Python Interview Questions

What should you focus on for your Python interview?

Which topic should you start with?

Start with data structures and coding. It was the most common topic in these interviews, appearing in 130 of 281 interviews. Most questions were junior-level, so begin by checking your understanding of the basics.

Can you name Python's data types, give examples of mutable and immutable objects, and explain the difference between == and is? Use these questions to find what you need to review before moving to more specialised topics.

Can you explain when to use lists and tuples?

Lists versus tuples was the most asked question, appearing in 35 of 281 interviews. Your answer should cover when you would choose each, not just how they differ.

Reviewed answers missed practical effects of tuple immutability, including preventing accidental changes and memory and performance implications. Some mutability answers also had missing or incorrect type examples.

Check whether you can answer these questions:

• When would you choose a list rather than a tuple?
• What does tuple immutability mean in practical use?
• Can you give correct examples? Lists are mutable; tuples and strings are immutable.
• How do shallow and deep copies differ for nested lists?

Can you show a decorator and a useful lambda?

Reviewed decorator answers sometimes lacked a definition in code and an example using @decorator syntax. Can you write a decorator and show how to apply it to a function?

For lambdas, the missing detail was a practical reason to use one. Can you show a short inline function passed to sorted, map or filter, and explain why you chose it?

Can you complete a coding task?

Code-writing tasks appeared in 95 of 281 interviews. String reversal was the most common listed task. Some reviewed answers described an approach without presenting a complete implementation.

Can you write a function that returns the reversed string? Check that your answer includes the working code, not only an explanation.

Then check whether you can write code to:

• Generate the Fibonacci series.
• Remove duplicate items from a list.
• Check whether a number is prime.
• Check whether a number is even.

Can you explain how the GIL affects threads?

The GIL was among the most asked questions. Can you explain how it affects multithreading for CPU-bound work and for I/O-bound work? Cover both kinds of work rather than only saying what GIL stands for.

Who gets asked Python

The 20 most asked Python questions

Counted by interview, not by mention: a question asked twice in one conversation counts once.

1. How do Python lists and tuples differ, and when would you choose each?

   Asked in 35 of 281 interviews · last asked Oct 18 · Concept · Junior

   Show answer

   Lists are mutable: you can add, remove, or replace items. Tuples are immutable: you cannot change their items after creation. Choose a list for a collection that changes, and a tuple for a fixed record, such as coordinates, to prevent accidental changes.

   • Both preserve order and support indexing, slicing, and duplicate values.
   • A tuple can contain mutable objects, such as lists, whose contents can still change.
   • A tuple can be a dictionary key only if all its items are hashable; lists cannot.
   • Tuples typically use less memory than lists, but they are not always faster.

   What the interviewer checks: The interviewer checks whether you understand mutability and can choose the right type for the data.

   Common mistake (in 6 of 12 reviewed answers): Many answers forget that tuple immutability prevents accidental item changes but does not freeze objects stored inside.

   Other ways it was asked

   • “What is the difference between a list and a tuple?”
   • “What is the difference between a list and a tuple in Python?”
   • “What is the difference between a Python list and a tuple?”

2. What are decorators in Python?

   Asked in 17 of 281 interviews · last asked Oct 17 · Concept · Junior

   Show answer

   A decorator is a callable that takes a function and usually returns a replacement function that adds behavior. It lets you add behavior without changing the original function’s code. Common uses include logging, access checks, and caching; decorators can also apply to classes.

   • `@decorate` above a function means `function = decorate(function)`.
   • A wrapper can run code before or after calling the original function.
   • `functools.wraps` preserves details such as the original function’s name and docstring.

   PythonCopy

   from functools import wraps
   def log_call(func):
       @wraps(func)
       def wrapper(*args, **kwargs):
           print("Calling", func.__name__)
           return func(*args, **kwargs)
       return wrapper
   @log_call
   def greet(name):
       return f"Hello, {name}"

   What the interviewer checks: The interviewer checks whether you understand how decorators wrap functions and how to define and apply them.

   Common mistake (in 5 of 11 reviewed answers): Many answers forget that explaining decorators should include defining one and applying it with @ syntax.

   Other ways it was asked

   • “What is a decorator in Python?”
   • “What are Python decorators, and when would you use them?”
   • “What is a decorator in Python, and what is it used for?”

3. What is Python, and what are its key features?

   Asked in 15 of 281 interviews · last asked Oct 18 · Concept · Junior

   Show answer

   Python is a high-level, general-purpose programming language known for readable syntax. It is dynamically typed, manages memory automatically, and is usually run through an interpreter. It supports several programming styles and has a large standard library and many third-party packages.

