City, Prague Open Data Getting Started: Accessing Data (2026)

Getting started overview

To begin using City, Prague Open Data, users typically do not need to create an account or obtain API keys, as all data is freely available for public access. The portal offers various methods for data retrieval, including direct file downloads and programmatic access via APIs. Datasets are provided in common formats such as CSV, JSON, and GeoJSON, catering to diverse application needs. For geospatial data, the APIs frequently adhere to Open Geospatial Consortium (OGC) standards, such as Web Map Service (WMS) and Web Feature Service (WFS), which are widely adopted for handling geographic information Prague Open Data API documentation.

The initial setup process focuses on identifying the desired dataset and understanding its specific access method. Some datasets are best accessed via direct download, while others are better suited for API calls, especially when real-time or filtered data is required. The official documentation provides specific instructions and examples for interacting with each dataset and its corresponding API endpoint Prague Open Data official documentation.

This guide outlines the steps to quickly make your first data request, focusing on a common API endpoint to demonstrate programmatic access. It covers identifying data, constructing a request, and interpreting the response, along with common troubleshooting tips.

Quick reference table

Create an account and get keys

For most datasets provided by City, Prague Open Data, creating an account and obtaining API keys is not necessary. The platform is designed to offer public access to its data without authentication requirements Prague Open Data access information. This approach simplifies the getting started process for developers, researchers, and the public, allowing immediate access to information like transportation schedules, environmental readings, and demographic statistics.

Unlike many commercial APIs that require API keys for rate limiting, authentication, or billing purposes (e.g., Stripe API keys overview or Google Maps API key setup), City, Prague Open Data operates on an open-access model. Users can directly query endpoints or download files without prior registration.

If a specific advanced service or a future premium dataset were to require authentication, details would be provided within the relevant dataset's documentation on the official portal. However, as of the current offerings, the emphasis remains on open and unrestricted access.

Your first request

This section demonstrates how to make a basic API request to City, Prague Open Data using a common tool like curl. We will target a publicly available dataset, such as public transport stops, which is typically offered through a WFS (Web Feature Service) endpoint for geospatial data.

Example Dataset: Public Transport Stops

One accessible dataset is often related to public transport infrastructure. Let's assume there's a WFS endpoint for public transport stops. The general structure for a WFS GetFeature request involves specifying the service (WFS), version, request type (GetFeature), and the type name (the specific dataset layer).

Step 1: Identify the WFS Endpoint and Layer

Navigate to the Prague Open Data API documentation or browse the datasets on the Prague Open Data portal. Look for a dataset categorized under "Transportation" or "Public Transport" that offers WFS access. For this example, let's assume a hypothetical WFS endpoint and layer name:

• WFS Base URL: https://geoportal.prague.eu/wfs (hypothetical, replace with actual)
• Layer Name: praha:public_transport_stops (hypothetical, replace with actual)

You would find these specifics on the individual dataset's page or within the API documentation.

Step 2: Construct the GetFeature Request

A basic WFS GetFeature request to retrieve data for a specific layer typically looks like this:

GET /wfs?service=WFS&version=2.0.0&request=GetFeature&typeName=praha:public_transport_stops&outputFormat=application%2Fjson HTTP/1.1
Host: geoportal.prague.eu

Let's break down the parameters:

• service=WFS: Specifies that we are using the Web Feature Service.
• version=2.0.0: Indicates the WFS version. Check documentation for the exact version supported.
• request=GetFeature: The operation to retrieve features (data records).
• typeName=praha:public_transport_stops: The specific layer or dataset to query.
• outputFormat=application%2Fjson: Requests the response in GeoJSON format, which is common for geospatial data and easily parsed. Other formats like text/xml; subtype=gml/3.2 might also be available.

Step 3: Execute the Request with curl

Open your terminal or command prompt and execute the following curl command. Remember to replace the hypothetical URL and layer name with the actual ones from the Prague Open Data portal.

curl "https://geoportal.prague.eu/wfs?service=WFS&version=2.0.0&request=GetFeature&typeName=praha:public_transport_stops&outputFormat=application%2Fjson"

Expected Response

A successful request will return a GeoJSON object containing a FeatureCollection. Each Feature within the collection represents a public transport stop, with its geometry (e.g., point coordinates) and properties (e.g., stop name, ID). The structure will resemble standard GeoJSON, as defined by the IETF RFC 7946 for GeoJSON.

