Weather API Testing & Analysis Project

Overview

The goal of this task is to extend the existing project by designing and implementing a module that tests and analyzes temperature data. This module should compare real-time readings from a public website and a weather API, store and process the data, and generate a discrepancy report.

⚠️ Important: This work must be use fork from this existing project.

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Test Case: City Temperature Discrepancy Analysis

1. City Selection

• Select 20 random cities for the analysis. (Cities names could be hardcoded)

2. Data Sources

• Website
  Scrape current temperature and feels like values from timeanddate.com.

• API
  Use the OpenWeatherMap API to fetch current weather data: https://api.openweathermap.org/data/2.5/weather?q={city name}&appid={API key}

3. Data Extraction

• Web Scraping
  Use Selenium or Playwright to extract:

• temperature_web

• feels_like_web

• API Call
  Extract the following fields from the JSON response:

• temperature_api

• feels_like_api

4. Database Integration

• You are free to define your own database but use this schema.
• For each city, store:
• temperature_web
• feels_like_web
• temperature_api
• feels_like_api
• Add a computed column:
• avg_temperature — the average of the web and API temperature values.

5. Reporting

After data collection, generate a report. You may choose between:

• A single combined report, or
• Two separate reports (e.g., one for discrepancies and one for statistics)

Format:

• Free choice (CSV, HTML, JSON, Markdown, etc.)

Contents:

• Cities where the difference between website and API temperatures exceeds a configurable threshold
• Summary statistics:
• Mean discrepancy
• Maximum discrepancy
• Minimum discrepancy

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Test Automation Framework

Your solution must include an automated test framework that covers:

• End-to-end tests for the full pipeline (data collection → DB → report)

Use a standard Python testing framework. Ensure tests can be easily executed with clear instructions.

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Submission Guidelines

1. Push the following to the ** GitHub repository**:

• Source code
• Configuration files
• Test scripts
• Generated report(s)

2. Include a README that provides:

• Setup instructions
• How to run the project and the tests
• How to view and interpret the report(s)

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Good luck, and make sure your code is clean, well-documented, and testable!