Search⌘ K
AI Features
Home
Courses
Learn Python 3: Comprehensive Programming Guide

Type Hints and Docstrings

Explore how to enhance your Python functions by adding type hints and structured docstrings. Understand how these tools clarify expected data types and document function behavior to make your code more readable and maintainable in professional projects. Learn to use type unions for flexible arguments and how docstrings provide essential usage guidance.

We'll cover the following...

Until now, we have written code primarily for the computer to execute. But professional software development is different; we write code for people to read. When we define a function, we know exactly what it does and what arguments it needs right now. But what about three months from now? Or when a teammate tries to use it?

Without clear guideposts, a simple function can become an opaque box that requires line-by-line deciphering. We solve this by embedding documentation and type expectations directly into the code itself, turning our programs into readable, self-explanatory blueprints.

The ambiguity of dynamic typing

Python is dynamically typed, which means we do not have to explicitly declare variable types. While this makes writing scripts fast, it can create ambiguity in larger programs. Consider a function designed to combine data.

Python
def combine(a, b):
    return a + b
# Is this addition?
print(combine(10, 20))
# Is this string concatenation?
print(combine("Hello, ", "World"))
# What happens if we mix them?
# combine(10, "World")  # This causes a crash

Without looking at the internal code (or running it and crashing), we cannot know if a and b should be numbers, strings, or lists. This ambiguity forces developers to guess or endlessly check implementation details, slowing down development and increasing bugs.

Adding type hints

To remove ...