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Attendance-Monitor

(★ 11)

Developed an automated attendance monitoring system to track employee login and logout times using fingerprint authentication. The system securely records attendance, calculates working hours, and generates daily and monthly reports, reducing manual effort and improving accuracy for organizations managing large teams.

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- settings.json
- - .env
  - alembic.ini
  - Dockerfile
  - requirements.txt
  - verify_hr.py
- - schema.sql
- - pubspec.yaml
- docker-compose.yml
- README.md
.dockerignore
.gitattributes
.gitignore
alembic.ini
api.py
api_service.dart
attendance-system-v2.zip
attendance.dart
attendance.py
base.py
config.py
database_service.dart
docker-compose.yml
Dockerfile
env.py
fake_api.py
index.html
main.py
main.yml
pubspec.yaml
README.md
requirements.txt
schema.sql
security.py
session.py
user.dart
user.py

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This project aims to re-architect and re-implement the attendance system for improved flexibility, reliability, and maintainability. The new architecture adopts a **Clean Architecture** approach for the backend, utilizes **FastAPI** for robust API development, and integrates **Flutter** for a cross-platform mobile application.

## Project Structure

```
attendance-system-v2/
│
├── mobile_app/           # Flutter mobile application
│   ├── lib/
│   │   ├── screens/      # UI screens/pages
│   │   ├── models/       # Data models (e.g., DTOs, entities)
│   │   ├── services/     # Business logic, API calls, local storage
│   │   ├── widgets/      # Reusable UI components
│   │   └── main.dart     # Application entry point
│
├── backend/              # FastAPI backend with Clean Architecture
│   ├── src/
│   │   ├── app/
│   │   │   ├── api/
│   │   │   │   └── v1/   # API versioning
│   │   │   ├── core/     # Core configurations, security, and utilities
│   │   │   │   ├── config/    # Application settings
│   │   │   │   └── security/  # Authentication (JWT) and authorization
│   │   │   ├── db/       # Database interactions
│   │   │   │   ├── migrations/ # Alembic migration scripts
│   │   │   │   └── repositories/ # Data access layer (CRUD operations)
│   │   │   ├── services/ # Business logic and use cases
│   │   │   ├── schemas/  # Pydantic models for request/response validation
│   │   │   └── main.py   # FastAPI application entry point
│   │   ├── tests/        # Unit and integration tests
│   │   └── scripts/      # Utility scripts (e.g., initial data seeding)
│   ├── Dockerfile        # Dockerfile for backend service
│   └── requirements.txt  # Python dependencies
│
├── database/             # Database schema and initial setup
│   └── schema.sql        # SQL schema definition
│
├── .github/              # GitHub Actions CI/CD workflows
│   └── workflows/
│       └── main.yml
│
├── docker-compose.yml    # Docker Compose configuration
│
└── README.md             # Project overview and documentation
```

## Technologies Used

### Backend
- **FastAPI**: Modern, fast (high-performance) web framework for building APIs with Python 3.7+ based on standard Python type hints.
- **SQLAlchemy**: Python SQL toolkit and Object Relational Mapper (ORM) that gives application developers the full power and flexibility of SQL.
- **Alembic**: Lightweight database migration tool for usage with SQLAlchemy.
- **Pydantic**: Data validation and settings management using Python type hints.
- **JWT (JSON Web Tokens)**: For secure authentication and authorization.
- **Docker**: For containerization, ensuring consistent environments across development, testing, and production.

### Mobile App
- **Flutter**: Google's UI toolkit for building natively compiled applications for mobile, web, and desktop from a single codebase.
- **Provider/Riverpod**: State management solutions for Flutter.
- **Dio**: A powerful HTTP client for Dart, which supports Interceptors, FormData, Request Cancellation, File Downloading, Timeout, etc.
- **SQFlite**: SQLite plugin for Flutter, providing local database capabilities for offline support.

## Architectural Principles

### Clean Architecture (Backend)
- **Separation of Concerns**: Clear boundaries between layers (Presentation, Application Business Rules, Enterprise Business Rules, Infrastructure).
- **Independent of Frameworks**: The architecture does not depend on the existence of some library of feature-laden software.
- **Independent of Database**: The business rules are not bound to the database.
- **Independent of UI**: The UI can change easily, without changing the rest of the system.
- **Testability**: Business rules can be tested without the UI, Database, Web Server, or any other external element.

