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Quizzes > Quizzes for Business > Technology

Python Developer Skills Assessment: Take the Quiz

Evaluate Your Python Coding Proficiency Today

Difficulty: Moderate
Questions: 20
Learning OutcomesStudy Material
Colorful paper art illustrating a quiz on Python Developer Skills Assessment

Dive into this free Python Developer Skills Assessment to benchmark your coding expertise - whether refining fundamentals or tackling real-world challenges. Ideal for aspiring developers, educators, or anyone seeking to validate their Python skills, this interactive python quiz can highlight areas for improvement. Try the Python Programming Practice Quiz for targeted practice or explore core concepts with our Python Fundamentals Quiz. You can adjust all questions in our editor to tailor difficulty and focus. Ready to elevate your skills? Check out more quizzes now!

Which of the following Python data types is mutable?
FrozenSet
List
Tuple
String
Lists are mutable sequences in Python, meaning their contents can be changed after creation. Tuples, strings, and frozensets are immutable types that cannot be modified once defined.
Which syntax correctly creates a dictionary comprehension mapping each number x from 0 to 4 to x squared?
{x: x**2 for x in range(5)}
dict(x, x**2 for x in range(5))
[x**2 for x in range(5)]
{(x, x**2) for x in range(5)}
A dictionary comprehension uses braces with key:value pairs and an in-clause. The correct form is {x: x**2 for x in range(5)}, which generates a dict of numbers to their squares.
Which exception is raised by dividing a number by zero in Python?
ZeroDivisionError
ValueError
IndexError
TypeError
Attempting to divide by zero in Python specifically raises a ZeroDivisionError. This exception is a subclass of ArithmeticError and indicates an invalid arithmetic operation.
How would you correctly import the sqrt function from the math module?
import math.sqrt
import sqrt from math
import math.s
from math import sqrt
The correct syntax to import a specific function from a module is 'from module import function'. Therefore, 'from math import sqrt' imports only the sqrt function.
Given a class Person with an __init__ method accepting name, which code correctly creates an instance with name "Alice"?
p = Person
p = Person('Alice')
p = Person()
p = new Person('Alice')
To instantiate a class in Python, you call the class name with any required arguments. Person('Alice') correctly passes the name to the constructor.
What is the average time complexity of appending an element to the end of a Python list?
Amortized O(1)
O(n log n)
O(n)
O(log n)
Appending to a Python list is an amortized O(1) operation due to occasional resizing costs. Most append operations are constant time on average.
Which of the following creates a deep copy of an object 'obj'?
new_obj = obj[:]
import copy; new_obj = copy.copy(obj)
new_obj = obj
import copy; new_obj = copy.deepcopy(obj)
The copy.deepcopy function from the copy module performs a deep copy, recursively copying nested objects. copy.copy performs a shallow copy and slicing only works for sequences like lists.
In a function definition, what does **kwargs represent?
A list of keyword arguments
A tuple of positional arguments
A string of arguments
A dictionary of keyword arguments
In Python, **kwargs collects extra keyword arguments into a dictionary. Each key is the argument name and each value is the passed value.
Which statement best describes the difference between a list comprehension and a generator expression?
A generator expression computes elements on demand, saving memory
A generator expression returns a list in memory
A list comprehension yields items on demand
A list comprehension returns a generator object that yields items lazily
Generator expressions compute values lazily and yield items one by one as needed, which saves memory. List comprehensions compute all elements immediately and store them in a list.
Why is the 'if __name__ == "__main__":' statement commonly used in Python scripts?
To ensure code runs only when the script is executed directly
To initialize global variables before imports
To run code only when the module is imported
To declare the script's encoding
The conditional if __name__ == "__main__" ensures that code inside it runs only when the file is executed as the main program. It prevents that block from running during imports.
Which slicing operation will reverse the list 'items'?
items[1::-1]
items[::1]
items[:-1]
items[::-1]
Using items[::-1] creates a new list that is the reverse of items by stepping through the sequence backwards. The other slices either do nothing or exclude elements incorrectly.
Which built-in function allows you to iterate over a sequence and have access to both the index and the element?
zip()
map()
enumerate()
filter()
The enumerate() function adds a counter to an iterable and returns it as an enumerate object yielding pairs of (index, element). This is the standard way to get both index and value.
How do you define a private attribute 'value' in a Python class to trigger name mangling?
__value
value__
_value
value
Prefixing an attribute with two underscores, as in __value, triggers name mangling in Python. This makes the attribute accessible only via a transformed name, reducing accidental access.
Which approach properly ensures a file is closed after reading its contents?
try: f = open('file.txt') finally: pass
f = open('file.txt'); data = f.read(); f.close()
f = open('file.txt', 'r'); data = f.read()
with open('file.txt') as f: data = f.read()
Using a with statement ensures that the file is automatically closed when the block is exited, even if an exception occurs. Manual open and close calls can be error-prone.
What type of object does the built-in 'filter' function return in Python 3?
Filter object (iterator)
Dictionary
Tuple
List
In Python 3, filter() returns an iterator known as a filter object. To obtain a list, you must explicitly convert it with list(filter_obj).
To implement a custom context manager, which methods must be defined in a class?
__start__ and __finish__
__call__ and __exit__
__init__ and __del__
__enter__ and __exit__
Defining __enter__ and __exit__ in a class implements the context manager protocol, allowing use of the with statement. __enter__ executes at block entry and __exit__ handles cleanup.
In Python, what is a metaclass?
A class that defines methods for instances
A special module type
The class of a class, controlling its creation
A function decorator
A metaclass is the class of a class, meaning it defines how classes behave and are constructed. By default, the metaclass for most classes is type.
Which pattern allows a decorator to accept arguments?
Defining a class with __call__ only
Using @decorator without parentheses
Defining a function that returns a decorator function
Passing arguments directly into the decorated function
A decorator factory is a function that takes arguments and returns a decorator. This pattern allows passing parameters to the decorator before it wraps the target function.
What is the key difference between a generator function defined with 'yield' and a list comprehension?
A generator function returns all items at once in a list
A list comprehension can only generate numbers
A generator function produces items lazily and can maintain internal state
A generator function requires less code than a list comprehension
Generator functions use yield to produce values one at a time and can maintain local state between yields. List comprehensions generate the entire list in memory immediately.
Which standard library module is designed for asynchronous I/O and coroutines?
concurrent
multiprocessing
threading
asyncio
The asyncio module provides infrastructure for writing single-threaded concurrent code using async/await syntax. It is specifically designed for asynchronous I/O and coroutines.
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Learning Outcomes

