PWA and Django #What is a Progressive Web Application?
Originally published on Substack: https://andresalvareziglesias.substack.com/p/pwa-and-django-1-what-is-a-web-application?r=1ymfiv
The current web applications are much more than web pages that show interactive info. Sometimes, they behave almost like native apps. And what kind of magic do they use to do that? This series of posts will answer that question...
What is a Progressive Web Application
I like the definition of PWA's at Mozilla Developer site (https://developer.mozilla.org/en-US/docs/Web/Progressive_web_apps):
A progressive web app (PWA) is an app that's built using web platform technologies, but that provides a user experience like that of a platform-specific app. Like a website, a PWA can run on multiple platforms and devices from a single codebase. Like a platform-specific app, it can be installed on the device, can operate while offline and in the background, and can integrate with the device and with other installed apps.
It's an hybrid between a native app and a webpage, thanks to the incredible capacities of the nowadays web browsers, like:
- Embedded database
- Offline workers
- Desktop and mobile operating system integration
- Etc.
In this series of posts, we will develop an offline and installable Progressive Web Application using our beloved Django, with the help of Google Project IDX.
Create the demo environment
Create a github repo:
Create a new app in IDX importing that repo:
Initialize the Django app from the IDX console:
python -m venv ~/.venv source ~/.venv/bin/activate mkdir src cd src echo "django" > requirements.txt pip install --upgrade pip pip install -r requirements.txt django-admin startproject djangopwa
Do the initial migration and run the server:
python manage.py migrate python manage.py runserver
Create IDX files to enable embedded preview, with the help of the project https://github.com/arifnd/nix-idx/, that compiles several IDX configurations:
cd ~/djangopwa wget https://raw.githubusercontent.com/arifnd/nix-idx/main/python/django/devserver.sh cd ~/djangopwa/.idx wget https://raw.githubusercontent.com/arifnd/nix-idx/main/python/django/dev.nix
NOTE: Edit the default dev.nix and devserver.sh as needed and restart IDX environment
Then, create demo app:
python manage.py startapp demo
Add an empty view:
from django.shortcuts import render def index(request): context = {} return render(request, "index.html", context)
Create the routes to the new app:
from django.contrib import admin from django.urls import include, path urlpatterns = [ path("", include("demo.urls")), path('admin/', admin.site.urls), ]
And wait a few days until the next chapter!
About the list
Among the Python and Docker posts, I will also write about other related topics, like:
- Software architecture
- Programming environments
- Linux operating system
- Etc.
If you found some interesting technology, programming language or whatever, please, let me know! I'm always open to learning something new!
About the author
I'm Andrés, a full-stack software developer based in Palma, on a personal journey to improve my coding skills. I'm also a self-published fantasy writer with four published novels to my name. Feel free to ask me anything!
The above is the detailed content of PWA and Django #What is a Progressive Web Application?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.

You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

You can learn the basics of Python within two hours. 1. Learn variables and data types, 2. Master control structures such as if statements and loops, 3. Understand the definition and use of functions. These will help you start writing simple Python programs.

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.
