PCAP Practice Exam 4 — 20 Questions

Question 1

Refer to the exhibit. A developer ran the script and saw the above traceback. The intended behavior was to load a JSON configuration file, and if the file is missing, create a default config. What is the most likely root cause of the second exception (NameError)?

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

Accepted Answer

The script did not import the json module.. The traceback shows a NameError for 'json.loads', which indicates that the name 'json' is not defined in the current namespace. This occurs when the script attempts to call json.loads() without first importing the json module. The intended behavior of loading a JSON configuration file requires the json module to parse the file content, and its absence causes the NameError exception.

Answer

The variable 'f' was not defined due to the FileNotFoundError.

Answer

The config.json file exists but is empty.

Answer

The file was opened in binary mode instead of text mode.

Question 2

Consider a class `D` that inherits from multiple base classes `B` and `C`. The developer wants to call a method from a specific parent class while ensuring correct method resolution order (MRO). Which is the safest way?

Accepted Answer

`super().method()`. In Python, `super().method()` is the safest way to call a method from a parent class in a multiple inheritance scenario because it respects the Method Resolution Order (MRO) defined by the C3 linearization algorithm. This ensures that the method is resolved from the next class in the MRO, avoiding hard-coded references that could break if the inheritance hierarchy changes. It also correctly handles cooperative multiple inheritance, where each class in the MRO can collaborate via `super()` calls.

Answer

`self.method()`

Answer

`ParentClass.method(self)`

Answer

`BaseClass.method(self)`

Question 3

A developer installs a third-party package using pip, but when they try to import it in their script, Python raises a ModuleNotFoundError. The package is definitely installed (pip list shows it). What is the most likely cause?

Accepted Answer

The Python interpreter being used is different from the one where the package was installed.. When a package is installed via pip, it is placed into the site-packages directory of a specific Python interpreter. If the developer runs their script with a different Python interpreter (e.g., one from a virtual environment, a different version, or a system Python vs. a user-installed Python), that interpreter's import system will not search the site-packages where the package was installed, resulting in a ModuleNotFoundError even though pip list shows the package. This is the most common cause of such a mismatch.

Answer

The package name contains a hyphen.

Answer

The script is in a directory that shadows the package name.

Answer

The package does not have an __init__.py file.

Question 4

A developer is creating a custom exception hierarchy for a library. The base exception is `LibraryError`. Which definition ensures that subclasses can be caught using the parent exception, but also allows distinguishing between different error types?

Accepted Answer

class LibraryError(Exception): pass
class FileError(LibraryError): pass
class ParseError(LibraryError): pass. It defines `LibraryError` as a subclass of `Exception`, which is the proper base class for all user-defined exceptions in Python. Subclasses `FileError` and `ParseError` inherit from `LibraryError`, so they can be caught with `except LibraryError` while still being distinguishable by their own type. This follows the standard Python exception hierarchy, where custom exceptions should derive from `Exception`, not `BaseException` or no base class.

Answer

class LibraryError: pass
class FileError(LibraryError): pass
class ParseError(LibraryError): pass

Answer

class LibraryError(BaseException): pass
class FileError(LibraryError): pass
class ParseError(LibraryError): pass

Answer

class LibraryError(Exception): pass
class FileError(Exception): pass
class ParseError(Exception): pass

Question 5

A programmer writes a class with a method that should be called on the class itself, not on instances. Which decorator is appropriate?

Accepted Answer

@classmethod. The @classmethod decorator transforms a method so that it receives the class itself as the first implicit argument (cls), rather than an instance (self). This allows the method to be called on the class directly, e.g., MyClass.my_method(), and is the correct choice when a method should operate on the class level, not on instances.

Answer

@property

Answer

@abstractmethod

Answer

@staticmethod

Question 6

A developer needs to count the number of occurrences of the substring 'is' in the string 'This is a test. Is this a test?'. Which code correctly performs the count?

Accepted Answer

'This is a test. Is this a test?'.count('is'). Python's string method `count(substring)` returns the number of non-overlapping occurrences of the substring in the string. In 'This is a test. Is this a test?', 'is' appears twice (in 'This' and 'is'), and the method counts them correctly, ignoring case sensitivity (the capitalized 'Is' is not counted).

Answer

'This is a test. Is this a test?'.split().count('is')

Answer

'This is a test. Is this a test?'.index('is')

Answer

'This is a test. Is this a test?'.find('is')

Question 7

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?

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.

Answer

Use a class method to modify the list.

Answer

Use `deepcopy` when accessing the list.

