Transport for Czech Republic SDKs & Libraries: Official & Community (2026)

SDKs overview

Transport for Czech Republic (PID) provides developers with access to public transport data primarily through General Transit Feed Specification (GTFS) static and real-time (GTFS-RT) feeds, as well as a dedicated HTTP API. These resources enable the creation of applications that display real-time departure information, plan journeys, and analyze transport patterns. While PID does not offer a large suite of official, language-specific SDKs, its data formats are widely supported by existing open-source libraries designed for GTFS and GTFS-RT data processing. Access to these data feeds and the API generally requires an API key, which can be requested through the official PID integration and digitalization page. The primary method for consuming PID data involves direct HTTP requests to the API endpoints or parsing the GTFS/GTFS-RT feeds.

The GTFS format, a standard for public transport schedules and associated geographic information, allows for interoperability across various tools and platforms. The GTFS-RT format extends this by providing real-time updates on vehicle positions, service alerts, and trip updates, crucial for dynamic passenger information systems. Developers building with PID's data can utilize a range of programming languages and frameworks that support HTTP requests and JSON/Protobuf parsing, the latter being common for GTFS-RT feeds. The Google Transit Feed Specification reference provides comprehensive details on the GTFS format structure, which is directly applicable to the static data provided by PID.

Official SDKs by language

As of 2026, Transport for Czech Republic does not provide a suite of officially maintained, language-specific SDKs in the traditional sense, such as those offered by cloud providers or payment gateways. Instead, developers interact directly with the API endpoints and data feeds. The data is available primarily through standard formats like GTFS and GTFS-RT, which are designed to be consumed by general-purpose libraries and parsers available in various programming languages. The official documentation outlines the API endpoints and data structures, allowing developers to construct their own client-side integrations.

The core interaction methods involve:

• HTTP requests: For the RESTful API endpoints that provide departures, stops, and connection information. These typically return JSON data.
• GTFS feed parsing: Downloading and parsing static GTFS files, which are a collection of CSV files detailing routes, stops, schedules, and other static transit data.
• GTFS-RT feed processing: Consuming real-time feeds, often provided in Protocol Buffers format, for dynamic updates on vehicle positions, trip delays, and service alerts. The GTFS Realtime reference details this format.

While there are no official SDKs, the following table illustrates the typical approach developers might take, using common libraries to interact with the data formats PID provides:

Installation

Installation for interacting with Transport for Czech Republic's data typically involves setting up a development environment for your chosen programming language and installing relevant HTTP client libraries and, for GTFS-RT feeds, Protocol Buffer parsing libraries. The following examples demonstrate common installation steps for Python and Node.js, two popular choices for API integration and data processing.

Python

To use Python for interacting with the PID API and GTFS-RT feeds, you generally need to install the requests library for HTTP calls and the gtfs-realtime-bindings library for parsing GTFS-RT Protocol Buffer messages. It is recommended to use a virtual environment to manage dependencies.

# Create a virtual environment
python3 -m venv pid_env
source pid_env/bin/activate

# Install required libraries
pip install requests
pip install gtfs-realtime-bindings

JavaScript (Node.js)

For Node.js applications, the axios library is a common choice for making HTTP requests, and gtfs-rt-bindings can be used for parsing GTFS-RT data. Initialize a new Node.js project and install the packages:

# Create a new project directory and initialize npm
mkdir pid-js-app
cd pid-js-app
npm init -y

# Install required libraries
npm install axios
npm install gtfs-rt-bindings

Quickstart example

This quickstart example demonstrates how to fetch data from a hypothetical PID API endpoint using Python to get real-time departure information for a specific stop and how to parse a GTFS-RT feed. Replace YOUR_API_KEY and actual API/GTFS-RT URLs with those obtained from the official PID documentation.

Python example: Fetching real-time departures

This script fetches real-time departure data from a hypothetical PID API endpoint for a given stop ID. The actual endpoint and parameters will be specified in the PID API documentation.

import requests
import os

# Replace with your actual API key and endpoint
API_KEY = os.getenv("PID_API_KEY", "YOUR_API_KEY")
API_BASE_URL = "https://api.pid.cz/v1/departures" # Hypothetical endpoint
STOP_ID = "U123Z101" # Example stop ID

