PCAP Object-Oriented Programming Practice Test 9 — 15 Questions

Question 1

A class has a class attribute that is a list. A developer modifies this list via one instance, and the change is reflected in all other instances. What is the best practice to avoid this unintended sharing?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Initialize the list in `__init__` rather than as a class attribute.. Class attributes are shared across all instances. By initializing the list inside `__init__`, each instance gets its own independent list object, preventing unintended mutation from affecting other instances. This is the standard Python pattern for instance-specific mutable data.

Answer

Use a tuple instead of a list.

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Use a class method to modify the list.

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Use `deepcopy` when accessing the list.

Question 2

Which of the following correctly uses `__slots__` to restrict attribute creation to only `x` and `y`?

Accepted Answer

`class Foo: __slots__ = ['x', 'y']`. Options C and D are both correct because `__slots__` must be assigned an iterable of strings. A list `['x', 'y']` and a tuple `('x', 'y')` are both valid iterables that restrict attribute creation to exactly `x` and `y`. Option A uses a single string, which would restrict to individual characters `'x'`; Option B uses a string in parentheses without a trailing comma, which is also just a string. Both A and B would produce unexpected behavior.

Answer

`class Foo: __slots__ = 'x'`

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`class Foo: __slots__ = ('x')`

Question 3

Which TWO of the following are special methods in Python?

Accepted Answer

`__init__`. `__init__` is a predefined special method in Python used as a constructor to initialize an object's state when an instance of a class is created. It is automatically invoked by the Python runtime upon object instantiation, making it a core part of the object-oriented programming model in Python.

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`__bar__`

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`__main__`

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`__foo__`

Question 4

Which THREE of the following are true about the `__init__` method in Python?

Accepted Answer

It can be called manually.. The __init__ method is a special method in Python classes used for initializing newly created objects. It can be called manually (e.g., obj.__init__()), it accepts arguments that are passed during instance creation, and it is automatically invoked when an instance is created via the class constructor. It does not require a return value (it returns None), and it is inherited by subclasses unless explicitly overridden.

Answer

It must return a value.

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It is not inherited.

Question 5

Which THREE of the following are true about method overriding in Python?

Accepted Answer

The subclass method must have the same name.. Method overriding in Python requires the subclass method to have the same name as the parent class method. This is the fundamental rule of overriding — without the same name, the method is not overriding but rather defining a new method. The subclass method replaces the inherited method when called on an instance of the subclass.

Answer

The `@override` decorator is required.

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The subclass method can have a different number of parameters.

Question 6

A developer defines a class with an __init__ method that sets instance attributes. Which of the following is the correct way to call the parent class's __init__ from a child class?

Accepted Answer

super().__init__(arg1, arg2). `super().__init__(arg1, arg2)` is the modern, recommended way to call the parent class's `__init__` method in Python. It uses the `super()` function without arguments to automatically resolve the parent class based on the method resolution order (MRO), ensuring proper cooperative multiple inheritance and avoiding hardcoding the parent class name.

Answer

super(self, Child).__init__(arg1, arg2)

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Parent.__init__(self, arg1, arg2)

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Child.__init__(self, arg1, arg2)

Question 7

Which of the following is a correct use of the @property decorator to create a getter and setter for an attribute named 'score' that ensures score stays between 0 and 100?

Accepted Answer

@property
def score(self): return self._score
@score.setter
def score(self, value): if 0 <= value <= 100: self._score = value. It uses the @property decorator to define a getter method that returns the private attribute `self._score`, and a setter method that validates the new value is between 0 and 100 before assigning it to `self._score`. This ensures encapsulation and data validation, which is the intended use of properties in Python.

Answer

@property
def _score(self): return self.score
@_score.setter
def _score(self, value): self.score = value

Answer

@property
def score(self): return self.score
@score.setter
def score(self, value): self.score = value

Answer

def get_score(self): return self._score
def set_score(self, value): self._score = value
score = property(get_score, set_score)

Question 8

Refer to the exhibit. What is the output when this code is executed?

Accepted Answer

AttributeError. The code attempts to access the attribute `balance` on an instance of `BankAccount`, but the class uses `__balance` (double underscore) in the `__init__` method, which triggers Python's name mangling. The attribute is actually stored as `_BankAccount__balance`. Therefore, `balance` does not exist on the instance, and accessing it raises an `AttributeError`. In Python, accessing a non-existent attribute raises an error rather than returning a default value.

Answer

0

Answer

None

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100

Question 9

Refer to the exhibit. What is the output and why?

Accepted Answer

2. The code defines a class `A` with a class attribute `counter` set to 0, and an `__init__` method that increments `A.counter` (the class attribute) by 1 each time an instance is created. Creating two instances (`a1` and `a2`) increments the class attribute twice, so `A.counter` becomes 2. The `print(A.counter)` statement outputs the class attribute value, which is 2.

Answer

AttributeError

Answer

1

Answer

3

Question 10

A developer creates a metaclass 'Meta' that modifies class creation by adding a class attribute 'created_by' set to 'Meta'. Which code snippet correctly defines and uses this metaclass?