{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "geometry": {
        "type": "Point",
        "coordinates": [14.4212, 50.0878]
      },
      "properties": {
        "id": "12345",
        "name": "Staroměstská",
        "type": "tram_bus"
      }
    },
    // ... more features
  ]
}

Step 4: Parse and Use the Data

Once you receive the JSON response, you can parse it using a JSON parser in your preferred programming language. For example, in Python:

import requests
import json

url = "https://geoportal.prague.eu/wfs?service=WFS&version=2.0.0&request=GetFeature&typeName=praha:public_transport_stops&outputFormat=application%2Fjson"
response = requests.get(url)

if response.status_code == 200:
    data = response.json()
    print(f"Retrieved {len(data['features'])} public transport stops.")
    for feature in data['features']:
        print(f"Stop Name: {feature['properties']['name']}, Coordinates: {feature['geometry']['coordinates']}")
else:
    print(f"Error: {response.status_code} - {response.text}")

Common next steps

After successfully making your first request to City, Prague Open Data, consider these common next steps to further integrate and utilize the data:

1. Explore More Datasets: The Prague Open Data portal hosts a wide array of datasets beyond public transport. Investigate other categories like environmental data, demographic information, or public services to find data relevant to your project. Each dataset page will provide specific access details and documentation.
2. Refine API Queries: Learn to use advanced parameters for filtering, spatial queries, and pagination. WFS, for instance, supports CQL (Common Query Language) filters to retrieve only specific features based on attributes or spatial relationships. This can significantly reduce the amount of data transferred and processed.
3. Integrate into Applications: Incorporate the data into web maps using libraries like Leaflet or OpenLayers, or build civic applications that leverage the data for public information, urban planning tools, or academic research.
4. Data Visualization: Utilize tools and libraries such as D3.js, Tableau, or Power BI to create interactive visualizations and dashboards from the retrieved data. This can help in identifying patterns, trends, and insights from the urban environment.
5. Automate Data Retrieval: For ongoing projects that require updated data, set up automated scripts using cron jobs or cloud functions to periodically fetch and process new information from the APIs.
6. Understand Data Licensing: Although the data is open, it's good practice to review the specific licenses associated with each dataset on the portal to ensure compliance with usage terms.
7. Engage with the Community: If available, participate in forums or communities related to Prague's open data initiatives. This can provide opportunities to share insights, ask questions, and collaborate on projects.

Troubleshooting the first call

Encountering issues during your first API call is common. Here's a guide to troubleshoot typical problems when accessing City, Prague Open Data:

• Incorrect Endpoint or Layer Name:
• Symptom: HTTP 404 Not Found or an empty response with no data.
• Solution: Double-check the exact WFS base URL and the typeName parameter against the Prague Open Data API documentation. Layer names are case-sensitive.
• Invalid Parameters:
• Symptom: HTTP 400 Bad Request or an XML error message from the WFS server.
• Solution: Verify all query parameters (service, version, request, outputFormat) match the documented specifications. Ensure there are no typos, extra spaces, or incorrect values. For example, WFS versions might be 1.0.0, 1.1.0, or 2.0.0.
• Output Format Issues:
• Symptom: Response is not in the expected format (e.g., XML instead of JSON) or parsing errors occur.
• Solution: Confirm the outputFormat parameter is correctly specified (e.g., application%2Fjson for GeoJSON). Some WFS services might require specific MIME types or offer different JSON variants.
• Network Connectivity:
• Symptom: Connection timed out or DNS resolution errors.
• Solution: Check your internet connection. Ensure there are no firewalls or proxies blocking access to the geoportal.prague.eu domain. Try pinging the domain to confirm reachability.
• Server-Side Errors:
• Symptom: HTTP 5xx errors (e.g., 500 Internal Server Error, 503 Service Unavailable).
• Solution: These indicate a problem on the server side. Wait a few minutes and retry the request. If the issue persists, check the official Prague Open Data portal for announcements regarding service interruptions or maintenance.
• Data Volume/Pagination:
• Symptom: The response contains fewer features than expected, or the request takes a very long time.
• Solution: WFS requests often have default limits on the number of features returned. You may need to use parameters like count (for WFS 2.0.0) or maxFeatures (for WFS 1.x.x) to specify the desired number of features, or implement pagination to retrieve data in chunks. Refer to the specific WFS documentation for pagination methods.
• URL Encoding:
• Symptom: Request fails or returns unexpected data when parameters contain special characters.
• Solution: Ensure all URL parameters, especially complex filter expressions, are properly URL-encoded. Tools like curl typically handle basic encoding, but complex strings might require explicit encoding in your programming language.

Always consult the specific Prague Open Data API documentation for the dataset you are working with, as endpoint structures and supported parameters can vary.