Welcome to the Python Abstraction and Encapsulation MCQs! Abstraction and encapsulation are basic ideas in object-oriented programming (OOP) that promote code group, reusability, and safety. Abstraction includes hiding pointless particulars and displaying solely important options of an object, whereas encapsulation includes bundling the information and strategies that function on the information right into a single unit. These questions will take a look at your understanding of those ideas in Python, together with how you can create summary lessons, implement encapsulation, and leverage these ideas for environment friendly code design. Every query is multiple-choice, with just one right reply. Take your time to fastidiously learn every query and select the best choice. Let’s delve into the world of Python abstraction and encapsulation collectively!
30+ MCQs on Python Abstraction and Encapsulation
Q1. What’s Abstraction in Python?
a) Abstraction is the method of hiding the implementation particulars and displaying solely the mandatory options of an object.
b) Abstraction is the method of exposing all of the implementation particulars of an object.
c) Abstraction is the method of making a number of objects from a single class.
d) Abstraction is the method of defining a brand new class from an present class.
Reply: a
Rationalization: Abstraction in Python permits programmers to cover the implementation particulars and present solely the mandatory options of an object to the skin world.
Q2. What’s Encapsulation in Python?
a) Encapsulation is the method of exposing all of the implementation particulars of an object.
b) Encapsulation is the method of mixing information and capabilities right into a single unit referred to as a category.
c) Encapsulation is the method of making a number of objects from a single class.
d) Encapsulation is the method of defining a brand new class from an present class.
Reply: b
Rationalization: Encapsulation in Python is the bundling of knowledge and the strategies that function on that information right into a single unit referred to as a category. It helps in hiding the implementation particulars of an object.
Q3. Which of the next is a bonus of Abstraction?
a) It will increase code reusability
b) It makes this system run sooner
c) It makes the code extra advanced
d) It reduces the necessity for code group
Reply: a
Rationalization: Abstraction will increase code reusability by permitting programmers to reuse the abstracted class or object with out worrying about its implementation particulars.
This fall. Which of the next is a bonus of Encapsulation?
a) It reduces code reusability
b) It makes this system run slower
c) It makes the code much less versatile
d) It prevents information from being accessed by unauthorized code
Reply: d
Rationalization: In Python, encapsulation is used to cover the implementation particulars of an object and to guard the information from unauthorized entry. It improves safety and makes the code extra strong.
Q5. In Python, how do you create an summary class?
a) By utilizing the summary key phrase
b) By utilizing the abstractmethod decorator from the abc module
c) By utilizing the summary methodology from the abc module
d) By inheriting from the summary class
Reply: b
Rationalization: In Python, summary lessons are created utilizing the abstractmethod decorator from the abc (Summary Base Lessons) module.
Q6. Which of the next is true about summary strategies in Python?
a) Summary strategies have a physique and should be applied within the derived class
b) Summary strategies haven’t any physique and should be applied within the derived class
c) Summary strategies can’t be overridden within the derived class
d) Summary strategies are elective to implement within the derived class
Reply: b
Rationalization: Summary strategies in Python haven’t any physique and require implementation within the derived (youngster) class. They characterize a technique within the mother or father class that each one youngster lessons should implement.
Q7. What’s the function of Encapsulation in Python?
a) To make this system run sooner
b) To cover the implementation particulars of an object
c) To create a number of objects from a single class
d) To outline a brand new class from an present class
Reply: b
Rationalization: In Python, encapsulation is used to cover the implementation particulars of an object and to guard the information from unauthorized entry.
Q8. Which key phrase is used to outline a protected variable in Python?
a) personal
b) defend
c) __private
d) _
Reply: d
Rationalization: In Python, protected variables are outlined utilizing a single underscore _ prefix.
Q9. What does it imply for a variable or methodology to be personal in Python?
a) It can’t be accessed from outdoors the category
b) It will possibly solely be accessed from outdoors the category
c) It’s accessible from any class
d) It’s accessible solely throughout the similar module
Reply: a
Rationalization: Non-public variables or strategies in Python can’t be accessed from outdoors the category. They’re solely accessible throughout the class itself.
Q10. What’s the good thing about utilizing Encapsulation in Python?
a) It will increase the complexity of the code
b) It makes code much less safe
c) It permits for higher management over class attributes and strategies
d) It makes code much less organized
Reply: c
Rationalization: Encapsulation in Python permits for higher management over class attributes and strategies, resulting in improved safety and maintainability of the code.
