How to Set Up Your Django React Boilerplate Project

Mar 16, 2022 | Programming

Integrating Django with React can seem like a daunting task, but with the Django React Boilerplate, this process becomes much simpler and efficient. This boilerplate gives you a robust framework to build your applications with the latest libraries and tools. In this guide, we’ll walk through the setup and features of this boilerplate, ensuring you can get started without a hitch!

Overview of Django React Boilerplate

The Django React Boilerplate serves as a foundation for your projects by incorporating various modern tools including:

Setting Up Your Project

Follow these steps to kickstart your project:

  1. Ensure Python 3.12 is installed.
  2. Install Django by running: pip install django.
  3. Open your terminal and navigate to your desired project directory.
  4. Run the following command to create your Django project (replace project_name with your chosen name):
  5. django-admin startproject project_name --extension py,json,yml,yaml,toml --name Dockerfile,README.md,.env.example,.gitignore,Makefile --template=https://github.com/vintasoftware/django-react-boilerplate/archive/refs/heads/main.zip
  6. If needed, create your project in the current directory using:
  7. django-admin startproject project_name . --extension py,json,yml,yaml,toml --name Dockerfile,README.md,.env.example,.gitignore,Makefile --template=https://github.com/vintasoftware/django-react-boilerplate/archive/refs/heads/main.zip

Understanding the Code Structure

Think of the boilerplate code as a well-organized library. Each book represents a tool or library that contributes to the overall ecosystem of your application. In this library:

  • Django is like the librarian, overseeing the organization and management of resources (data).
  • React is akin to interactive displays, engaging users and bringing the information to life.
  • TypeScript adds a layer of well-organized shelving, preventing misplaced books (errors) by enforcing strict organization (types).
  • Tools like Celery and PostgreSQL serve as the back-office staff, managing tasks efficiently behind the scenes.

This cohesive library enables users to locate what they need swiftly without chaos, much like your application should operate seamlessly for its users.

Running the Project

To run the project:

  • Navigate to the project directory with cd project_name.
  • Set up the local environment files:
  • cp backend/project_name/settings/local.py.example backend/project_name/settings/local.py
    cp backend/.env.example backend/.env
  • Run the initial setup with Docker:
  • make docker_setup
  • Create and migrate your database:
  • make docker_makemigrations
    make docker_migrate
  • Start your project:
  • make docker_up

Now, access your application at http://localhost:8000 to view it running!

Troubleshooting

If you encounter issues, here are some suggestions:

  • Ensure you have all dependencies installed correctly.
  • Check for any typos in the configuration files.
  • Make sure Docker is running if using Docker.
  • If you experience a blank page, verify if the frontend is communicating with the backend correctly, particularly if the Django app is running on port 8000.
  • Check container logs for specific errors with:
  • make docker_logs service_name
  • If problems persist, consult the documentation or reach out for help.

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Final Thoughts

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

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