Function Basics

Functions are the primary building block for organizing code in Python. They allow you to define reusable blocks of logic, improve code readability, and make debugging easier. Understanding function definition, invocation, and the execution model is essential for every Python developer.

Defining Functions

The def keyword creates a function object and binds it to a name:

• Function name: Follows the same rules as variable names — use snake_case by convention
• Parameters: Listed in parentheses — can include positional, keyword, default, args, and *kwargs
• Docstring: Optional but recommended first line — describes what the function does
• Body: Indented block of statements that executes when the function is called
• Return: Optional return statement — if omitted, the function returns None implicitly

Function Execution Model

• Definition time: def creates a function object — no code runs yet
• Call time: Parentheses after the name trigger execution — func()
• Local frame: Each call creates a new local scope with its own variables
• Stack frames: Nested calls create a call stack — Python's default limit is ~1000 frames

Multiple Return Values

Python functions can return multiple values using tuples. This is commonly used for functions that compute related results:

• Tuple packing: return a, b, c automatically packs into a tuple
• Tuple unpacking: x, y, z = func() unpacks the returned tuple
• Named tuples: Use collections.namedtuple for readable multi-value returns

Best Practices

• Single responsibility: Each function should do one thing and do it well
• Descriptive names: Use verb phrases like calculate_total() or validate_email()
• Keep them short: Functions longer than ~20 lines should be broken into smaller functions
• Avoid side effects: Prefer pure functions that don't modify external state