Question 8

A senior developer in a team argues that using try-except blocks is slower than checking conditions with if statements. They propose replacing all try blocks that handle file I/O errors with existence checks using os.path.exists before opening files. During a code review, you recall that Python's official documentation and best practices prefer EAFP (Easier to Ask for Forgiveness than Permission) over LBYL (Look Before You Leap) in many cases, especially in concurrent environments. The team's application is a multi-threaded web server that serves static files from a shared directory. Which is the strongest counterargument against the senior developer's proposal?

Accepted Answer

LBYL leads to race conditions in concurrent code because the file's state can change between the check and the use.. In a multi-threaded web server, the LBYL approach (checking with os.path.exists) introduces a classic TOCTOU (Time of Check, Time of Use) race condition: between the existence check and the actual file open, another thread could delete or rename the file, causing the open to fail despite the check passing. Python's EAFP idiom (try-except) avoids this window by attempting the operation directly and handling the exception if it fails, which is inherently atomic with respect to the file system state. This is why official Python documentation recommends EAFP over LBYL in concurrent environments.

Answer

if statements are harder to read and maintain.

Answer

try-except can catch multiple exception types more cleanly.

Answer

try-except blocks have no performance cost at all.

Question 9

In Python, if you have a try block followed by an except clause that catches all exceptions, which of the following is true about the else clause?

Accepted Answer

The else clause runs only if no exception is raised in the try block.. In Python, the `else` clause in a `try` statement executes only if no exception was raised in the `try` block. This is true regardless of whether the `except` clause catches all exceptions (e.g., bare `except:` or `except Exception:`). The `else` block is specifically designed for code that should run only when the `try` block completes successfully without any exception.

Answer

The else clause runs only if an exception occurs.

Answer

The else clause runs before the finally block regardless of exceptions.

Answer

The else clause is used to specify additional exception handlers.

Question 10

Which of the following demonstrates that strings are immutable?

Accepted Answer

s[0] = 'J' results in a TypeError. Attempting to assign a new character to an index of a string (e.g., s[0] = 'J') raises a TypeError, which directly demonstrates that strings are immutable in Python. Immutability means the object's value cannot be changed after creation; any operation that appears to modify a string actually creates a new string object.

Answer

s.upper() changes s in place

Answer

s += '!' modifies s

Answer

s.replace('a','b') modifies s

Question 11

A developer needs to parse a log file where each line contains a timestamp followed by a message. The timestamp format is 'YYYY-MM-DD HH:MM:SS'. Which string method is most appropriate to split the timestamp from the message?

Accepted Answer

str.split(). Str.split(), is the most appropriate because it splits a string on whitespace by default. Although the timestamp 'YYYY-MM-DD HH:MM:SS' contains a space, using split() without arguments returns a list of all space-separated elements. Since the timestamp is always the first two elements (date and time), the developer can join them with a space to get the full timestamp. Alternatively, split() can be used with a specified separator and maxsplit to achieve the desired split. This flexibility makes str.split() the best choice among the given options.

Answer

str.rsplit()

Answer

str.splitlines()

Answer

str.partition()

Question 12

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

Answer

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

Answer

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

Question 13

A function receives a file path like '/home/user/docs/file.txt' and needs to return the path without the file extension, e.g., '/home/user/docs/file'. Which code reliably removes only the last dot extension, even if the directory names contain dots?

Accepted Answer

path.rsplit('.', 1)[0]. `rsplit('.', 1)` splits the string from the right, limiting the split to exactly one occurrence, which isolates the file extension (the part after the last dot) and returns everything before it. This reliably removes only the last dot extension, even if directory names contain dots, because it targets the final dot in the path.

Answer

path.split('.')[0]

Answer

path.replace('.', '', 1)

Answer

path[:path.find('.')]

Question 14

Refer to the exhibit. A developer is writing a script to read this JSON configuration file. The script should write the logging configuration to a separate file called 'logging.conf'. Which file mode should be used to create the file if it doesn't exist, and overwrite it if it does?

Accepted Answer

'w'. ('w') is correct because the 'w' mode opens a file for writing, truncating it first if it exists, and creating it if it does not. This matches the requirement to overwrite an existing 'logging.conf' file or create a new one if absent.

Answer

'x'

Answer

'r+'

Answer

'a'

Question 15

A package 'mypackage' has subpackages 'sub1' and 'sub2'. In sub1/__init__.py, there is: from sub2 import helper. When importing mypackage, an ImportError occurs: No module named 'sub2'. What is the most likely cause?

