Analytics Pages is a Django-based web application designed to showcase data science projects. The application allows users to view, add, and manage projects, with features for user authentication and project details.

• User authentication (registration, login, logout)
• Add, update, and view data science projects
• Responsive design with Bootstrap
• Integration with PostgreSQL using Docker
• Continuous integration with GitHub Actions

• Python 3.9+
• Docker
• Docker Compose

1. Clone the Repository:

   git clone https://github.com/surajwate/analyticspages.git
   cd analyticspages

2. Create a .env File:

   Create a .env file in the root directory with the following contents:

   SECRET_KEY=your-secret-key
   DEBUG=True
   ALLOWED_HOSTS=localhost,127.0.0.1
   POSTGRES_DB=yourdbname
   POSTGRES_USER=yourusername
   POSTGRES_PASSWORD=yourpassword
   DATABASE_URL=postgres://yourusername:yourpassword@db:5432/yourdbname
   

3. Create and Activate Virtual Environment (if not using Docker):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

4. Install Dependencies:

   pip install -r requirements.txt

1. Build and Run Containers:

   docker-compose up --build

2. Apply Migrations:

   docker-compose exec web python manage.py migrate

3. Create a Superuser:

   docker-compose exec web python manage.py createsuperuser

4. Access the Application:

   Open your web browser and navigate to http://localhost:8000.

1. Run Tests with Docker:

   docker-compose exec web pytest

2. Run Tests Locally:

   pytest

We use GitHub Actions for continuous integration. The CI pipeline runs tests and checks for code quality on every push and pull request. The configuration is defined in the .github/workflows/ci.yml file.

• GitHub Discussions: Join the conversation in our Discussions section.
• Wiki: Check out our Wiki for detailed documentation and guides.

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

1. Fork the repository
2. Create a new branch (git checkout -b feature-branch)
3. Make your changes
4. Commit your changes (git commit -m 'Add new feature')
5. Push to the branch (git push origin feature-branch)
6. Open a pull request

Feel free to suggest improvements or contribute to the project!