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# Getting Started with Django and GraphQL Using Strawberry: A Comprehensive Guide

**[Collections](https://daily.dev/sources/collections)** · 3 min read · 2 upvotes · 0 comments

## Summary

The guide helps new developers set up a Django app with GraphQL using Strawberry, and PostgreSQL within Docker containers. It covers installing Visual Studio Code and Docker Desktop, using Docker compose for container management, and configuring VSCode for efficient coding. Designed for beginners, it aims to enhance understanding of Django ORM and GraphQL.

## Content

# Comprehensive Guide to Setting Up Django with GraphQL and Docker

This article serves as a detailed guide for new developers looking to set up their development environment for building a Django application using GraphQL with Strawberry. By the end of this guide, you will have a Django app configured with PostgreSQL running inside Docker containers, with Visual Studio Code set up for efficient coding.

## Course Introduction

In this course, you will learn how to build GraphQL APIs using Django and Strawberry. It covers fundamental concepts, including defining models, querying data, managing relationships, and optimizing queries. Designed for beginners with basic Python knowledge, this course helps developers understand Django ORM and GraphQL's practical aspects. Additional resources are available on platforms like YouTube and Udemy.

## Setting Up Visual Studio Code

Visual Studio Code (VSCode) is a powerful open-source code editor ideal for Python development. Install VSCode on your preferred OS—Windows, Mac, or Linux—and customize the interface's scale and theme according to your preferences. Utilize the integrated terminal and install essential extensions to enhance your coding prowess.

### Customizing Your Environment

Enhance your experience with formatters and linters. Use tools like Ruff for Python formatting to maintain code readability and efficiency. Set formatting rules and automate code formatting through configuration files, ensuring consistent coding practices across your projects.

## Installing Docker Desktop

Docker Desktop simplifies the process of managing containers and volumes, allowing you to create consistent development environments across various machines. Begin by installing Docker Desktop, an intuitive application facilitating container orchestration via a user-friendly interface.

### Understanding Docker Fundamentals

**Images and Containers**: Docker images contain all the application code and dependencies, while containers are running instances of these images. 

**Volumes**: Volumes are used for storing data so that it persists even when containers are stopped. These ensure your data remains secure and accessible across sessions.

## Creating PostgreSQL and Django Containers

This section focuses on setting up PostgreSQL with Django inside Docker containers, necessary for developing a robust backend.

### Writing Docker Files

Create Docker files to define your application's environment and instructions for creating your images. These files contain all the necessary details regarding the specific services your application relies on.

### Using Docker Compose

Define multi-container applications in a Docker Compose file, ensuring efficient integration and management of services like Django and PostgreSQL. Docker Compose allows you to run multiple docker containers as a single service, specified in simple YAML files, promoting ease in deployment and scalability.

## Final Thoughts

By following this comprehensive guide, you've set the groundwork for building efficient, scalable Django applications with GraphQL and Docker. The course aims to facilitate practical understanding and application of these technologies, empowering developers to create robust, reliable backend services.

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---

Tags: [#webdev](https://daily.dev/tags/webdev), [#python](https://daily.dev/tags/python), [#postgresql](https://daily.dev/tags/postgresql), [#graphql](https://daily.dev/tags/graphql), [#django](https://daily.dev/tags/django)

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