Q11. Which of the next is true about Abstraction in Python?
a) It exposes all of the implementation particulars of an object
b) It hides the implementation particulars and exhibits solely the mandatory options of an object
c) It’s not associated to lessons and objects
d) It makes this system run slower
Reply: b
Rationalization: Abstraction in Python hides the implementation particulars of an object and exhibits solely the mandatory options to the skin world, bettering readability and decreasing complexity.
Q12. What’s the function of the getter methodology in Python Encapsulation?
a) To set the worth of a non-public variable
b) To get the worth of a non-public variable
c) To delete a non-public variable
d) To outline a non-public variable
Reply: b
Rationalization: A getter methodology in Python Encapsulation is used to get the worth of a non-public variable, permitting managed entry to the variable from outdoors the category.
Q13. Which of the next finest describes Encapsulation in Python?
a) Combining information and capabilities right into a single unit referred to as a category
b) Exposing all of the implementation particulars of an object
c) Creating a number of objects from a single class
d) Defining a brand new class from an present class
Reply: a
Rationalization: Encapsulation in Python includes combining information and capabilities right into a single unit referred to as a category, permitting for higher group and modularity within the code.
Q14. What’s the function of a setter methodology in Python Encapsulation?
a) To set the worth of a non-public variable
b) To get the worth of a non-public variable
c) To delete a non-public variable
d) To outline a non-public variable
Reply: a
Rationalization: A setter methodology in Python Encapsulation is used to set the worth of a non-public variable, offering managed entry and validation for the variable.
Q15. Which of the next is true about Abstraction in Python?
a) It will increase code complexity
b) It reduces code reusability
c) It helps in code group and administration
d) It exposes all of the implementation particulars
Reply: c
Rationalization: Abstraction in Python helps in code group and administration by hiding the implementation particulars and displaying solely the mandatory options of an object.
Q16. Which key phrase defines a non-public methodology in Python?
a) personal
b) defend
c) __private
d) __
Reply: d
Rationalization: In Python, personal strategies are outlined utilizing a double underscore __ prefix.
Q17. Think about the next Python code:
class Circle:
def __init__(self, radius):
self.__radius = radius
def get_radius(self):
return self.__radius
def set_radius(self, radius):
if radius > 0:
self.__radius = radius
# Create an occasion of the Circle class
c = Circle(5)
# Change the radius to 10
c.set_radius(10)
# Get the brand new radius
print(c.get_radius())
What would be the output of this code?
a) 5
b) 10
c) 15
d) Error: Can not entry personal attribute __radius
Reply: b
Rationalization: The set_radius methodology is used to alter the radius to 10, after which get_radius methodology is used to get the up to date radius, which is 10.
Q18. Think about the next Python code:
class BankAccount:
def __init__(self, stability=0):
self.__balance = stability
def deposit(self, quantity):
if quantity > 0:
self.__balance += quantity
def withdraw(self, quantity):
if quantity > 0 and quantity <= self.__balance:
self.__balance -= quantity
return quantity
else:
return "Inadequate funds"
def get_balance(self):
return self.__balance
# Create an occasion of BankAccount
acc = BankAccount(100)
# Deposit $50
acc.deposit(50)
# Withdraw $70
print(acc.withdraw(70))
# Get the present stability
print(acc.get_balance())
What would be the output of this code?
a) 70, 80
b) 70, 50
c) 50, 80
d) Inadequate funds, 80
Reply: a
Rationalization: Initially, the stability is 100. After depositing 50, the stability turns into 150. After withdrawing 70, the output of withdraw(70) is 70, and the present stability is 80.
Q19. Think about the next Python code:
class Particular person:
def __init__(self, title, age):
self.__name = title
self.__age = age
def get_name(self):
return self.__name
def set_name(self, title):
self.__name = title
def get_age(self):
return self.__age
def set_age(self, age):
self.__age = age
# Create an inventory of Particular person objects
individuals = [Person("Alice", 30), Person("Bob", 25), Person("Charlie", 35)]
# Print the names of individuals over 30 years previous
for individual in individuals:
if individual.get_age() > 30:
print(individual.get_name())
What occurs when this code executes?
a) Alice, Bob, Charlie
b) Alice, Charlie
c) Bob, Charlie
d) Alice
Reply: c
Rationalization: The code iterates by the record of Particular person objects and prints the names of these with an age over 30. Solely Bob and Charlie meet this situation, so their names are printed.
