Functions & basics
Reusable building blocks — parameters, returns, scope, and clear function design.
Add Type Hints to Function Parameters and Return in Python
Add type hints to function parameters and return values in Python for clearer, more maintainable code using the typing module.
from typing import List, Optional, Dict
def average(numbers: List[float]) -> float:
return sum(numbers) / len(numbers)
def full_name(first: str, last: Optional[str] = "") -> str:
return f"{first} {last}".strip()
def build_user(name: str, age: int, email: Optional[str] = None) -> Dict[str, object]:
us…Chain Generators with yield from in Python
Combine multiple generators into one seamless sequence using the `yield from` delegation syntax in Python.
def numbers():
yield 1
yield 2
yield 3
def letters():
yield 'a'
yield 'b'
yield 'c'
def combined():
yield from numbers()
yield from letters()
if __name__ == "__main__":
print(list(combined()))Create a retry decorator with max attempts in Python
A decorator that retries a function up to a specified number of times when it raises an exception, with an optional delay between attempts.
import functools
import time
def retry(max_attempts, delay=0.1):
"""Retry a function up to max_attempts times on exception."""
def decorator(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
for attempt in range(1, max_attempts + 1):
try:
…How to Compose Two Functions into a Single Callable in Python
Combine two Python functions into a single callable using a compose helper, then apply the chained call.
def add_one(x):
return x + 1
def double(x):
return x * 2
def compose(f, g):
return lambda x: f(g(x))
add_then_double = compose(double, add_one)
double_then_add = compose(add_one, double)
result1 = add_then_double(5)
result2 = double_then_add(5)
print(f"add_one then double(5) = {result1}")
print(f"doub…How to Implement a Trampoline for Tail Recursion in Python
This code implements a trampoline decorator that converts tail-recursive functions into iterative loops, allowing deep recursion without hitting Python's recursion limit.
def trampoline(fn):
"""Convert a tail-recursive function into an iterative loop."""
def wrapper(*args, **kwargs):
result = fn(*args, **kwargs)
while callable(result):
result = result()
return result
return wrapper
@trampoline
def factorial(n, acc=1):
"""Tail-recursi…How to Use the if __name__ == '__main__' Guard in Python
This code defines reusable functions and uses the standard main guard to run them only when the script is executed directly, not when imported.
def greet(name: str) -> str:
"""Return a friendly greeting."""
return f"Hello, {name}!"
def get_planet() -> str:
"""Return the name of our planet."""
return "Earth"
if __name__ == "__main__":
user = "Dorothy"
print(greet(user))
print(f"We live on {get_planet()}.")How to Validate Function Arguments in Python
Shows how to manually check argument types and values in a Python function, raising clear TypeError and ValueError messages.
def calculate_area(length: float, width: float) -> float:
"""Calculate the area of a rectangle with manual type validation."""
if not isinstance(length, (int, float)) or isinstance(length, bool):
raise TypeError(f"length must be a number, got {type(length).__name__}")
if not isinstance(width, (int,…Python Function Default Parameters Explained with Examples
Learn how to define Python functions with default parameter values and call them with fewer arguments than declared.
def greet(name, greeting="Hello", punctuation="!"):
return f"{greeting}, {name}{punctuation}"
def calculate_area(length, width=1, unit="sq units"):
area = length * width
return f"Area: {area} {unit}"
if __name__ == "__main__":
print(greet("Alice"))
print(greet("Bob", "Hi"))
print(greet("Charl…Browse by section
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Functions & basics — Python code examples
What you will find here
This page collects functions & basics snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.