   • Dynamic typing means types belong to objects, and variable names can refer to objects of different types.
   • Python supports procedural, object-oriented, and functional programming styles.
   • Python runs on major operating systems, though some code and packages depend on the platform.
   • Its libraries support tasks such as web development, automation, data analysis, and machine learning.

   What the interviewer checks: The interviewer is checking whether you can define Python and explain its main features clearly.

   Other ways it was asked

   • “What is Python?”
   • “What are the features of Python?”
   • “What is the definition of Python?”

4. What is the difference between mutable and immutable objects, and which Python types are examples?

   Asked in 15 of 281 interviews · last asked Oct 22 · Concept · Junior

   Show answer

   Mutable objects can change after they are created. Immutable objects cannot change after they are created. Lists, dictionaries, and sets are mutable; integers, floats, strings, tuples, and frozensets are immutable.

   • Changing a mutable object affects all variables that refer to that object.
   • Reassigning a variable is not the same as changing its object.
   • A tuple cannot replace its items, but mutable objects inside it can still change.

   PythonCopy

   items = [1, 2]
   alias = items
   items.append(3)
   print(alias)  # [1, 2, 3]
   
   text = "cat"
   original = text
   text += "s"  # Assigns a new string; the original stays unchanged.
   print(original)  # cat

   What the interviewer checks: The interviewer is checking whether you know common Python types and understand changing an object versus reassigning a variable.

   Common mistake (in 5 of 9 reviewed answers): Many answers forget that lists are mutable, while tuples and strings are immutable.

   Other ways it was asked

   • “What is the difference between mutable and immutable data types?”
   • “What are mutable and immutable objects in Python?”
   • “Can you explain mutable and immutable objects, with examples?”

5. What is Python's GIL, and how does it affect multithreading for CPU-bound and I/O-bound workloads?

   Asked in 14 of 281 interviews · last asked Oct 17 · Concept · Mid-level

   Show answer

   The GIL, or Global Interpreter Lock, lets only one thread execute Python bytecode at a time in standard CPython. CPU-bound Python threads therefore do not run in parallel across CPU cores. I/O-bound threads can still help because blocking I/O usually releases the GIL, letting other threads run.

   • Use multiprocessing for CPU-bound Python work that needs multiple cores.
   • Some native libraries release the GIL, allowing CPU-bound work to run in parallel.
   • Optional free-threaded CPython builds, available from Python 3.13, can run without the GIL.
   • The GIL does not make shared data automatically safe; threads may still need locks.

   What the interviewer checks: The interviewer checks whether you distinguish CPU work from I/O waiting and choose a suitable concurrency approach.

   Other ways it was asked

   • “What is the Global Interpreter Lock in Python?”
   • “What is the GIL (Global Interpreter Lock) in CPython, and how does it affect multithreading?”
   • “What is the Global Interpreter Lock (GIL) in Python, and how does it affect concurrency?”

6. What is the difference between shallow and deep copies in Python, especially for nested lists?

   Asked in 12 of 281 interviews · last asked Oct 17 · Concept · Mid-level

   Show answer

   A shallow copy creates a new outer list but shares the nested lists with the original. A deep copy also copies the nested lists, so changing them does not change the original. Replacing an item in the outer list of either copy does not change the original outer list.

   • Use list.copy(), slicing, or copy.copy() for a shallow list copy.
   • Use copy.deepcopy() to copy nested lists too.
   • Assignment alone does not copy a list; both names refer to the same list.

   PythonCopy

   import copy
   
   original = [[1, 2], [3, 4]]
   shallow = original.copy()
   deep = copy.deepcopy(original)
   shallow[0].append(9)
   print(original)  # [[1, 2, 9], [3, 4]]
   print(deep)      # [[1, 2], [3, 4]]

   What the interviewer checks: The interviewer is checking whether you understand shared references and how changes affect nested lists.

   Other ways it was asked

   • “What is the difference between a shallow copy and a deep copy?”
   • “What is the difference between a deep copy and a shallow copy?”
   • “What is the difference between shallow and deep copying in Python, and when can a shallow copy cause problems?”

7. What is the difference between == and is in Python?

   Asked in 9 of 281 interviews · last asked Oct 15 · Concept · Junior

   Show answer

   `==` checks whether two objects have equal values. `is` checks whether they are the same object. Use `==` to compare values and `is None` to check for `None`. A single `=` assigns a value; it does not compare values.

   • Two different objects can have equal values.
   • Classes can customize equality with `__eq__`; they cannot customize identity checks.
   • Do not use `is` to compare numbers or strings; object reuse can make results misleading.