Accepted Answer

class Meta(type): def __new__(cls, name, bases, dct): dct['created_by']='Meta'; return super().__new__(cls, name, bases, dct). It defines a proper metaclass by subclassing `type` and overriding `__new__`, which is the correct method for modifying the class dictionary before the class is created. The `__new__` method must return the result of `super().__new__(cls, name, bases, dct)` to actually create the class object. Adding `dct['created_by']='Meta'` inside `__new__` ensures the attribute is set during class creation.

Answer

class Meta(type): def __new__(cls, name, bases, dct): dct['created_by']='Meta'

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class Meta(type): def __init__(cls, name, bases, dct): dct['created_by']='Meta'

Answer

def Meta(name, bases, dct): dct['created_by']='Meta'; return type(name, bases, dct)

Question 11

A developer wants a class 'LoggedDict' that behaves like a dict but logs all attribute access in the console. Which method override correctly implements this for getting an attribute?

Accepted Answer

def __getattribute__(self, name): print(f'Access {name}'); return super().__getattribute__(name). `__getattribute__` is the universal method called for every attribute access on an object. By overriding it, the developer can log the attribute name before delegating to the superclass implementation via `super().__getattribute__(name)`, which preserves the normal attribute lookup chain. This ensures that all attribute accesses (including those that exist and those that don't) are logged, which is the requirement for 'LoggedDict'.

Answer

def __get__(self, instance, owner): print(f'Access'); return self

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def __getattr__(self, name): print(f'Access {name}'); return self.__dict__[name]

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def __getitem__(self, key): print(f'Access {key}'); return dict.__getitem__(self, key)

Question 12

A development team is building a real-time chat application using Python. The application uses a class 'ChatRoom' that maintains a list of 'User' objects as active participants. Each User object holds a reference back to its ChatRoom to send messages. Over time, the application runs out of memory. Profiling reveals that User objects are not being garbage collected even after users disconnect. The team suspects circular references. Which solution would effectively resolve the memory leak without breaking the functionality?

Accepted Answer

Use weakref.WeakSet for the participants list in ChatRoom, so that when a User is no longer referenced elsewhere, it is automatically removed. Using a `weakref.WeakSet` for the participants list in `ChatRoom` means the `ChatRoom` holds only weak references to `User` objects. When a user disconnects and all external references to that `User` are removed, the `User` object becomes unreachable and can be garbage collected, even though the `User` still holds a strong reference back to the `ChatRoom`. This breaks the circular reference without requiring manual intervention or altering the `User`-to-`ChatRoom` relationship.

Answer

Increase the Python heap size using PYTHON_MALLOC_DEBUG to avoid memory issues

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Store the ChatRoom reference in User using a weakref.ref, so that the cycle is broken

Answer

Manually call gc.collect() every time a user disconnects

Question 13

A junior developer writes a class 'Logger' that should only ever have one instance (singleton). They attempt to implement it by overriding __new__ to always return the same instance. However, when multiple threads attempt to create a Logger, they sometimes get different instances. Which modification will make the singleton thread-safe?

Accepted Answer

Use a lock (threading.Lock) in __new__ to serialize access. The race condition occurs when multiple threads simultaneously check `cls._instance` and find it `None`, then both proceed to create a new instance. Wrapping the creation logic inside a `threading.Lock` in `__new__` ensures that only one thread can execute the critical section at a time, guaranteeing that only one instance is ever created.

Answer

Use a class method get_instance() that checks a class variable and creates the instance if needed, and call that from __init__

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Use a metaclass that overrides __call__ to return the singleton

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Override __init__ to check if the instance was already initialized and if so, skip initialization

Question 14

Which three statements about the Method Resolution Order (MRO) in Python are true? (Choose three.)

Accepted Answer

The MRO can be viewed using the __mro__ attribute.. Every Python class has an `__mro__` attribute that returns a tuple of classes in the order they are searched for methods and attributes. This attribute is automatically generated by the C3 linearization algorithm and provides a clear, inspectable view of the resolution order.

Answer

The MRO is only used for methods, not attributes.

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The MRO can be changed by modifying the class hierarchy at runtime.

Question 15

A junior developer wrote a class representing a bank account with a private attribute balance. They used double underscore prefix (__balance) to make it private. However, in a test script, they are still able to access the attribute using the mangled name _Account__balance. The developer is confused about why encapsulation is not enforced. Which statement best explains this behavior?

Accepted Answer

Python's name mangling is only a convention and does not prevent access.. Python's name mangling (triggered by a double underscore prefix) is not a security mechanism but a syntactic transformation that renames the attribute to _ClassName__attribute. This prevents accidental name clashes in subclasses but does not enforce true encapsulation; the attribute can still be accessed via the mangled name from outside the class. The developer's confusion stems from mistaking name mangling for a privacy guarantee, which Python intentionally does not provide.

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The double underscore prefix actually makes the attribute completely inaccessible from outside the class.

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The developer forgot to use the @property decorator.

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The test script must have used a different class attribute name.