Case Study
Explore how to improve object-oriented design using Python's @dataclass decorator and immutable NamedTuple classes. Understand the benefits and limitations of dataclasses, including automatic method generation and type hinting with forward references. Learn to navigate design trade-offs between inheritance and composition to build clearer, maintainable code in Python data models.
We'll cover the following...
Let’s revisit our design, leveraging Python’s @dataclass definitions. This holds some potential for streamlining our design. We’ll be looking at some choices and limitations, leading us to explore some difficult engineering trade-offs where there isn’t one obvious best approach.
We’ll also look at immutable NamedTuple class definitions. These objects have no internal state changes, leading to the possibility of some design simplifications. This will also change our design to make less use of inheritance and more use of composition.
Logical model
Let’s review the design we have so far for our model.py module. This shows the hierarchy of Sample class definitions, used to reflect the various ...