Q20. Think about the next Python code:
class Worker:
def __init__(self, title, wage):
self.__name = title
self.__salary = wage
def get_name(self):
return self.__name
def get_salary(self):
return self.__salary
def set_salary(self, wage):
if wage > 0:
self.__salary = wage
# Create an Worker object
emp = Worker("John", 50000)
# Set a brand new wage
emp.set_salary(60000)
# Attempt to straight entry the personal attribute __salary
print(emp.__salary)
What’s going to occur when this code is executed?
a) The brand new wage 60000 might be printed
b) The previous wage 50000 might be printed
c) Error: AttributeError: ‘Worker’ object has no attribute ‘__salary’
d) Error: TypeError: ‘Worker’ object just isn’t subscriptable
Reply: c
Rationalization: Making an attempt to straight entry a non-public attribute __salary outdoors of the category will end in an AttributeError.
Q21. Think about the next Python code:
class Rectangle:
def __init__(self, size, width):
self.__length = size
self.__width = width
def space(self):
return self.__length * self.__width
# Create a Rectangle object
rect = Rectangle(5, 10)
# Get the realm
print(rect.space())
# Attempt to straight entry the personal attribute __length
print(rect.__length)
What occurs when this code executes?
a) The world 50 might be printed, adopted by an error
b) The world 50 might be printed, adopted by the worth of __length
c) Error: AttributeError: ‘Rectangle’ object has no attribute ‘__length’
d) Error: TypeError: ‘Rectangle’ object just isn’t subscriptable
Reply: a
Rationalization: The code will print the realm, which is 50. Nevertheless, making an attempt to straight entry a non-public attribute __length outdoors of the category will end in an AttributeError.
Q22. Think about the next Python code:
class E-book:
def __init__(self, title, writer):
self.__title = title
self.__author = writer
def get_title(self):
return self.__title
def get_author(self):
return self.__author
# Create a E-book object
guide = E-book("Python Programming", "John Doe")
# Attempt to change the title
guide.__title = "New Title"
# Print the title and writer
print(guide.get_title())
print(guide.get_author())
What might be printed when this code is executed?
a) Python Programming, John Doe
b) New Title, John Doe
c) Error: AttributeError: ‘E-book’ object has no attribute ‘__title’
d) Error: TypeError: ‘E-book’ object just isn’t subscriptable
Reply: a
Rationalization: The try to alter __title straight with guide.__title = "New Title" creates a brand new occasion variable, but it surely doesn’t change the personal __title attribute outlined within the class. So when get_title() is named, it returns the unique title “Python Programming”.
Q23. Think about the next Python code:
class Automobile:
def __init__(self, make, mannequin):
self.__make = make
self.__model = mannequin
def get_make(self):
return self.__make
def get_model(self):
return self.__model
# Create a Automobile object
automobile = Automobile("Toyota", "Camry")
# Print the make and mannequin
print(automobile.get_make())
print(automobile.get_model())
# Attempt to change the make
automobile.__make = "Honda"
# Print the make once more
print(automobile.get_make())
What might be printed when this code is executed?
a) Toyota, Camry, Honda
b) Toyota, Camry, Toyota
c) Error: AttributeError: ‘Automobile’ object has no attribute ‘__make’
d) Error: TypeError: ‘Automobile’ object just isn’t subscriptable
Reply: a
Rationalization: The try to alter __make straight with automobile.__make = "Honda" creates a brand new occasion variable, but it surely doesn’t change the personal __make attribute outlined within the class. So when get_make() is named, it returns the unique make “Toyota”.
Q24. Which of the next is NOT a good thing about utilizing Abstraction and Encapsulation?
a) Improved code maintainability
b) Enhanced safety
c) Elevated code complexity
d) Higher code group
Reply: c
Rationalization: Elevated code complexity just isn’t a good thing about Abstraction and Encapsulation. These ideas are designed to simplify code by hiding pointless particulars.
Q25. Which of the next is an instance of Abstraction in Python?
a) Utilizing a for loop to iterate over an inventory
b) Defining a perform with parameters and a return worth
c) Instantiating an object from a category and calling its strategies
d) Declaring a non-public class attribute with a __ prefix
Reply: c
Rationalization: Instantiating an object from a category and calling its strategies is an instance of Abstraction, because it hides the interior implementation of the category.
