Functions are fundamental to writing clean, efficient, and reusable code in Python. They allow you to group code into logical blocks that can be called multiple times, with or without inputs, and can return outputs.
This tutorial includes:
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What functions are and why they’re useful
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Defining and calling functions
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Parameters vs arguments
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Return values
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Default, keyword, and variable-length arguments
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Scope and lifetime
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Lambda functions
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Common pitfalls and tips
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A complete example at the end
✅ What is a Function?
A function is a block of code that only runs when called. It can take inputs (parameters) and return outputs.
Benefits of Using Functions
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Avoid repetition (DRY principle)
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Improve readability and structure
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Easy debugging and testing
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Promote code reusability
Defining a Function
def greet():
print("Hello, welcome to Python!")
Calling the Function
greet()
Output:
Hello, welcome to Python!
Function with Parameters
def greet_user(name):
print(f"Hello, {name}!")
greet_user("Alice")
Output:
Hello, Alice!
Returning Values with return
def square(number):
return number * number
result = square(4)
print(result)
Output:
16
Multiple Parameters
def add(a, b):
return a + b
print(add(5, 3))
⚙️ Default Parameters
def greet(name="Guest"):
print(f"Hello, {name}!")
greet() # Hello, Guest!
greet("John") # Hello, John!
Keyword Arguments
def describe_pet(animal, name):
print(f"{name} is a {animal}.")
describe_pet(animal="dog", name="Buddy")
Variable-Length Arguments
✳️ *args – Multiple Positional Arguments
def add_all(*numbers):
return sum(numbers)
print(add_all(1, 2, 3, 4)) # 10
✳️ **kwargs – Multiple Keyword Arguments
def print_user_info(**info):
for key, value in info.items():
print(f"{key}: {value}")
print_user_info(name="Alice", age=30)
Scope: Local vs Global
x = 10 # Global variable
def show():
x = 5 # Local variable
print("Inside:", x)
show()
print("Outside:", x)
Output:
Inside: 5
Outside: 10
Lambda Functions – Anonymous One-Liners
square = lambda x: x * x
print(square(5)) # 25
Another Example
add = lambda a, b: a + b
print(add(3, 4)) # 7
Use lambdas for small, throwaway functions — not complex logic.
Complete Example: Calculator
def calculator(a, b, operation):
if operation == "add":
return a + b
elif operation == "subtract":
return a - b
elif operation == "multiply":
return a * b
elif operation == "divide":
if b == 0:
return "Cannot divide by zero"
return a / b
else:
return "Unknown operation"
print(calculator(10, 5, "add")) # 15
print(calculator(10, 0, "divide")) # Cannot divide by zero
Common Pitfalls
| Mistake | Description | Fix |
|---|---|---|
| Forgetting to call function | def func(): does nothing unless called |
Use func() to call it |
| Confusing parameters vs args | Parameters are declared, arguments are passed | Understand function signatures |
| Modifying global variables | Can cause bugs | Use global keyword carefully |
No return where expected |
Function returns None |
Add a return statement |
Tips and Best Practices
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✅ Use functions to break large tasks into small steps
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✅ Use meaningful names for functions and parameters
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✅ Add docstrings for documentation
def greet(name):
"""Prints a greeting to the user."""
print(f"Hello, {name}")
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✅ Keep functions short and focused on a single task
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✅ Use type hints (Python 3.5+):
def add(a: int, b: int) -> int:
return a + b
Summary Table
| Concept | Example |
|---|---|
| Basic function | def func(): |
| With parameters | def func(x): |
| Return value | return x * x |
| Default values | def greet(name="Guest") |
| Variable args | *args, **kwargs |
| Lambda function | lambda x: x + 1 |
| Docstring | """Function doc.""" |
What’s Next?
After mastering functions, explore:
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Recursion (functions calling themselves)
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Function decorators
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First-class functions & closures
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Generators &
yield
