Python Functions Practice: 15 Core Exercises with Solutions

Part 1: Basic Definition, Parameters & Arguments (Questions 1 to 4) 🔝

1. Question 1: Define a function greet(name) that prints a personalized greeting with an optional default value.
   View Solution

   def greet(name='Guest'):
       print(f'Hello, {name}!')
   
   greet('Alex')
   greet()

   Terminal Output:

   Hello, Alex!
   Hello, Guest!

2. Question 2: Demonstrate positional vs. keyword arguments in a function describe_pet(animal, name).
   View Solution

   def describe_pet(animal, name):
       print(f'I have a {animal} named {name}.')
   
   # Positional arguments
   describe_pet('dog', 'Buddy')
   # Keyword arguments (order independent)
   describe_pet(name='Whiskers', animal='cat')

   Terminal Output:

   I have a dog named Buddy.
   I have a cat named Whiskers.

3. Question 3: Write a function sum_all(*numbers) that sums an arbitrary number of numeric arguments.
   View Solution

   def sum_all(*numbers):
       total = 0
       for n in numbers:
           total += n
       return total
   
   print('Sum 3 items: ', sum_all(10, 20, 30))
   print('Sum 5 items: ', sum_all(1, 2, 3, 4, 5))

   Terminal Output:

   Sum 3 items:  60
   Sum 5 items:  15

4. Question 4: Write a function build_profile(first, last, **user_info) accepting arbitrary keyword arguments.
   View Solution

   def build_profile(first, last, **user_info):
       profile = {'first_name': first, 'last_name': last}
       profile.update(user_info)
       return profile
   
   user = build_profile('Alex', 'Ronald', role='Admin', dept='IT')
   print(user)

   Terminal Output:

   {'first_name': 'Alex', 'last_name': 'Ronald', 'role': 'Admin', 'dept': 'IT'}

Part 2: Return Values, Mutability & Type Hinting (Questions 5 to 8) 🔝

5. Question 5: Write a function get_min_max(numbers) returning both minimum and maximum as an unpacked tuple.
   View Solution

   def get_min_max(numbers):
       return min(numbers), max(numbers)
   
   low, high = get_min_max([15, 3, 89, 42, 7])
   print('Lowest: ', low)
   print('Highest:', high)

   Terminal Output:

   Lowest:  3
   Highest: 89

6. Question 6: Demonstrate early return by writing find_first_even(numbers) which halts at the first even match.
   View Solution

   def find_first_even(numbers):
       for num in numbers:
           if num % 2 == 0:
               return num  # Early exit
       return None
   
   print('First even:', find_first_even([1, 3, 7, 8, 11]))
   print('No even:   ', find_first_even([1, 3, 5]))

   Terminal Output:

   First even: 8
   No even:    None

7. Question 7: Write a pure function remove_negatives(numbers) returning a new list without mutating the original.
   View Solution

   def remove_negatives(numbers):
       return [x for x in numbers if x >= 0]
   
   raw_data = [10, -5, 20, -1, 30]
   clean_data = remove_negatives(raw_data)
   print('Original untouched:', raw_data)
   print('Cleaned output:    ', clean_data)

   Terminal Output:

   Original untouched: [10, -5, 20, -1, 30]
   Cleaned output:     [10, 20, 30]

8. Question 8: Define calculate_bmi(weight_kg, height_m) using Python type hints and a docstring.
   View Solution

   def calculate_bmi(weight_kg: float, height_m: float) -> float:
       """Calculates Body Mass Index (BMI) using weight and height."""
       return round(weight_kg / (height_m ** 2), 2)
   
   bmi = calculate_bmi(70.0, 1.75)
   print('BMI Value:  ', bmi)
   print('Docstring:  ', calculate_bmi.__doc__)

   Terminal Output:

   BMI Value:   22.86
   Docstring:   Calculates Body Mass Index (BMI) using weight and height.

