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Python Quiz Questions

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About Python Quizzes

Python is the world's most popular programming language for good reason: its clean syntax, expressive idioms, and vast ecosystem make it equally at home in data science, web development, automation, AI research, and system scripting. Yet despite Python's reputation for being beginner-friendly, it has surprising depths — descriptors, metaclasses, the GIL, CPython internals — that trip up even experienced engineers.

QuizBytesDaily's Python quizzes are designed to close that gap. Each question targets a specific concept: how list comprehensions handle nested loops, when a generator is more memory-efficient than a list, what happens when you mutate a default mutable argument, or why `is` and `==` can give different results on the same integers.

Our questions span the full spectrum from Beginner to Advanced. Beginner questions focus on types, control flow, and basic data structures. Intermediate questions cover OOP, file I/O, standard library modules (`itertools`, `collections`, `functools`), decorators, and context managers. Advanced questions tackle async/await concurrency, descriptor protocol, metaclasses, and CPython-level behaviours.

Why Learn Python?

Industry demand
Python consistently ranks #1 in developer surveys and is the dominant language for data engineering, ML research, and backend APIs.
Versatility
A single language covers scripting, web (Django/FastAPI), data science (pandas/numpy), ML (PyTorch/TensorFlow), and CLI tooling.
Interview relevance
Python is the go-to language for FAANG coding interviews. Deep knowledge of built-ins and idioms can set you apart from candidates who only know the basics.

What You'll Find in Our Python Quizzes

  • Syntax gotchas (mutable defaults, late binding closures)
  • Data structure operations (dict, set, deque, heap)
  • OOP concepts (MRO, property, __slots__, ABC)
  • Functional patterns (map, filter, reduce, comprehensions)
  • Async/await and the event loop
  • Memory management and the GIL
  • Standard library deep-dives
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Other Quiz Categories

🤖 AI & Machine Learning🧮 Algorithms JavaScript🏗️ System Design📘 TypeScript

Sample Python Quiz Questions

A taste of what you'll find in the Python quiz series.

1

What is the output of the following code? def add(x, lst=[]): lst.append(x) return lst print(add(1)) print(add(2))

A.[1] then [2]
B.[1] then [1, 2]✓ Correct
C.[1, 2] then [1, 2]
D.Error

Explanation: Python evaluates default arguments once at function definition time, not each call. The same list object is reused across calls, so the second call appends to the same list, producing [1, 2]. This is a classic mutable default argument gotcha — use `lst=None` and create a new list inside the function instead.

2

What does `isinstance(True, int)` return in Python?

A.False
B.True✓ Correct
C.TypeError
D.None

Explanation: In Python, `bool` is a subclass of `int`. This means `True` and `False` are instances of both `bool` and `int`. As a result, `isinstance(True, int)` returns `True`. This also means `True + True` evaluates to `2` and `True == 1` is `True`.

3

Which of the following creates a generator in Python?

A.def gen(): return [x * 2 for x in range(5)]
B.def gen(): yield from [x * 2 for x in range(5)]✓ Correct
C.gen = (x * 2 for x in range(5)) but calling gen()
D.def gen(): return (x * 2 for x in range(5))

Explanation: A function that contains a `yield` or `yield from` statement becomes a generator function — calling it returns a generator object that produces values lazily. Option B uses `yield from` to delegate to a list comprehension. A generator expression like `(x*2 for x in range(5))` is also a generator, but option C describes calling it as a function, which would fail.

4

What is the time complexity of looking up a key in a Python dict?

A.O(n)
B.O(log n)
C.O(1) average, O(n) worst case✓ Correct
D.O(n log n)

Explanation: Python dicts are hash tables. Key lookups are O(1) on average because the hash function maps the key directly to a bucket. In the worst case — when every key hashes to the same bucket (hash collision) — lookup degrades to O(n). CPython's dict implementation uses a compact open-addressing scheme that keeps the average case very close to O(1) in practice.

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