The primary objective of this project is to leverage data engineering techniques to enhance location-based services. By harnessing the Google Location API, we extract precise coordinates from address data. These coordinates are pivotal for powering our Streamlit application, enabling users to interact seamlessly with location-based data. The Docker containerization ensures easy deployment and scalability of our application, allowing for efficient management of resources. Through the application's frontend, users can input their address, triggering a request to the Google Location API. Subsequently, the application retrieves and displays nearby gas station locations on a map, providing users with valuable insights into gasoline prices in their vicinity.
- Data Engineering: Process address data to extract coordinates using the Google Location API.
- Streamlit Application: Utilize Streamlit for building an interactive frontend to facilitate user input.
- Docker Containerization: Containerize both the backend and frontend components for easy deployment and scalability.
- Location-based Services: Retrieve and display nearby gas station locations on a map, ranked based on gasoline prices.
- User Interaction: Enable users to input their address via the frontend, triggering requests to the Google Location API.