Master Python’s Type System: Write Safer, Smarter Code

Learn how to use Python’s type system to protect your code against weaknesses and understand its role in modular systems

What you’ll learn
✓ How to fix bugs faster by understanding runtime error messages better
✓ To prevent common type problems by using best type system practices
✓ How to use static type checkers and type hints to improve code quality
✓ To detect architectural problems earlier by using protocol classes with type hints
✓ The proper terminology of type features that you already are using today
✓ How attribute lookup and dynamic typing are the key to duck typing in Python
✓ To make the transition from another language more effective by learning Python’s unique language features and type system
✓ How variables work with type inference and inspecting their type tags

Requirements
● Beginner experience in Python or another programming language
● Python 3.12 or newer installed

Description
In Python, it’s easy to overlook types. You can simply write a = 10, and it works without needing to specify its type. However, beneath Python’s simple and intuitive syntax lies a surprisingly complex type system. In fact, as you’ll discover in this course, Python integrates multiple type systems to manage data and behavior effectively.

You might ask—why study types at all? After all, you probably use them every day in Python without thinking much about it. And that’s true: it’s entirely possible to write functioning code without understanding the details of how the type system works. But, as with many aspects of software engineering, gaining a deeper understanding of the how and why allows you to make smarter, more intentional design decisions in your code and systems.

Target audience

Developers who especially benefit from this course, are

• Beginners and intermediates who want to know the mechanics and purpose of types and type systems in Python

• Software engineers who want to use the type system as an extra development tool by adding type hints to improve their code quality

• Developers who want to learn the proper terminology to make discussing code in your team and searching for information online more efficient

Challenges

Python is an easy language to learn. It hides many of the nuances about data types. But when developers get more experienced, they are more confronted with Python’s unique way to create, instantiate and work with data types. It is at this moment where it helps to take a deep dive into Types and Type Systems.

What can you do after this course?

• Fix bugs faster by understanding error messages better

• Prevent common type problems by knowing type system techniques

• Make classes more efficient by using Python’s unique language features

• Create clean modular design by using Protocol classes and type hints

• Discuss pro’s and con’s of proposed solutions by learning proper technical terms

• Make the transition from another language to Python more efficient

Topics

• Introduction to type systems: Type system categories and their basic building blocks: types.

• Implicit vs. explicit typing: Literals, variables and attributes.

• Dynamic vs. static typing: Duck typing, Python protocols and the Python Datamodel, Compilers and interpreters.

• Type Hints: Annotations, static type checkers, kind of types, special typing constructs.

• Type flexibility: Safe, sound, complete. Promotion, conversion and comparison.

• Nominal vs. structural typing: Using composite classes and protocols to design interfaces for modular systems.

Duration

3 hours video time.

The teacher

This course is taught by Loek van den Ouweland, a senior software engineer with 30 years of professional experience. Loek is the creator of Wunderlist for windows, Microsoft To-do and Mahjong for Windows and loves to teach software engineering.

Who this course is for
■ Beginners and intermediates who want to know the mechanics and purpose of types and type systems in Python
■ Software engineers who want to use the type system as an extra development tool by adding type hints to improve their code quality
■ Developers who want to learn the proper terminology to make discussing code in your team and searching for information online more efficient