Python Functions Deep Dive Practice

Practise default and keyword arguments, *args and **kwargs, returning several values, scope, lambda functions and recursion.

Intermediate10 problemsUpdated October 23, 2026

Review first: Parameters, Arguments, Return Values, Scope, Lambda Functions, Recursion

1.Default and keyword arguments
Intermediate
Write greet(name, greeting="Hello", punctuation="!") that returns a greeting string. Call it as greet("Asha"), greet("Ravi", "Welcome") and greet("Meera", punctuation="?").
Show hint
Parameters with defaults go after the ones without. A keyword argument lets you skip over greeting.
Show solution
Python
def greet(name, greeting="Hello", punctuation="!"): return f"{greeting}, {name}{punctuation}" print(greet("Asha")) print(greet("Ravi", "Welcome")) print(greet("Meera", punctuation="?"))
Output
Hello, Asha! Welcome, Ravi! Hello, Meera?
2.Average of any number of values
Intermediate
Write average(*numbers) that returns the average of any number of arguments, or None if it is called with none. Print average(4, 8, 6), average(10) and average().
Show hint
*numbers collects the arguments into a tuple. An empty tuple is falsy.
Show solution
Python
def average(*numbers): if not numbers: return None return sum(numbers) / len(numbers) print(average(4, 8, 6)) print(average(10)) print(average())
Output
6.0 10.0 None
3.Build a profile with **kwargs
Intermediate
Write profile(name, **details) that prints the name, then each extra detail as - key: value. Call it with profile("Asha", city="Pune", role="Analyst", years=3).
Show hint
**details collects keyword arguments into a dictionary.
Show solution
Python
def profile(name, **details): print(name) for key, value in details.items(): print(f"- {key}: {value}") profile("Asha", city="Pune", role="Analyst", years=3)
Output
Asha - city: Pune - role: Analyst - years: 3
4.Return several values
Intermediate
Write stats(values) that returns the smallest value, the largest value and the average (rounded to 2 decimals) in one return. Unpack the result of stats([12, 7, 21, 9]) into three variables and print them.
Show hint
return a, b, c returns a tuple, which you can unpack with low, high, avg = stats(...).
Show solution
Python
def stats(values): return min(values), max(values), round(sum(values) / len(values), 2) low, high, avg = stats([12, 7, 21, 9]) print(low, high, avg) print(stats([12, 7, 21, 9]))
Output
7 21 12.25 (7, 21, 12.25)

5.Predict the scope

Intermediate

What does this print? Work it out first, then run it.

Python

count = 10

def change():
    count = 99
    print("inside:", count)

def change_global():
    global count
    count = 50

change()
print("after change:", count)
change_global()
print("after change_global:", count)

Show hint

Assigning to a name inside a function creates a new local variable, unless the name is declared global.

Show solution

Python

count = 10

def change():
    count = 99
    print("inside:", count)

def change_global():
    global count
    count = 50

change()
print("after change:", count)
change_global()
print("after change_global:", count)

Output

inside: 99
after change: 10
after change_global: 50

change() creates its own local count, so the global one stays 10. change_global() declares global count, so it changes the module-level variable. In real code, prefer returning a value over changing globals.

6.Sort with a lambda
Intermediate
Sort students = [("Asha", 88), ("Ravi", 95), ("Meera", 88), ("John", 72)] by score from highest to lowest, with ties sorted alphabetically by name, and print the result.
Show hint
key=lambda s: (-s[1], s[0]) sorts by the negative score first, then by the name.
Show solution
Python
students = [("Asha", 88), ("Ravi", 95), ("Meera", 88), ("John", 72)] ranked = sorted(students, key=lambda s: (-s[1], s[0])) for name, score in ranked: print(name, score)
Output
Ravi 95 Asha 88 Meera 88 John 72
7.filter and map
Intermediate
From prices = [120, 45, 300, 80, 15], keep the prices over 50 and add 18% tax to each, rounded to 2 decimals. Use filter and map with lambdas, then the same with a list comprehension.
Show hint
filter(lambda p: p > 50, prices) keeps items; map(lambda p: ..., items) transforms them. Wrap the result in list() to see it.
Show solution
Python
prices = [120, 45, 300, 80, 15] with_tax = list(map(lambda p: round(p * 1.18, 2), filter(lambda p: p > 50, prices))) print(with_tax) same = [round(p * 1.18, 2) for p in prices if p > 50] print(same)
Output
[141.6, 354.0, 94.4] [141.6, 354.0, 94.4]
Both give the same result. Most Python programmers find the list comprehension easier to read.
8.Sum of digits, recursively
Intermediate
Write a recursive function digit_sum(n) that adds up the digits of a non-negative integer, so digit_sum(4096) is 4 + 0 + 9 + 6 = 19. Print digit_sum(4096) and digit_sum(7).
Show hint
The base case is a single digit (n < 10). Otherwise, the last digit is n % 10 and the rest of the number is n // 10.
Show solution
Python
def digit_sum(n): if n < 10: return n return n % 10 + digit_sum(n // 10) print(digit_sum(4096)) print(digit_sum(7))
Output
19 7
9.Flatten a nested list
Intermediate
Write a recursive function flatten(items) that turns [1, [2, 3], [4, [5, [6]]], 7] into [1, 2, 3, 4, 5, 6, 7].
Show hint
For each item, if it is a list, extend the result with flatten(item); otherwise append it.
Show solution
Python
def flatten(items): result = [] for item in items: if isinstance(item, list): result.extend(flatten(item)) else: result.append(item) return result print(flatten([1, [2, 3], [4, [5, [6]]], 7]))
Output
[1, 2, 3, 4, 5, 6, 7]
Recursion is a natural fit here because the data itself is nested to an unknown depth.

10.The mutable default trap

Intermediate

This function is meant to start a new list on every call, but it has a bug. Predict the output, then fix it.

Python

def add_item(item, basket=[]):
    basket.append(item)
    return basket

print(add_item("apple"))
print(add_item("bread"))

Show hint

A default value is created once, when the function is defined, not on every call.

Show solution

Python

def add_item_buggy(item, basket=[]):
    basket.append(item)
    return basket

print(add_item_buggy("apple"))
print(add_item_buggy("bread"))  # the same list is reused!


def add_item(item, basket=None):
    if basket is None:
        basket = []
    basket.append(item)
    return basket

print(add_item("apple"))
print(add_item("bread"))

Output

['apple']
['apple', 'bread']
['apple']
['bread']

Never use a mutable value (a list, dictionary or set) as a default argument. Use None and create the new object inside the function.

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