   PythonCopy

   a = [1, 2]
   b = [1, 2]
   c = a
   print(a == b)  # True: equal values
   print(a is b)  # False: different objects
   print(a is c)  # True: same object

   What the interviewer checks: The interviewer is checking whether you understand value equality, object identity, and when to use each operator.

   Other ways it was asked

   • “What is the difference between `==` and `is` in Python?”
   • “In Python 3, what is the difference between == and is, and when would you use each?”
   • “In Python, what is the difference between = and ==?”

8. What data types are available in Python?

   Asked in 9 of 281 interviews · last asked Sep 30 · Concept · Junior

   Show answer

   Python has numeric types (`int`, `float`, `complex`), booleans (`bool`), and text (`str`). Its collection types include `list`, `tuple`, `range`, `dict`, `set`, and `frozenset`. Binary types include `bytes`, `bytearray`, and `memoryview`; `None` has type `NoneType` and represents no value.

   • Lists, dictionaries, and sets are mutable: their contents can change.
   • Numbers, strings, and tuples are immutable: they cannot be changed in place.
   • Dictionaries store key-value pairs; sets store unique elements.
   • Python is dynamically typed: a variable can refer to objects of different types.

   What the interviewer checks: The interviewer is checking whether you know the main built-in types and their basic differences.

   Other ways it was asked

   • “What built-in data types does Python provide?”
   • “Name the data types in Python.”
   • “What are Python data types?”

9. What string hashing algorithm is used in Python?

   Asked in 9 of 281 interviews · last asked Oct 22 · Concept · Mid-level

   Show answer

   CPython normally uses SipHash for string hashing, with SipHash13 as the default since Python 3.11. The exact algorithm depends on the Python implementation, version, and build. String hashes are randomized between processes by default.

   • CPython 3.4–3.10 normally used SipHash24.
   • Check sys.hash_info.algorithm to see your runtime’s algorithm.
   • Do not use hash() for persistent IDs or cryptographic checks.

   PythonCopy

   import sys
   
   print(sys.hash_info.algorithm)

   What the interviewer checks: The interviewer checks whether you know the default algorithm and understand version differences and hash randomization.

   Other ways it was asked

   • “What hashing algorithm is used for strings in Python?”
   • “What hashing algorithm is used for Python string hashing?”

10. What is a lambda function in Python, and how do you use it?

    Asked in 9 of 281 interviews · last asked Oct 22 · Concept · Junior

    Show answer

    A lambda function is a small, anonymous function created with `lambda arguments: expression`. It returns the value of that single expression. Use it for short inline functions, such as a sorting key; use `def` when the function needs statements or clearer, reusable logic.

    • A lambda can take multiple arguments, but its body must be one expression.
    • The expression's value is returned automatically, without a return statement.
    • Pass a lambda to sorted, map, or filter for a short operation.

    PythonCopy

    people = [("Ana", 30), ("Ben", 20)]
    by_age = sorted(people, key=lambda person: person[1])
    print(by_age)  # [('Ben', 20), ('Ana', 30)]

    What the interviewer checks: The interviewer is checking whether you understand lambda syntax, its limits, and when it is useful.

    Common mistake (in 4 of 9 reviewed answers): Many answers forget that a lambda is useful for passing a short inline function to tools such as sorted.

    Other ways it was asked

    • “What is a lambda function?”
    • “What are lambda functions in Python?”
    • “What are Python lambda functions, and when would you use them?”

11. How would you write Python code to reverse a string?

    Asked in 8 of 281 interviews · last asked Sep 19 · Write code · Junior

    Show answer

    I use `s[::-1]` to return a string in reverse order. The step `-1` reads the string backward. If slicing and built-in functions are not allowed, I loop over the characters and add each one to the front of a new string.

    • Strings are immutable, so the original string stays unchanged.
    • Both methods handle empty strings and single-character strings.
    • Repeatedly adding characters to the front can take quadratic time.

    PythonCopy

    def reverse_string(s):
        return s[::-1]
    
    
    def reverse_without_builtins(s):
        result = ""
        for char in s:
            result = char + result
        return result

    What the interviewer checks: The interviewer is checking whether you can use slicing or a loop to build and return the reversed string.

    Common mistake (in 4 of 5 reviewed answers): Many answers forget that a complete solution must return the reversed string, not just describe the approach.

    Other ways it was asked

    • “Write Python code to reverse a string.”
    • “How would you reverse a string in Python without using slicing or built-in functions?”
    • “How do I reverse a string in Python?”

12. What is a Python list, and how do you create one?

    Asked in 7 of 281 interviews · last asked Oct 17 · Concept · Junior

    Show answer

    A Python list is an ordered collection of items that you can change after creating it. It can hold different types of values and repeated values. You create a list with square brackets, such as [1, 2, 3], or with list() from an iterable.

