VPI_backend a FastAPI Based Data Backend for VPI Project

Project Purpose

This project is a FastAPI-based backend system designed to process, store, and serve visitor-related data for specified zones. It supports analyzing visitor behavior based on data such as:

• Visitor Types
• Age Groups
• Dwell Times

The application utilizes SQLite as its database and provides RESTful API endpoints for querying aggregated information.

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Project Structure

1. Database Layer

• database.py: Manages the database connection and session lifecycle using SQLAlchemy.
• models.py: Defines the database schema using SQLAlchemy ORM models.

2. Data Processing

• poc.py: Handles the creation of database tables and imports visitor data from CSV files.

3. Business Logic

• crud.py: Implements the database query logic for aggregating and filtering visitor data.

4. API Layer

• main.py: Exposes RESTful API endpoints for querying visitor data, including visitor types, age groups, and dwell times.

5. Configuration

• requirements.txt: Lists the Python dependencies required for the application.
• Dockerfile and docker-compose.yml: Define the containerized setup for running the application.

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Getting Started with Docker

Prerequisites

• Docker installed on your system.
• A terminal or command-line interface.

Steps to Set Up

1. Clone the Repository Clone the project repository to your local machine:

   git clone <repository-url>
   cd <repository-directory>

2. Build and Run the Application Navigate to the project directory containing the Dockerfile and docker-compose.yml. Then, run the following command:

   docker-compose up --build

3. Access the API Once the application starts, the API will be accessible at:

   http://127.0.0.1:8000
   

4. Test the Endpoints Use a tool like Postman, cURL, or a browser to test the available API endpoints:

   • GET /visitor-types/
   • GET /ages/
   • GET /dwell-times/

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Features

• Import visitor data from CSV files into a structured SQLite database.
• Serve visitor analytics through intuitive RESTful endpoints.
• Filter results by date, zone, and specific attributes like age group or dwell time.
• Easy-to-setup Docker-based deployment.

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Enjoy using the project!