  1. Analyse data structures and algorithms in Python code.
  2. Evaluate object-oriented programming implementations using classes.
  3. Master error handling and debugging techniques in Python.
  4. Identify best practices for writing efficient Python scripts.
  5. Apply knowledge of Python libraries and modules effectively.
  6. Demonstrate comprehension of advanced Python concepts and syntax.

Cheat Sheet

  1. Master Python's Core Data Structures - Dive into lists, tuples, dictionaries, and sets to build a rock-solid toolkit for any coding challenge. Lists are your go-to for ordered, mutable collections, while tuples lock things down with immutability. Dictionaries pair keys and values like magic, and sets keep duplicates at bay so you can crunch data fast. GeeksforGeeks
  2. Decode Time Complexity - Learn to measure how your algorithms scale by mastering Big O notation. When you know that a linear search is O(n) and a binary search sprints at O(log n), you can pick the fastest path through data jungles. It's like having a speedometer for your code's performance! Medium
  3. Conquer Object-Oriented Programming - Create classes with attributes and methods to organize code into neat, reusable packages. Embrace inheritance, encapsulation, and polymorphism to make your projects scalable and supermaintainable. Think of classes as blueprints for epic Python creations! Upenn SEAS
  4. Implement Robust Error Handling - Wrap risky operations in try-except blocks to catch and manage exceptions before they crash your party. You'll learn how to cleanly handle unexpected inputs and states, ensuring your scripts stay rock-solid under pressure. GeeksforGeeks
  5. Level Up Your Debugging Game - Channel your inner detective with print statements, logging, and Python's pdb debugger. Track down bugs and trace execution paths like a pro, turning frustrating errors into quick learning wins. GeeksforGeeks
  6. Follow PEP 8 and Best Practices - Write clean, readable code by sticking to the PEP 8 style guide. From naming conventions to indentation rules, you'll keep your projects consistent, approachable, and easy to share - no more wild tab-vs-space turf wars! GeeksforGeeks
  7. Explore Python's Standard Library - Unlock the power of built-in modules like os, math, datetime, and more to supercharge your scripts without reinventing the wheel. Whether you're handling files or crunching numbers, there's a library ready to lend a hand. GeeksforGeeks
  8. Demystify Recursion - Write functions that call themselves to solve problems elegantly, from factorials to tree traversal. You'll discover how complex tasks can shrink down to simple base cases, making your solutions both concise and powerful. GeeksforGeeks
  9. Compare Sorting Algorithms - Study quicksort, mergesort, and more to understand different ways of organizing data. Learn their time and space trade-offs so you can pick the right sorter for every scenario and keep your programs humming. GeeksforGeeks
  10. Unlock Advanced Python Features - Dive into decorators, generators, and context managers to write code that's both concise and ultra-powerful. These advanced tools help you automate repetitive tasks and manage resources with style. GeeksforGeeks
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