🌦️ Weather API with Caching (Flask)

A backend-focused Flask project that fetches weather data from a 3rd‑party API, caches responses using a Redis‑like in‑memory cache, and serves results via a clean server‑rendered UI.

This project is intentionally designed to emphasize API integration, caching logic, environment variables, and clean architecture — not frontend complexity.

📷 Screenshots

Home Screen

Backend Output

🚀 Features

• 🔌 Fetches weather data from a 3rd‑party provider (Visual Crossing)
• 🧠 Caching layer with TTL (Redis‑like behavior, pure Python)
• ⏱️ Automatic cache expiry (12 hours)
• 🔐 Environment variable–based configuration
• 🧩 Clean separation of concerns (Flask / service / cache)
• 🖥️ Simple server‑rendered UI (no JavaScript required)

🏗️ Project Structure

project/
│
├── app.py                # Flask app (routes & orchestration)
├── weather_service.py    # 3rd‑party weather API logic
├── cache.py              # In‑memory Redis‑like cache with TTL
│
├── templates/
│   └── index.html        # UI template
│
├── static/
│   └── styles.css        # Basic styling
│
├── .env                  # Environment variables (not committed)
├── .env.example          # Env template
├── requirements.txt
└── README.md

⚙️ How It Works (High‑Level Flow)

User submits form
      ↓
Flask route (/weather)
      ↓
Check cache (key = city + date range)
      ↓
Cache hit? → return cached data
Cache miss? → call 3rd‑party API
                     ↓
                store in cache (with TTL)
                     ↓
                return result

🧠 Caching Strategy

• Implemented a Redis‑like in‑memory cache using Python dictionaries

• Each cache entry stores:

  • the response data
  • an expiration timestamp (TTL)

• Expired entries are automatically removed on access

Why fake Redis?

Redis does not officially support Windows. To avoid unnecessary setup complexity, this project uses an in‑memory cache that mimics Redis behavior.

The cache layer is abstracted, so swapping to real Redis later requires minimal changes.

🔁 Swapping to Real Redis (Future‑Ready)

When deploying to Linux / Docker / Cloud:

• Replace cache internals with redis-py
• Keep the same get_cache() and set_cache() interface

No changes required in app.py.

🔐 Environment Variables

Create a .env file based on .env.example:

BASE_URL=https://weather.visualcrossing.com/VisualCrossingWebServices/rest/services/timeline/
API_KEY=your_api_key_here

⚠️ Never commit .env to version control.

▶️ Running the Project

1️⃣ Install dependencies

pip install -r requirements.txt

2️⃣ Run Flask app

python app.py

3️⃣ Open in browser

http://127.0.0.1:5000

📦 Example Output

The application currently displays the raw JSON response from the weather provider for transparency and debugging purposes.

This is intentional and aligns with API‑first design principles.

🧪 Error Handling

• Missing form fields → user‑friendly error
• API failure → graceful message
• Cache handles expiration automatically

📌 Notes

• This project focuses on backend engineering, not frontend design
• No JavaScript is used (by choice)
• Ideal for demonstrating API usage, caching, and clean architecture

📈 Possible Enhancements

• Normalize weather response (temperature, humidity, condition)
• Add rate limiting
• Add logging
• Replace fake cache with real Redis
• Expose a pure JSON API endpoint

🧠 Key Takeaway

Redis is not magic — it’s a fast key‑value store with expiration. This project demonstrates that concept clearly and cleanly.

👤 Author

Built with focus on backend fundamentals and practical system design.

⭐ If you found this useful, consider starring the repo!

Project: https://roadmap.sh/projects/weather-api-wrapper-service