Django framework and libraries documentation

Django Framework Documentation

Django is a free framework for Python-based web applications that uses the MVC design pattern.

Python documentation

Python is an easy to learn, powerful programming language.

Django ORM Cookbook

Django ORM Recipes is a book about working with Django ORM and Django models. Django ORM is one of the key pillars of Django.

Django Rest Framework

Django Rest Framework (DRF) is a library that works with standard Django models to create a flexible and powerful API for a project.


SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL.

Django CMS

Django CMS is a modern web publishing platform built on Django, a web application framework "for perfectionists with deadlines".

Channels - extension for asynchronous work with Django

Channels is a project that takes Django and extends it beyond HTTP to handle WebSockets, chat protocols, IoT protocols, and more.

asgiref - ASGI specification and utilities

ASGI (Asynchronous Server Gateway Interface) is the spiritual successor to WSGI, designed to provide a standard interface between asynchronous web servers, platforms, and Python applications.

Django Crispy Forms - best form builder

The best way to get Django DRY forms. Create reusable programmatic layouts from components with full control over the rendered HTML without writing HTML in templates. All this without breaking the standard Django way of working, so it works great with any other forms application.

Python Social Auth Documentation

Python Social Auth is an easy-to-configure social authentication/registration mechanism with support for multiple platforms and authentication providers.

Articles, news, and tips on Django and Python

Python Decorators

Decorators are quite a useful Python feature. However, it can seem that any resources or insights surrounding them makes the whole concept impossible to understand. But decorators are, in fact, quite simple. Read on, and we’ll show you why.

Python List Comprehensions

Lists are easy to recognize in Python. Whenever we see brackets ‘[]’, we know that lists are afoot. Declaring lists is just about as easy as gets in Python.

Pyton Regular Expressions

REGEX is a module used for regular expression matching in the Python programming language. In fact, REGEX is actually just short for regular expressions, which refer to the pattern of characters used in a string. This concept can apply to simple words, phone numbers, email addresses, or any other number of patterns.

Modeling Trees with SQLAlchemy ORM and Postgres Ltree

When writing software, you’ll often encounter situations where a tree is the most appropriate data structure for working with hierarchical data. Although Python lacks a built-in native implementation of trees, it’s relatively straightforward to implement one yourself, especially with help from third-party libraries.

Guide to Python Dictionaries

Second to a Python list, the dictionary or “dict” is a place in memory to store a series of values – also called a collection. The dictionary is special because values are not referenced in order using a numerical index. Rather, in a dictionary, values are referenced with a user-defined key, just as words in a physical dictionary are “keys” associated with the “value” of their meaning. This key is usually a string, but could be any number of data types.

Guide to String Formatting with Python

String formatting is a robust and powerful part of any python programmer’s toolkit – nearly every piece of production software takes advantage of it in one way or another. The means of formatting strings, though, have greatly evolved over Python’s lifetime. From the % formatting, to the format() method, to formatted string literals, there’s no limit as to the potential of string crafting.

A Guide to Python’s Flask Web Interface

Flask is a bare-bones Python framework for building apps that use the web browser as the front-end, rather than the command-line as the front-end. Flask abstracts away lower-level tasks, such as setting up a development web server, managing information flow from the browser to the Python interpreter, and more. Using Flask thus allows you, the developer, to focus on the application logic rather than worrying about infrastructural things.

Practical Machine Learning with Python and Keras

Machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to “learn” (e.g., progressively improve performance on a specific task) from data, without being explicitly programmed. Think of how efficiently (or not) Gmail detects spam emails, or how good text-to-speech has become with the rise of Siri, Alexa, and Google Home.

Best Practices for Using Functional Programming in Python

Python is a very versatile, high-level programming language. It has a generous standard library, support for multiple programming paradigms, and a lot of internal transparency. If you choose, you can peek into lower layers of Python and modify them – and even modify the runtime on the fly as the program executes.

TensorFlow or PyTorch? A Guide to Python Machine Learning Libraries (with examples!)

Python is the fastest-growing programming language out there. That isn’t surprising given that it’s simple, easy to use, free, and applicable for many computing tasks. Data scientists in particular have embraced Python’s efficient syntax, learnability, and easy integrations with other languages such as C and C++.

Django and Python "Questions and answers"

Django Class-Based Views Reference