Adrian Dziubek - Python Descriptors for Better Data Structures Have you ever wondered how Django models work? I'll present a story of data structure transformation. I will talk about ideas from Django models that I used and how I rediscovered descriptor API. I will talk about printing, serializing, comparing data structures and some other examples, where descriptors excel at making declarative code easier to write. ----- I worked as a developer of a testing framework for a C++ server. The framework tested binary protocol implemented by the server. Most of the work involved testers preparing test cases. The data format was primitive structures -- hard to read and easy to break. Field order and all the data had to be entered manually. At the time, I have already seen the better world -- the models from Django. Have you ever wondered how those work? Step by step, I used the ideas from there to make the structures more friendly and on my way I rediscovered descriptors. I'll show in incremental steps, how: - used keyword arguments to lower signal to noise ratio, - order of definition for sorting the fields, - realized that `__call__` is used instead of assignment, - used `__setattribute__` as first step to extend primitive fields, - discovered that I'm actually reimplementing descriptors, and how it lead me to: - implement printing in a way that is friendly to regression testing, - use diff library for less code and better results, - implement more readable validation. I want to show how descriptors work in Python and how they enable declarative style of programming. By the end of the talk I want you to understand what is at the core of the magic behind field types used by object relational mappers like Django.