A modular Python project that fetches real‑time weather data, transforms it, stores it in SQLite, and runs SQL analytics — built with a data engineering mindset.

• ETL Pipeline (Extract → Transform → Load)
• Closest‑timestamp matching for humidity & pressure
• SQLite storage with idempotent inserts (UNIQUE(city, timestamp) + INSERT OR IGNORE)
• SQL analytics:
  • Latest weather per city
  • Temperature ranking (window function)
  • Duplicate detection
• CLI menu for easy interaction
• Fully modular architecture

weather/ ├── api.py # API calls (geocoding + weather) ├── transform.py # Data cleaning + timestamp matching ├── db.py # SQLite operations ├── analytics.py # SQL analytics queries ├── pipeline.py # ETL orchestration └── main.py # CLI entry point

Install dependencies:

pip install requests

Start the CLI:

python main.py

Menu options:

• Run ETL (fetch & save weather)
• Show latest weather
• Show ranked temperatures
• Show duplicates
• Exit

• Idempotent ETL (safe to rerun)
• UNIQUE constraints for data integrity
• INSERT OR IGNORE to prevent duplicates
• Window functions for ranking
• Subqueries for latest‑record selection
• Modular pipeline design

requests

MIT License.