Writing Type-Agnostic Functions

This lesson covers writing type-agnostic functions that take advantage of Python being a dynamically typed language. It's written for anyone searching "Python dynamic typing" or "Python generic functions".

Because Python is a dynamically typed language, a function can generally accept a value of any type. Writing "a general-purpose function that isn't tied to a single type" lets you reuse the same logic for both numbers and strings — a flexibility distinctly characteristic of Python, often contrasted with stricter languages like TypeScript.

The sample code's larger(a, b) function handles both numeric comparisons and string comparisons with the exact same logic. The > operator compares magnitude for numbers and dictionary (alphabetical) order for strings, letting the same function work unchanged across different data types.

This flexibility is a double-edged sword — passing in an unintended type doesn't raise an error, which can lead to a bug. Combining type hints or upfront validation where needed increases safety. Comparing a number and a string, for example, can produce an unexpected result, so be careful with unusual type combinations.

Balancing the flexibility of dynamic typing with safety is where real skill in Python code design shows. In large real-world projects, it's common to combine type hints with a type-checking tool like mypy to increase safety.