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Accept": "application/json"
}

params = {
    "stopId": STOP_ID,
    "limit": 5 # Get next 5 departures
}

try:
    response = requests.get(API_BASE_URL, headers=headers, params=params)
    response.raise_for_status() # Raise an exception for HTTP errors (4xx or 5xx)
    departures_data = response.json()

    print(f"Upcoming departures for stop {STOP_ID}:")
    for departure in departures_data.get("departures", []):
        line = departure.get("lineName", "N/A")
        destination = departure.get("destination", "N/A")
        time_utc = departure.get("scheduledDeparture", "N/A")
        realtime_delay = departure.get("delaySeconds", 0)
        print(f"  Line: {line}, Destination: {destination}, Scheduled: {time_utc}, Delay: {realtime_delay}s")

except requests.exceptions.HTTPError as http_err:
    print(f"HTTP error occurred: {http_err}")
except requests.exceptions.ConnectionError as conn_err:
    print(f"Connection error occurred: {conn_err}")
except requests.exceptions.Timeout as timeout_err:
    print(f"Timeout error occurred: {timeout_err}")
except requests.exceptions.RequestException as req_err:
    print(f"An error occurred: {req_err}")
except Exception as e:
    print(f"An unexpected error occurred: {e}")

Python example: Parsing GTFS-RT feed

This example demonstrates how to fetch and parse a GTFS-RT feed to get real-time trip updates. GTFS-RT feeds typically use Protocol Buffers for efficiency.

import requests
from google.transit import gtfs_realtime_pb2
import os

# Replace with your actual GTFS-RT feed URL (often requires API key in URL or headers)
GTFS_RT_FEED_URL = os.getenv("PID_GTFS_RT_URL", "https://gtfsrt.pid.cz/tripupdates") # Hypothetical URL
API_KEY = os.getenv("PID_API_KEY", "YOUR_API_KEY")

headers = {
    "Authorization": f"Bearer {API_KEY}"
} # May not be needed if key is in URL

try:
    response = requests.get(GTFS_RT_FEED_URL, headers=headers)
    response.raise_for_status()

    feed = gtfs_realtime_pb2.FeedMessage()
    feed.ParseFromString(response.content)

    print("GTFS-RT Trip Updates:")
    for entity in feed.entity:
        if entity.HasField('trip_update'):
            trip_id = entity.trip_update.trip.trip_id
            route_id = entity.trip_update.trip.route_id
            start_time = entity.trip_update.trip.start_time
            print(f"  Trip ID: {trip_id}, Route ID: {route_id}, Start Time: {start_time}")
            for stop_time_update in entity.trip_update.stop_time_update:
                stop_sequence = stop_time_update.stop_sequence
                stop_id = stop_time_update.stop_id
                arrival_delay = stop_time_update.arrival.delay if stop_time_update.HasField('arrival') else 'N/A'
                departure_delay = stop_time_update.departure.delay if stop_time_update.HasField('departure') else 'N/A'
                print(f"    Stop Sequence: {stop_sequence}, Stop ID: {stop_id}, Arrival Delay: {arrival_delay}s, Departure Delay: {departure_delay}s")

except requests.exceptions.RequestException as e:
    print(f"Error fetching or parsing GTFS-RT feed: {e}")
except Exception as e:
    print(f"An unexpected error occurred: {e}")

Community libraries

Given that Transport for Czech Republic primarily exposes data through standard GTFS and GTFS-RT feeds, a significant ecosystem of community-developed libraries exists that can be adapted to consume PID's data. These libraries are not specific to PID but are designed to work with any GTFS-compliant data source. Developers often leverage these tools instead of building parsers from scratch.

Examples of common community approaches and libraries include:

• GTFS Parsers: Libraries in various languages (e.g., Python's gtfs-feed, JavaScript's gtfs-parser) that can read and process static GTFS CSV files. These tools often provide convenient data structures and query methods for routes, stops, and schedules.
• GTFS-RT Bindings: Protocol Buffer bindings for GTFS-RT are available for many languages (e.g., Python's gtfs-realtime-bindings, Java's gtfs-realtime-bindings). These libraries deserialize the binary GTFS-RT feed into language-specific objects, making it easier to access real-time information like vehicle positions, service alerts, and trip updates.
• Mapping Libraries: Integration with mapping libraries (e.g., Google Maps Platform, Leaflet, Mapbox) is common for visualizing transport data. Developers can overlay stop locations, route paths, and real-time vehicle positions on interactive maps using the geographic data provided by PID's GTFS feeds.
• Routing Engines: Open-source routing engines (e.g., OpenTripPlanner, R5) can consume GTFS data to calculate multi-modal journeys, which can be enhanced with real-time data from GTFS-RT feeds.
• API Clients: While PID does not provide official clients, community members may develop wrappers or client libraries for specific languages to simplify interaction with the HTTP API endpoints. These are typically found on platforms like GitHub and may vary in maintenance and stability.

When using community libraries, developers should review their documentation, community support, and licensing to ensure they meet project requirements. The flexibility of standard data formats allows for a broad range of tools to be applied to PID's public transport data.