Luciano Ramalho - Fluent Python

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Guidos sense of the aesthetics of language design is amazing. Ive 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.

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 find 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, coroutines, classes, context managers, and so on.

When using a framework,we spend a lot of time coding methods that are called by the framework.The same happens when we leverage the Python Data Model.The Python interpreter invokes special methods to perform basic object operations,often triggered by special syntax.The special method names are always written with leading and trailing double underscores (i.e., __getitem__).For example, the syntax obj[key] is supported by the __getitem__ special method.In order to evaluate my_collection[key], the interpreter calls my_collection.__getitem__(key).

The special method names allow your objects to implement,support, and interact with fundamental language constructs such as:

• Collections;

• Attribute access;

• Iteration (including asynchronous iteration using async for);

• Operator overloading;

• Function and method invocation;

• String representation and formatting;

• Asynchronous programing using await;

• Object creation and destruction;

• Managed contexts (including asynchronous context managers using async with).