PCAP Practice Test 2 — 10 Questions

Question 1

When importing a module, Python searches for it in a specific order. Which of the following lists the correct order of directories searched?

Accepted Answer

[current directory] then PYTHONPATH then site-packages. When Python imports a module, it first searches the directory containing the input script (or current working directory), then iterates through the directories listed in the PYTHONPATH environment variable, and finally checks installation-dependent default paths such as site-packages. This order is reflected in sys.path, which is built from the script directory, PYTHONPATH entries, and default site-packages. Option B accurately lists this sequence: current directory, then PYTHONPATH, then site-packages.

Answer

PYTHONPATH then sys.path

Answer

sys.path + [current directory]

Answer

[current directory] + sys.path

Question 2

Which THREE of the following are valid ways to import a function named 'calculate' from a module named 'math_ops' located in a subpackage 'operations' of a package 'app'?

Accepted Answer

from app.operations.math_ops import calculate. It uses the standard Python import syntax to directly import the 'calculate' function from the 'math_ops' module, which is located in the 'operations' subpackage of the 'app' package. This is the most straightforward and recommended way to import a specific attribute from a module.

Answer

import app.operations.math_ops.calculate

Answer

from app.import operations.math_ops import calculate

Question 3

You are working on a legacy system that processes financial transactions. The system uses a class hierarchy: Transaction (base), Deposit, Withdrawal, Transfer. Each subclass overrides a method 'process()' to handle its specific logic. The code often runs in a multi-threaded environment and you notice intermittent errors where a transaction is processed twice. The logging shows that the same transaction object is being passed to the process method multiple times. The transaction objects are created from a factory function that caches recently used transactions. The errors seem to occur when two threads call the factory at the same time with the same parameters. After investigating, you find that the factory uses a class-level dictionary to cache objects. Which of the following is the most appropriate solution to prevent double processing?

Accepted Answer

Make the process() method idempotent by checking if the transaction has already been applied to the account (e.g., check balance changes). The core issue is that the same transaction object can be processed multiple times in a multi-threaded environment, even if the factory is fixed. Making process() idempotent by checking whether the transaction has already been applied (e.g., verifying account balance changes) ensures that repeated calls with the same object do not cause duplicate financial effects, directly addressing the symptom of double processing regardless of how the object is cached or retrieved.

Answer

Add a lock around the cache lookup and creation in the factory function

Answer

Add a flag to each transaction object to indicate if it has been processed, and check it at the start of process()

Answer

Remove the caching mechanism from the factory function to ensure new objects are always created

Question 4

A developer uses the .index() method on a string to find the position of a substring. If the substring is not found, what exception is raised?

Accepted Answer

ValueError. The `.index()` method on a string raises a `ValueError` when the specified substring is not found. This is because `ValueError` is the standard Python exception for cases where a function receives an argument with the correct type but an inappropriate value, such as a substring that does not exist in the target string.

Answer

KeyError

Answer

IndexError

Answer

TypeError

Question 5

A programmer wants to restrict a class to only allow specific attribute names and reduce memory usage. Which feature should they use?

Accepted Answer

Define `__slots__` as a tuple of allowed attribute names.. Defining `__slots__` as a tuple of allowed attribute names restricts the class to only those attributes, preventing the creation of a per-instance `__dict__` and thereby reducing memory usage. This is a built-in Python mechanism that overrides the default dynamic attribute storage, making it ideal for memory-constrained applications.

Answer

Override `__init_subclass__` to enforce restrictions.

Answer

Use @property for every attribute.

Answer

Define `__dict__` as a class variable.

Question 6

Which THREE of the following statements about Python's 'with' statement are true? (Select exactly 3)

Accepted Answer

It can be used with any object that implements __enter__ and __exit__ methods.. Option A is correct because the context manager protocol is defined precisely by the presence of __enter__ and __exit__ methods, so any object implementing both can be used with 'with'. Option B is correct because the 'with' statement's semantics ensure __exit__ is invoked when the block exits, whether normally or via an exception, which is the core guarantee of the protocol. Option C is correct because Python supports 'with A() as a, B() as b:' syntax, allowing multiple context managers separated by commas (equivalent to nested with statements). Option D is not marked correct because while 'with' often replaces try/finally for resource cleanup, it does not eliminate the need for try/finally in all cases, such as when no context manager exists or when cleanup logic must run without one. Option E is not marked correct because 'with' works with any context manager, not only file objects; files are just a common example.

Answer

It eliminates the need for try/finally blocks for resource management.

Answer

It can only be used with file objects.

Question 7

A developer needs to combine a list of 10,000 strings into a single string. Which approach is most efficient in terms of memory and performance?

Accepted Answer

Use ''.join(string_list). The `''.join(string_list)` method is the most efficient because it pre-allocates memory for the final string by first calculating the total length of all strings in the list, then building the result in a single pass. This avoids the quadratic time complexity and repeated memory reallocations caused by string immutability in Python when using `+=` in a loop.

Answer

Use a loop with str += to concatenate each string

Answer

Use str.replace() to merge the strings

Answer

Use str.format() to build the string step by step

Question 8

A team is developing a large application and wants to organize code into packages. Which of the following is a best practice for package design?

Accepted Answer

Use absolute imports with the package name to prevent breakage when the package is moved. Using absolute imports with the full package name (e.g., `from package.module import something`) ensures that the import path is explicit and independent of the module's location within the package. This prevents breakage when the package is moved or installed in a different location, as the import references the top-level package name rather than a relative path that may change. Absolute imports are the recommended style in PEP 8 for clarity and maintainability in larger applications.

Answer

Use relative imports inside the package to avoid hardcoding the package name

Answer

Keep all modules in a single package for simplicity

Answer

Avoid using __init__.py to keep packages lightweight

Question 9

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 10

A developer notices that a custom package 'mypackage' is not being found when importing, even though it is installed in the site-packages directory. The developer suspects a conflict with another package of the same name. Which command should the developer run to diagnose the location from which Python is importing the package?

Accepted Answer

print(mypackage.__file__). `mypackage.__file__` returns the filesystem path from which the module was loaded, allowing the developer to see exactly which `mypackage` Python is using. This directly reveals if the wrong package (e.g., from a different location or a conflicting installation) is being imported instead of the intended one.

Answer

print(mypackage)

Answer

print(__file__)

Answer

import os; print(os.getcwd())