to their users, such as displaying nearby bus stops and arrival times directly within a local business directory or event planning application.

Community Transit's approach to data sharing aligns with the broader movement toward open data in public services, promoting transparency and fostering innovation within the developer community. The availability of both static schedule data and real-time vehicle position data allows for the development of dynamic applications that reflect current transit conditions. This includes real-time bus tracking, delay notifications, and predictive arrival estimates. The straightforward access to these data files via direct links on their developer page simplifies the initial setup for new projects, making it a practical resource for anyone looking to build transit-focused solutions for Snohomish County.

While the primary focus is on GTFS data, the implications extend to various sectors. For instance, smart city initiatives can incorporate this data to inform traffic management systems or public information displays. Educational institutions can use it as a practical dataset for data science courses. The consistent updates to the GTFS feeds ensure that applications built on this data remain accurate and relevant, reflecting any changes in routes, schedules, or service disruptions. This commitment to maintaining up-to-date data is crucial for the reliability of any transit-dependent application.

Key features

• GTFS Static Data Access: Provides access to General Transit Feed Specification (GTFS) files for scheduled routes, stops, and timetables for Snohomish County transit services.
• GTFS Real-time Data Access: Offers real-time GTFS feeds for vehicle positions, service alerts, and trip updates, enabling dynamic application development.
• Direct Download Links: Developer portal provides direct links to current GTFS static and real-time data files, simplifying data acquisition.
• Standardized Data Format: Utilizes the industry-standard GTFS format, ensuring compatibility with a wide range of existing transit tools and libraries.
• Publicly Available: All GTFS data is freely available for public use without requiring API keys or registration, fostering open development.

Pricing

Community Transit provides its GTFS data free of charge for public use. There are no subscription fees, API call limits, or commercial licensing requirements for accessing the standard GTFS feeds. This policy supports open data initiatives and encourages widespread use of transit information for application development and research.

Pricing as of 2026-05-28. For the most current information, refer to the Community Transit developer page.

Common integrations

• Transit Planning Applications: Integrate GTFS data into mobile or web applications for route planning, schedule lookup, and real-time bus tracking.
• Mapping Services: Overlay transit routes and stop locations onto mapping platforms like Google Maps or OpenStreetMap using the provided GTFS data.
• Data Analytics Platforms: Import GTFS data into analytics tools for transportation research, urban planning, and service optimization studies.
• Smart City Dashboards: Incorporate real-time transit information into public information displays or smart city management systems.
• Local Information Portals: Embed transit schedules and real-time arrivals into community websites or local business directories.

Alternatives

• King County Metro: Provides public transit services and GTFS data for King County, Washington, including Seattle.
• Sound Transit: Offers regional express bus, light rail, and commuter rail services across the Puget Sound region, with GTFS data available.
• TriMet: The public transit agency for the Portland metropolitan area in Oregon, offering GTFS data for its services.

Getting started

To begin working with Community Transit's GTFS data, you typically download the static and real-time feeds and then parse them using a GTFS library in your preferred programming language. The following Python example demonstrates how to download and read a GTFS static feed, then print details about a few routes.

First, ensure you have the gtfs-feed library installed:

pip install gtfs-feed

Then, use the following Python code to access and explore the data:

import requests
from gtfs_feed.gtfs import GTFS
import zipfile
import io

def get_community_transit_gtfs_data():
    # URL for the static GTFS feed from Community Transit's developer page
    gtfs_url = "https://www.communitytransit.org/docs/default-source/gtfs/gtfs.zip?sfvrsn=a99d0e2e_12"
    
    print(f"Downloading GTFS data from: {gtfs_url}")
    response = requests.get(gtfs_url)
    response.raise_for_status() # Raise an exception for HTTP errors
    
    # GTFS data is typically a zip file
    with zipfile.ZipFile(io.BytesIO(response.content)) as zf:
        # The GTFS library can read directly from a zip file object
        feed = GTFS(zf)
        
        print("\nSuccessfully loaded GTFS feed. Here are some routes:")
        for i, route in enumerate(feed.routes):
            if i >= 5: # Print details for the first 5 routes as an example
                break
            print(f"  Route ID: {route.route_id}")
            print(f"  Route Short Name: {route.route_short_name}")
            print(f"  Route Long Name: {route.route_long_name}")
            print(f"  Route Type: {route.route_type} (0=Tram, 1=Subway, 2=Rail, 3=Bus, 4=Ferry, 5=Cable car, 6=Gondola, 7=Funicular)")
            print("  ---")

        print("\nExample: Finding stops for a specific route (e.g., '101'):")
        route_101_stops = set()
        for trip in feed.trips:
            if trip.route_id == '101':
                for stop_time in trip.stop_times:
                    route_101_stops.add(stop_time.stop_id)
        
        print(f"  Number of stops on Route 101: {len(route_101_stops)}")
        # To get stop names, you'd iterate through feed.stops and match stop_id

        print("\nExample: Accessing agency information:")
        for agency in feed.agency:
            print(f"  Agency Name: {agency.agency_name}")
            print(f"  Agency URL: {agency.agency_url}")
            print(f"  Agency Timezone: {agency.agency_timezone}")
            print("  ---")

if __name__ == "__main__":
    get_community_transit_gtfs_data()

This script first downloads the zipped GTFS archive. It then uses the gtfs-feed library to parse the contents, allowing access to various entities like routes, trips, stops, and agencies. The example demonstrates how to list basic information for several routes and count stops for a specific route. For real-time data, you would follow a similar process, downloading the GTFS-RT feed (often in Protocol Buffer format) and using a suitable library to parse it. The Community Transit developer documentation provides the direct links to both static and real-time data feeds.