Requests and JSON APIs in Python

Table of Contents

1. Challenge

   Understand the project and starter structure

   In this lab, you will turn a small Python starter project into a working command-line utility that retrieves JSON data from the web and converts it into a readable trail conditions bulletin. The project is intentionally scoped to core Python skills: calling a third-party package, decoding JSON into native data structures, navigating lists and dictionaries, and composing small functions into a simple end-to-end workflow. info> This lab experience was developed by the Pluralsight team using an internally developed AI tool. All sections were verified by human experts for accuracy prior to publications. However, content may still contain errors or inaccuracies, and we recommend independent verification.
   
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2. Challenge

   Fetch and decode remote JSON data

   This step builds the application's data-ingestion pipeline. You will create the function that performs the HTTP request, the function that validates and decodes the response body, and the function that extracts the nested trail list from the decoded payload.

3. Challenge

   Normalize and filter the decoded trail data

   This step transforms raw API records into dependable internal data. Once external JSON has been decoded, the values may still be inconsistent: names can include extra spaces, status text might use mixed casing, numbers can arrive as strings, and optional lists can be missing entirely.

4. Challenge

   Format and assemble the bulletin output

   This step turns processed data into a user-facing report. The program already knows how to fetch JSON, decode it, normalize trail records, filter visible items, and count alert labels.

5. Challenge

   Add CLI options and graceful error handling

   The reporting engine is now functional, but a useful tool also needs a clean entry point. This final step adds the command-line layer that lets users customize input and receive helpful feedback when network requests fail. ## Run the Application

   You're ready to test the completed application!

   First, start the sample API server in first Terminal tab:

   python3 sample_server.py
   

   Leave the server running, then in the second Terminal tab and run the application against the local server:

   python3 -m trail_bulletin.cli --url http://localhost:8000/api/trails
   

   If everything is working correctly, the application downloads the trail data and displays a formatted bulletin that includes:

   • A heading with the region, update time, and number of displayed trails
   • One line for each visible trail
   • An alert summary at the end of the report

   To include both open and closed trails, run:

   python3 -m trail_bulletin.cli --all --url http://localhost:8000/api/trails
   

   If the server is unavailable or the request fails, the application should display a message beginning with Unable to download trail data: and exit with a status code of 1.