About

After years of working with different Django projects, I noticed some excellent design patterns and packages that helps maintain the project's code quality, simplicity, readability, maintainability, reliability, and testing.

This is a compilation of patterns and libraries that I learned over the years to help build a robust Django application fast.

Stack included

App

• Django3, framework for building fast and clean web applications
• Postgres, open-source object-relational database for persisting data
• Redis, in-memory data structure store used as a database, cache, and message broker
• GraphQL/Graphene, query language for the API and a runtime for fulfilling those queries with existing data
• Python decouple, helps you to organize your project settings on environment variables

Background and scheduled tasks:

• Celery, task queue with to process background tasks
• Celery Beat (Periodic tasks), scheduler to kick off tasks at regular intervals

Testing:

• Pytest, test framework that makes easy to write small and scalable tests
• Faker, generates fake data for you
• Freezegun, allows your tests to freeze or travel through time
• Factory Boy, fixture replacement tool that aims to easy-to-use factories for complex objects
• Pytest-Mock, plugin that provides a mocker fixture that is a wrapper around the mock package

Development

• Docker, build and run the entire application in docker containers
• Watchdog, python file change monitor to reload django fast when you modify a python file
• Isort, sort and organize your imports automatically
• Black, code-formatter that automatically restructure your code
• Flak8, tool for styled guide enforcement
• Pre-commit, framework for managing and maintaining pre-commit hooks

Patterns

• Repository Pattern
  • Almost every query should live in core/db/repository/
  • Avoid writing queries on Django's Manager/QuerySet.
  • The repository functions should return a list of instances, instead of a QuerySet. This makes easy caching data.
• Single Django app layer
  • It's recommend to write the entire application inside the core
  • Avoid creating new django apps
• One model per file
  • Each model should have its own file in core/db/models/
• Service layer
  • All business logic should be added in core/services/

Setup

Clone the project

$ git clone git@github.com:marcosflp/django-boilerplate.git project_name
$ cd project_name

Install pre-commit

$ pip install pre-commit
$ pre-commit install

Docker

• Running the app: $ docker compose up
• Running tests: docker compose exec web pytest

Locally

• Create a new virtual env
• Install the dependencies: $ pip install -r requirements.txt
• You have to install and run the postgres server. Also, configure the database settings
• Run migrations: $ python manage.py migrate
• Running the server: $ python manage.py runserver
• Running tests: $ pytest

Deployment

Automatically deploy this project to AWS with Terraform and Ansible!

Set environment variables

AWS - With admin access to create EC2, RDS instances and network resources

$ export AWS_ACCESS_KEY_ID=
$ export AWS_SECRET_ACCESS_KEY=

Terraform

$ export TF_VAR_AWS_DB_PASSWORD_DJANGO_BOILERPLATE=

Terraform

Setup

$ cd deployment/terraform
$ terraform init
$ terraform apply

Ansible

Create and set all Django production's settings env variables

$ cp deployment/config_files/.env.production.example deployment/config_files/.env.production

Update Nginx domain name at

$ deployment/config_files/nginx/sites-enabled/django_boilerplate.org.conf

Update gunicorn path at

$ deployment/config_files/gunicorn.service

Set the hosts at

$ deployment/config_files/inventory

Setup the entire Django app and Webservers

$ cd deployment/ansible
$ ansible-playbook -i inventory playbook_setup_ubuntu.yml playbook_setup_django.yml playbook_setup_webservers.yml --tags="setup"

Deploy updates

$ cd deployment/ansible
$ ansible-playbook -i inventory playbook_setup_ubuntu.yml playbook_setup_django.yml playbook_setup_webservers.yml --tags="deploy"