Q26. In Python, what’s the significance of utilizing title mangling with double underscore (__) for attributes?
a) It makes attributes accessible from outdoors the category
b) It hides attributes from throughout the class
c) It prevents attribute modification from outdoors the category
d) It permits subclass strategies to entry mother or father class attributes
Reply: b
Rationalization: Identify mangling with double underscore (__) in Python is used to make attributes personal, hiding them from outdoors the category.
Q27. Which assertion finest describes the connection between Encapsulation and Info Hiding?
a) Encapsulation is similar as Info Hiding
b) Encapsulation is a broader idea that features Info Hiding
c) Info Hiding is a safer type of Encapsulation
d) Info Hiding is a design precept, whereas Encapsulation is a programming approach
Reply: b
Rationalization: Encapsulation is a broader idea that features Info Hiding, because it includes bundling information and strategies collectively, and controlling entry to them.
Q28. Why do programmers suggest utilizing getter and setter strategies for personal attributes in Python?
a) To make the code extra advanced
b) To supply a constant method to entry and modify attributes
c) To keep away from utilizing personal attributes altogether
d) To straight entry personal attributes for effectivity
Reply: b
Rationalization: Getter and setter strategies present a managed method to entry and modify personal attributes, imposing encapsulation and making certain information integrity.
Q29. Think about the next Python code:
class Scholar:
def __init__(self, title, age):
self.__name = title
self.__age = age
def get_name(self):
return self.__name
def get_age(self):
return self.__age
# Create a Scholar object
pupil = Scholar("Alice", 20)
# Try and entry a non-public attribute straight
print(pupil.__name)
What error happens when executing this code?
a) AttributeError: ‘Scholar’ object has no attribute ‘__name’
b) TypeError: ‘Scholar’ object just isn’t subscriptable
c) SyntaxError: invalid syntax
d) No error, it can print “Alice”
Reply: a
Rationalization: Making an attempt to straight entry a non-public attribute __name outdoors of the category will end in an AttributeError since personal attributes can’t be accessed straight from outdoors the category.
Q30. Which of the next code snippets accurately defines a Python class referred to as Particular person with an __init__ methodology to initialize title and age attributes?
a)
class Particular person:
def __init__(self, title, age):
self.title = title
self.age = age
b)class Particular person:
def __init__(self, title, age):
title = title
age = age
c)
class Particular person:
def __init__(self, title, age):
self.title = title
age = age
d)
class Particular person:
def __init__(self, title, age):
self.title = title
self.__age = age
Reply: a
Rationalization: Possibility (a) accurately defines the Particular person class with self.title and self.age attributes initialized within the __init__ methodology.
Q31. What’s going to the next code snippet output?
class Circle:
def __init__(self, radius):
self.radius = radius
def get_area(self):
return 3.14 * self.radius ** 2
c = Circle(5)
print(c.get_area())
a) 78.5
b) 314
c) 25
d) Error: ‘Circle’ object has no attribute ‘get_area’
Reply: a
Rationalization: The get_area methodology calculates the realm of the circle primarily based on the given radius (5), which is 78.5.
Q32. What does the next code snippet do?
class Rectangle:
def __init__(self, width, top):
self.width = width
self.top = top
def get_area(self):
return self.width * self.top
r = Rectangle(4, 5)
print(r.get_area())
a) Calculates the perimeter of a rectangle with width 4 and top 5
b) Calculates the realm of a rectangle with width 4 and top 5
c) Prints the string illustration of the Rectangle object
d) Raises an error as a result of there isn’t a __init__ methodology
Reply: b
Rationalization: The get_area methodology calculates the realm of the rectangle primarily based on the given width (4) and top (5), which is 20.
Congratulations on finishing the Python Abstraction and Encapsulation MCQs! Abstraction and encapsulation are important ideas in OOP that assist in designing maintainable, scalable, and safe code. By mastering these ideas, you acquire the power to create clear and concise class buildings, conceal implementation particulars, and defend information integrity. Hold working towards and exploring Python’s abstraction and encapsulation functionalities to develop into proficient in designing strong and environment friendly functions. If in case you have any questions or wish to delve deeper into any matter, don’t hesitate to proceed your studying journey. Joyful coding!
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