Task Manager API

A modern task management application built with Flask, SQLAlchemy, and a clean web interface. This application allows users to create, read, update, and delete tasks through both a web interface and REST API endpoints.

Features

• Clean and responsive web interface
• RESTful API endpoints
• SQLite database for data persistence
• Task status tracking
• Real-time updates without page refresh

Prerequisites

Before you begin, ensure you have the following installed:

• Python 3.9 or higher
• pip (Python package installer)

Installation

1. Clone the repository:

git clone https://github.com/TennysonGeorge/task-manager-app.git
cd task-manager-app/task-manager-api

2. Create a virtual environment:

# For macOS/Linux
python3 -m venv task-manager
source task-manager/bin/activate

# For Windows
python -m venv task-manager
task-manager\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

Running the Application

1. Activate the virtual environment (if not already activated):

# For macOS/Linux
source task-manager/bin/activate

# For Windows
task-manager\Scripts\activate

2. Start the Flask application:

python app.py

3. Access the application:

• Web Interface: Open http://127.0.0.1:5001 in your browser
• API Endpoints: Available at http://127.0.0.1:5001/tasks

API Endpoints

Method	Endpoint	Description
GET	/	Web interface
GET	/tasks	Retrieve all tasks
POST	/tasks	Create a new task
GET	/tasks/<id>	Retrieve a specific task
PUT	/tasks/<id>	Update a task
DELETE	/tasks/<id>	Delete a task

Example API Usage

Create a new task:

curl -X POST http://127.0.0.1:5001/tasks \
  -H "Content-Type: application/json" \
  -d '{"title": "New Task", "description": "Task description"}'

Project Structure

task-manager-api/
├── api/
│   ├── __init__.py
│   ├── models.py      # Database models
│   └── routes.py      # API routes
├── static/
│   ├── css/
│   │   └── style.css  # Application styles
│   └── js/
│       └── script.js  # Frontend JavaScript
├── templates/
│   └── index.html     # Main HTML template
├── app.py            # Application entry point
├── requirements.txt  # Python dependencies
└── README.md        # This file

Development

To run the application in development mode with debug features:

python app.py

The application will automatically reload when you make changes to the code.

Docker Support

The application includes Docker support for containerized deployment.

1. Build the Docker image:

docker build -t task-manager-api .

2. Run the container:

docker run -p 5001:5000 task-manager-api

Or use Docker Compose:

docker-compose up

Testing

Run the test suite:

pytest

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.