Accepted Answer

The import should be from .sub2 import helper (relative import).. When a subpackage (sub1) tries to import from a sibling subpackage (sub2) using a bare name (from sub2 import helper), Python looks for 'sub2' as a top-level module, not as a sibling within the same parent package. Since 'sub2' is not installed as a top-level module, an ImportError occurs. Using a relative import (from .sub2 import helper) explicitly tells Python to look for sub2 as a sibling package under the same parent, resolving the import correctly.

Answer

Sub2 is not installed in the Python environment.

Answer

Sub2 must be imported before sub1 in the package's __init__.py.

Answer

Sub1 should not have an __init__.py file.

Question 16

A developer tries to modify a string: s = 'hello'; s[0] = 'H'. What happens when this code runs?

Accepted Answer

It raises a TypeError: 'str' object does not support item assignment. Strings in Python are immutable, meaning their contents cannot be changed after creation. Attempting to assign a new character to an index position (e.g., s[0] = 'H') raises a TypeError: 'str' object does not support item assignment. To modify a string, you must create a new string using slicing or concatenation.

Answer

It changes the string to 'Hello'

Answer

It creates a new string 'Hello' and assigns it to s

Answer

It raises an IndexError because index 0 is out of range

Question 17

You are a DevOps engineer managing a Python application that consists of multiple microservices. One microservice, 'data_processor', imports a shared library 'common_lib' which is also used by other microservices. The shared library is developed in a separate repository and is installed via pip in each microservice's virtual environment as an editable package (pip install -e). Recently, you updated 'common_lib' with new functions, but when you redeploy 'data_processor' (by restarting the container), the new functions are not available; the old version is still used. The container uses a Docker image built from a requirements file that specifies 'common_lib' from a Git repository. You verify that the Git commit hash in the requirements file points to the latest version. What is the most likely cause and what is the correct course of action?

Accepted Answer

Update the commit hash or use a version tag that points to the latest, and rebuild the Docker image without using cache (--no-cache).. When a Docker image is built, pip installs the package from the Git repository at the commit hash specified in the requirements file. Even if the requirements file points to the latest commit, Docker's layer caching may reuse a previously built layer that contains the old version of the package. Rebuilding the image with --no-cache forces Docker to re-execute the pip install step, fetching the latest code from Git and installing the updated common_lib. Simply restarting the container does not rebuild the image, so the old installed package persists.

Answer

Add the common_lib source directory to sys.path in the microservice code.

Answer

Rename the package in the requirements file to force a fresh install.

Answer

Change the Python interpreter to a different version.

Question 18

A developer is building a logging system that writes logs to a file. The system should handle disk-full situations gracefully without crashing the main application. Which approach is appropriate?

Accepted Answer

Wrap the log write in a try/except that catches OSError and writes to stderr as fallback.. It uses a targeted try/except block around only the log write operation, catching OSError (which includes disk-full conditions) and falling back to stderr. This prevents the main application from crashing while still reporting the error, adhering to the principle of handling exceptions at the point where they occur and only when you can meaningfully recover.

Answer

Check disk space before each write; if low, skip logging.

Answer

Wrap the entire application in a try/except that catches all exceptions.

Answer

Let the OSError propagate to the main program's exception handler.

Question 19

A Python script fails with 'ModuleNotFoundError: No module named 'myapp.config''. The environment variable PYTHONPATH is not set. Which of the following is the most likely cause?

Accepted Answer

The module is located in a directory not included in sys.path. When PYTHONPATH is not set, Python relies solely on sys.path to locate modules. sys.path includes the script's directory, standard library paths, and site-packages. If 'myapp.config' is not in any of these directories, Python raises ModuleNotFoundError. Option A correctly identifies that the module is in a directory not included in sys.path.

Answer

The module's __init__.py is missing

Answer

The module is installed in a different Python version's site-packages

Answer

The module has a syntax error

Question 20

A package 'pkg' is installed as an egg-link in development mode. Inside the package, there is a module 'submod.py' that uses relative imports. When a developer modifies 'submod.py', they find that changes are not always reflected on import. What is the most likely reason?

Accepted Answer

Python's module caching in sys.modules prevents re-loading the modified source.. Python caches imported modules in `sys.modules`. When a module is imported, Python stores the module object in `sys.modules` and subsequent imports retrieve it from this cache without re-executing the module's code. Modifying the source file of `submod.py` does not automatically invalidate this cache, so the changes are not reflected unless the module is explicitly reloaded (e.g., with `importlib.reload()`) or the interpreter is restarted.

Answer

The sys.path is altered by the egg-link, causing a different module to be loaded.

Answer

Relative imports are cached in the __init__.py file.

Answer

The __pycache__ directory is not cleared automatically.