Part 3: Variable Scope, Closures & Default Traps (Questions 9 to 12) 🔝

9. Question 9: Demonstrate variable shadowing where a local variable inside a function masks an outer global variable.
   View Solution

   x = 100  # Global variable
   
   def shadow_demo():
       x = 200  # Local variable shadowing global x
       print('Inside function: ', x)
   
   shadow_demo()
   print('Outside function:', x)

   Terminal Output:

   Inside function:  200
   Outside function: 100

10. Question 10: Use the global keyword to modify a module-level variable from inside a function.
    View Solution

    counter = 0
    
    def increment():
        global counter
        counter += 1
    
    increment()
    increment()
    print('Global counter:', counter)

    Terminal Output:

    Global counter: 2

11. Question 11: Use the nonlocal keyword in nested functions to modify a variable in the enclosing outer scope.
    View Solution

    def make_counter():
        count = 0
        def step():
            nonlocal count
            count += 1
            return count
        return step
    
    c = make_counter()
    print('Step 1:', c())
    print('Step 2:', c())

    Terminal Output:

    Step 1: 1
    Step 2: 2

12. Question 12: Identify the mutable default argument trap (lst=[]) and fix it using None.
    View Solution

    # Problem: lst=[] retains state across separate calls!
    # Fix: use default None and initialize inside
    def safe_append(item, target_list=None):
        if target_list is None:
            target_list = []
        target_list.append(item)
        return target_list
    
    print('Call 1:', safe_append('A'))
    print('Call 2:', safe_append('B'))

    Terminal Output:

    Call 1: ['A']
    Call 2: ['B']

Part 4: Recursion, Lambdas & Higher-Order Functions (Questions 13 to 15) 🔝

13. Question 13: Write a recursive function factorial(n) with an explicit base case and recursive step.
    View Solution

    def factorial(n):
        if n <= 1:  # Base case
            return 1
        return n * factorial(n - 1)  # Recursive step
    
    print('Factorial 5:', factorial(5))
    print('Factorial 0:', factorial(0))

    Terminal Output:

    Factorial 5: 120
    Factorial 0: 1

14. Question 14: Sort a list of student (name, score) tuples by score using an anonymous lambda function.
    View Solution

    students = [('Alex', 82), ('Sarah', 95), ('Ronald', 74), ('John', 88)]
    # Sort ascending by score (item[1])
    students.sort(key=lambda s: s[1])
    print('Sorted by score:', students)

    Terminal Output:

    Sorted by score: [('Ronald', 74), ('Alex', 82), ('John', 88), ('Sarah', 95)]

15. Question 15: Write a recursive function flatten(nested) that flattens an arbitrarily nested list structure.
    View Solution

    def flatten(nested_list):
        flat = []
        for item in nested_list:
            if isinstance(item, list):
                flat.extend(flatten(item))  # Recurse
            else:
                flat.append(item)
        return flat
    
    matrix = [1, [2, [3, 4], 5], [6, 7]]
    print('Flattened list:', flatten(matrix))

    Terminal Output:

    Flattened list: [1, 2, 3, 4, 5, 6, 7]

Interactive Notebook & Practice Exercises 🔝

Work through all 15 practice questions, explore variable scoping, and execute recursion traces in our interactive companion Jupyter Notebook:

Frequently Asked Questions (FAQ) 🔝

Further Reading & Related Tutorials 🔝

• Python User-Defined Functions (UDF) — Complete guide to defining and invoking functions.
• Python Local vs. Global Variable Scope — Understanding LEGB variable lookup rules.
• Python Recursion — Developing recursive algorithms with base cases.
• Python Lambda Functions — Anonymous single-expression function callbacks.
• Python Generators & yield — Memory-efficient stream evaluation.
• Python Built-in Functions — Comprehensive reference for all 62 built-in functions.

Subhendu Mohapatra

Author & Instructor at plus2net

I write and maintain practical tutorials on Python, PHP, SQL, JavaScript, HTML, jQuery, and web development at plus2net. The tutorials focus on clear explanations, working examples, and code that readers can test and adapt while learning.

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