Fluent Python

Chapter 1. The Python Data Model

Guido’s sense of the aesthetics of language design is amazing. I’ve met many fine language designers who could build theoretically beautiful languages that no one would ever use, but Guido is one of those rare people who can build a language that is just slightly less theoretically beautiful but thereby is a joy to write programs in.¹

Jim Hugunin, Creator of Jython, cocreator of AspectJ, architect of the .Net DLR

One of the best qualities of Python is its consistency. After working with Python for a while, you are able to start making informed, correct guesses about features that are new to you.

However, if you learned another object-oriented language before Python, you may have found it strange to use len(collection) instead of collection.len(). This apparent oddity is the tip of an iceberg that, when properly understood, is the key to everything we call Pythonic. The iceberg is called the Python data model, and it describes the API that you can use to make your own objects play well with the most idiomatic language features.

You can think of the data model as a description of Python as a framework. It formalizes the interfaces of the building blocks of the language itself, such as sequences, iterators, functions, classes, context managers, and so on.

While coding with any framework, you spend a lot of time implementing methods that are called by the framework. The same happens when you leverage the Python data model. The Python interpreter ...