    • Lists keep items in order and use indexes starting at zero.
    • You can add, remove, or replace items.
    • Use [] or list() to create an empty list.

    PythonCopy

    numbers = [10, 20, 30]
    mixed = [1, "hello", True]
    empty = []
    letters = list("abc")  # ['a', 'b', 'c']
    numbers[0] = 99
    numbers.append(40)

    What the interviewer checks: The interviewer is checking whether you understand basic list properties and how to create one.

    Other ways it was asked

    • “What is a list?”
    • “What is a list in Python?”
    • “Can you explain what a list is in Python?”

13. What are Python generators, and why would you use them instead of building lists?

    Asked in 6 of 281 interviews · last asked Oct 22 · Concept · Junior

    Show answer

    Python generators are iterators that produce values one at a time, instead of building a whole list. A generator function uses `yield` to pause and later resume with its state saved. I use generators to save memory and process large or infinite sequences when I do not need indexing or repeated passes.

    • Values are produced on demand, so unused values need not be computed.
    • Generators avoid storing all results at once.
    • An exhausted generator cannot restart; create a new one for another pass.
    • Lists support indexing and repeated passes; generators do not support indexing.

    PythonCopy

    def squares(count):
        for number in range(count):
            yield number * number
    
    values = squares(3)
    print(next(values))  # 0
    print(list(values))  # [1, 4]: only remaining values
    print(list(values))  # []: exhausted

    What the interviewer checks: The interviewer is checking whether you understand lazy iteration, memory savings, and when a list is more useful.

    Other ways it was asked

    • “What are the advantages of generators in Python?”
    • “What is a generator in Python?”
    • “What are generators in Python?”

14. What is a variable in Python?

    Asked in 5 of 281 interviews · last asked Oct 3 · Concept · Junior

    Show answer

    A variable in Python is a name that refers to an object. Assignment binds a name to an object, such as `age = 25`. Objects have types, but a variable can later refer to an object of a different type.

    • Assignment with `=` binds a name to an object.
    • You do not need to declare a variable’s type.
    • Different names can refer to the same object.

    PythonCopy

    age = 25
    print(age)  # 25
    age = "unknown"
    print(age)  # unknown

    What the interviewer checks: The interviewer is checking whether you understand names, assignment, and Python’s dynamic typing.

15. What does dynamic typing mean in Python, and how do variables relate to the values they reference?

    Asked in 4 of 281 interviews · last asked Oct 18 · Concept · Junior

    Show answer

    Dynamic typing means Python checks types at runtime, and variable names do not have fixed types. Each name refers to an object, and that object has a type. You can reassign a name to an object of a different type without changing the original object.

    • Types belong to objects, not variable names.
    • Assignment binds a name to an object; it does not automatically copy the object.
    • Dynamic typing does not mean all type combinations are valid; unsupported operations can raise TypeError.

    PythonCopy

    value = 42          # Refers to an integer object.
    value = "hello"     # Now refers to a string object.
    print(type(value))  # <class 'str'>

    What the interviewer checks: The interviewer is checking whether you distinguish a variable name from the object and type it refers to.

    Other ways it was asked

    • “Why is Python called a dynamically typed language?”
    • “What does dynamically typed mean in Python?”
    • “What does it mean that Python is dynamically typed, and how does a variable's type relate to the value assigned to it?”

16. What makes an object usable as a dictionary key, and how does this apply to lists, tuples, and classes?

    Asked in 4 of 281 interviews · last asked Aug 25 · Concept · Junior

    Show answer

    A dictionary key must be hashable: its hash must stay fixed, and equal objects must have equal hashes. Lists are not hashable. Tuples are hashable only if every item is hashable. User-defined class instances are hashable by default, but custom equality can make them unhashable.

    • A tuple containing a list cannot be a dictionary key.
    • Default class instances use identity for equality; defining __eq__ without __hash__ makes instances unhashable.
    • Do not change fields used by a key's hash or equality.
    • Unequal objects can share a hash; dictionaries use equality to tell them apart.

    What the interviewer checks: The interviewer checks whether you understand hashability, its link to equality, and how it applies to custom objects.

    Other ways it was asked

    • “What types of values can be used as keys in a Python dictionary?”
    • “What types of data can be used as keys in a Python dictionary?”
    • “If you use a tuple as a dictionary key, what must be true of all the items inside the tuple, and why?”