### Mobile App
- **Offline First**: The application is designed to work effectively without a constant internet connection, leveraging local storage.
- **Modular Design**: Breaking down the application into smaller, manageable modules for better organization and scalability.
- **State Management**: Efficient handling of application state to ensure a responsive and predictable user experience.

## Setup and Installation

This section provides instructions to set up and run the Attendance System locally.

### Prerequisites
- Docker and Docker Compose
- Python 3.11+
- Flutter SDK

### 1. Clone the Repository

```bash
git clone <repository_url>
cd attendance-system-v2
```

### 2. Database Setup (using Docker Compose)

Navigate to the root of the project and start the database service using Docker Compose:

```bash
docker-compose up -d db
```

This will start a PostgreSQL container and initialize the database with the schema defined in `database/schema.sql`.

### 3. Backend Setup

1.  **Navigate to the backend directory:**
    ```bash
    cd backend
    ```

2.  **Create a Python virtual environment and activate it:**
    ```bash
    python3 -m venv venv
    source venv/bin/activate
    ```

3.  **Install Python dependencies:**
    ```bash
    pip install -r requirements.txt
    ```

4.  **Configure Environment Variables:**
    Create a `.env` file in the `backend/` directory with the following content. Ensure `SECRET_KEY` is a strong, randomly generated string.
    ```env
    POSTGRES_SERVER=db
    POSTGRES_USER=postgres
    POSTGRES_PASSWORD=postgres
    POSTGRES_DB=attendance_db
    SECRET_KEY=YOUR_SUPER_SECRET_KEY_CHANGE_ME
    ACCESS_TOKEN_EXPIRE_MINUTES=10080 # 7 days
    ```
    *Note: When running the backend directly (not via docker-compose), `POSTGRES_SERVER` should be `localhost` if PostgreSQL is running directly on your machine, or the IP address of your PostgreSQL server.*

5.  **Run Alembic Migrations:**
    Initialize Alembic (if not already done):
    ```bash
    alembic init -t generic src/app/db/migrations
    ```
    *Note: The `env.py` and `alembic.ini` files are already configured for this project.*

Generate a new migration (if you make changes to models):
    ```bash
    alembic revision --autogenerate -m "Initial migration"
    ```

Apply migrations to the database:
    ```bash
    alembic upgrade head
    ```

6.  **Run the FastAPI application:**
    ```bash
    uvicorn src.app.main:app --host 0.0.0.0 --port 8000 --reload
    ```
    The backend API will be available at `http://localhost:8000`.

### 4. Mobile App Setup

1.  **Navigate to the mobile app directory:**
    ```bash
    cd mobile_app
    ```

2.  **Get Flutter dependencies:**
    ```bash
    flutter pub get
    ```

3.  **Run the Flutter application:**
    ```bash
    flutter run
    ```
    Ensure you have a device or emulator connected and configured for Flutter development.

### 5. Running with Docker Compose (Full Stack)

To run both the database and the backend service using Docker Compose:

1.  **Navigate to the root of the project:**
    ```bash
    cd attendance-system-v2
    ```

2.  **Build and start the services:**
    ```bash
    docker-compose up --build -d
    ```
    This will build the backend Docker image, start the PostgreSQL database, and then start the FastAPI backend. The backend will be accessible at `http://localhost:8000`.

3.  **Stop the services:**
    ```bash
    docker-compose down
    ```

## CI/CD with GitHub Actions

The project includes a basic GitHub Actions workflow (`.github/workflows/main.yml`) that performs the following:
-   **Test Backend**: Runs tests for the FastAPI backend on push and pull requests to the `main` branch.
-   **Build Docker Image**: Builds the Docker image for the backend on push to the `main` branch.

Further steps for deployment (e.g., pushing to a container registry, deploying to a cloud provider) can be added to this workflow.

## Future Enhancements
-   User management and roles.
-   More sophisticated attendance rules (e.g., geofencing).
-   Reporting and analytics features.
-   Push notifications for attendance reminders.
-   Comprehensive unit and integration tests for both backend and mobile app.

---
*Generated by Manus AI*