17. Write Python code to generate the Fibonacci series.

    Asked in 4 of 281 interviews · last asked Sep 11 · Write code · Junior

    Show answer

    Use a loop to generate Fibonacci numbers, starting with 0 and 1. Each next number is the sum of the previous two. This function returns the first n numbers as a list.

    • The sequence starts with 0, 1, 1, 2, 3, 5.
    • Update both values together so the calculation uses their old values.
    • Return an empty list for zero terms; reject negative counts.

    PythonCopy

    def fibonacci(n):
        if n < 0:
            raise ValueError("n must be non-negative")
        terms = []
        a, b = 0, 1
        for _ in range(n):
            terms.append(a)
            a, b = b, a + b
        return terms
    print(fibonacci(10))

    What the interviewer checks: The interviewer checks whether you can use a loop, update values correctly, and handle small inputs.

    Other ways it was asked

    • “Write a Python program to display the Fibonacci series.”
    • “Write a Python program for the Fibonacci series.”
    • “Can you write Python code to generate the Fibonacci sequence?”

18. What is a tuple in Python?

    Asked in 4 of 281 interviews · last asked Sep 17 · Concept · Junior

    Show answer

    A tuple is an ordered, immutable sequence in Python. It can hold different types of values, but you cannot replace, add, or remove its items after creation. I use tuples to group related values that belong together, such as coordinates.

    • Tuples support indexing, slicing, and unpacking.
    • A one-item tuple needs a trailing comma, such as (5,).
    • Mutable objects inside a tuple, such as lists, can still change.
    • A tuple can be a dictionary key only if all its items are hashable.

    PythonCopy

    point = (3, 7)
    x, y = point
    print(point[0])  # 3
    single = (5,)  # A one-item tuple

    What the interviewer checks: The interviewer is checking whether you understand tuples, immutability, and when to use them instead of lists.

    Other ways it was asked

    • “What are tuples in Python, and when would you use them?”
    • “What is a tuple?”

19. How do you remove duplicate items from a list in Python?

    Asked in 4 of 281 interviews · last asked Sep 30 · Write code · Junior

    Show answer

    Use list(set(items)) if order does not matter and all items are hashable. Use list(dict.fromkeys(items)) to keep the first occurrence order in Python 3.7 and later; this also needs hashable items. With a loop, add each item to a new list only if it is not already there.

    • A set does not guarantee the original list order.
    • Dictionary keys preserve insertion order in Python 3.7 and later.
    • A loop with list membership checks also handles unhashable items, such as lists.
    • List membership checks can make the loop take quadratic time.

    PythonCopy

    items = [3, 1, 3, 2, 1]
    unique = []
    for item in items:
        if item not in unique:
            unique.append(item)
    print(unique)  # [3, 1, 2]

    What the interviewer checks: The interviewer checks whether you can remove duplicates while considering order, hashability, and speed.

    Other ways it was asked

    • “How would you remove duplicates from a Python list?”
    • “What are other ways to remove duplicate items from a list in Python besides using a set?”
    • “How would you implement duplicate removal from a list using a loop and a new list in Python?”

20. What are `if`/`else` statements in Python?

    Asked in 3 of 281 interviews · last asked Aug 18 · Concept · Junior

    Show answer

    Python `if`/`else` statements choose which block of code runs based on a condition. The `if` block runs when the condition is true; the `else` block runs when it is false. You can add `elif` to test more conditions.

    • Python tests conditions in order and runs only the first matching branch.
    • The `else` block is optional and handles cases where no condition matches.
    • Use a colon after each condition or `else`, and indent each block.

    PythonCopy

    age = 20
    if age >= 18:
        print("Adult")
    else:
        print("Under 18")

    What the interviewer checks: The interviewer is checking whether you understand conditional flow and Python's block syntax.

    Other ways it was asked

    • “What are if-else statements in Python?”
    • “How do Python `if`/`else` statements control program flow? Give a simple example.”

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How this list is made

Every question here was asked by a real interviewer in a real job interview that a candidate ran MeetAssist in. After the call, the interviewer's questions are pulled from the transcript. Practice sessions, tests, exams and anything that was not a job interview are dropped.

Questions are rewritten so they make sense on their own: names of people, employers and clients are removed, and speech-to-text mistakes are fixed. Small talk, logistics and questions about one candidate's own résumé are left out. Rephrasings of the same question are merged, and the count is the number of different interviews it came up in.

The interviews come from candidates who use MeetAssist, so they lean towards software, data and AI roles: the shares describe these interviews, not every Python interview. Answers to the most asked questions are written and checked by an editor; a "common mistake" is shown only when reviews of real answers in these interviews show it, with the count.

281 interviews, 199 candidates, Nov 2025 to Oct 2026. Updated every month with new interviews.