Top 30 Most Common Interview Questions About Python You Should Prepare For
Written by
James Miller, Career Coach
Landing a job as a Python developer requires more than just coding skills; you need to articulate your understanding of the language's core concepts, features, and best practices. Technical interviews often involve a mix of coding challenges and theoretical questions designed to gauge your foundational knowledge and problem-solving approach. Preparing for these common inquiries can significantly boost your confidence and performance. This guide presents 30 frequently asked interview questions about Python, covering essentials from data types and functions to memory management and advanced features like generators and decorators. Mastering these topics demonstrates a solid grasp of Python's capabilities and nuances, making you a more attractive candidate in the competitive tech landscape. Understanding why these questions are asked helps you frame your answers effectively, showcasing not just what you know, but how you think about Python development.
What Are interview questions about python?
Interview questions about Python are inquiries posed by interviewers to assess a candidate's knowledge, skills, and experience with the Python programming language. These questions cover a wide spectrum, from fundamental concepts like data types, control flow, and functions to more advanced topics such as object-oriented programming, data structures, memory management, concurrency, and standard libraries. They might also delve into Python-specific features like decorators, generators, comprehensions, and the Global Interpreter Lock (GIL). The format can vary, including theoretical explanations, code snippets analysis, debugging exercises, or discussions about best practices and design patterns. The goal is to evaluate a candidate's understanding of Python's syntax, semantics, idioms, and its practical application in software development roles.
Why Do Interviewers Ask interview questions about python?
Interviewers ask interview questions about Python for several crucial reasons. Firstly, they want to verify that a candidate possesses a solid understanding of the language's core principles and features. This includes checking familiarity with Pythonic ways of writing code. Secondly, these questions help gauge a candidate's problem-solving abilities and how they apply Python constructs to solve real-world programming tasks. Understanding concepts like data structures, algorithms, and concurrency in a Python context is vital. Thirdly, discussing topics like memory management, the GIL, or mutable vs. immutable types reveals a deeper insight into how Python works internally, which is important for writing efficient and robust applications. Finally, these questions facilitate a technical conversation, allowing the interviewer to assess communication skills, thought process, and cultural fit within the team.
What is Python? List some key features of Python.
What is the difference between Python lists and tuples?
What is the
init()method in Python?What is the difference between global and local variables?
What is an iterator in Python?
What are lambda functions in Python and when should you use them?
What is the difference between Python arrays and lists?
Explain Python's memory management.
What are args and *kwargs in Python?
What is the difference between
range()andxrange()?What is the purpose of the
zip()function?What is inheritance in Python?
What are generators in Python?
What is the Global Interpreter Lock (GIL)?
What are docstrings in Python?
How can you capitalize the first letter of a string in Python?
What is the difference between
/(division) and//(floor division) operators?What is a Python decorator?
What is list comprehension?
What are Python modules and packages?
How do you handle exceptions in Python?
What is the difference between deep copy and shallow copy?
How can you make a Python script executable on Unix?
What are Python's key data types?
What is the difference between a set and a list?
How do you manage package dependencies in Python?
What is the difference between mutable and immutable types?
What is the Python
withstatement?How can Python code be written to be compatible with both Python 2 and 3?
What is a Python dictionary?
Preview List
1. What is Python? List some key features of Python.
Why you might get asked this:
This is a fundamental question to start with, ensuring you know what Python is and its basic characteristics. It tests your overall familiarity with the language.
How to answer:
Define Python briefly and then list its main selling points, focusing on what makes it popular and versatile in the industry.
Example answer:
Python is a high-level, interpreted language known for readability and simplicity. Key features include dynamic typing, extensive standard libraries, support for multiple paradigms, automatic memory management, and a large community.
2. What is the difference between Python lists and tuples?
Why you might get asked this:
This checks your understanding of Python's core sequence data structures, particularly the concept of mutability, which is a key distinction.
How to answer:
Clearly state the main difference: mutability vs. immutability. Mention other differences like syntax, performance implications, and common use cases.
Example answer:
Lists are mutable, allowing modification after creation (add, remove elements). Tuples are immutable, fixed once defined. Lists use [], tuples use (). Tuples are generally faster for iteration due to immutability.
3. What is the init() method in Python?
Why you might get asked this:
Tests your understanding of object-oriented programming in Python, specifically class constructors and object initialization.
How to answer:
Explain its role as a constructor and when it is called. Mention its purpose in initializing object attributes.
Example answer:
init() is the constructor method for a class. It's automatically called when a new object is created. Its primary use is to initialize the object's attributes with initial values or perform setup actions.
4. What is the difference between global and local variables?
Why you might get asked this:
This assesses your grasp of variable scope, a critical concept in programming that affects how data is accessed and modified within a program.
How to answer:
Define each type based on where it's declared and its accessibility scope. Explain potential issues like shadowing.
Example answer:
Local variables are defined inside a function and only exist and are accessible within that function. Global variables are defined outside functions and are accessible globally throughout the program, including inside functions.
5. What is an iterator in Python?
Why you might get asked this:
Checks your understanding of iteration protocols, which are fundamental to looping over data structures efficiently without loading everything into memory at once.
How to answer:
Define an iterator in terms of the iterator protocol (iter and next methods). Explain its purpose in sequential access.
Example answer:
An iterator is an object that implements the iterator protocol: it must have iter() returning the iterator itself and next() returning the next item. It allows iterating over sequences and collections, providing items one by one.
6. What are lambda functions in Python and when should you use them?
Why you might get asked this:
Assesses your knowledge of functional programming aspects in Python and the appropriate use cases for small, anonymous functions.
How to answer:
Define lambda functions (anonymous, single expression). Explain their typical use cases, particularly with higher-order functions.
Example answer:
Lambda functions are small, anonymous functions defined with the lambda keyword. They have no name and contain only one expression. They are best used for short, simple operations, often as arguments to functions like map(), filter(), or sorted().
7. What is the difference between Python arrays and lists?
Why you might get asked this:
Tests your understanding of data structures for storing collections, highlighting Python's distinction between general-purpose lists and specialized array types.
How to answer:
Explain that lists are built-in and flexible (heterogeneous types), while arrays require the array module and are type-specific, often used for numeric data.
Example answer:
Python lists are built-in and can hold items of different data types. Arrays, from the array module, are more memory efficient but must hold items of the same data type, primarily used for sequences of numbers.
8. Explain Python's memory management.
Why you might get asked this:
This question probes your understanding of how Python handles memory allocation and deallocation, relevant for writing efficient applications and debugging memory issues.
How to answer:
Mention the private heap, the memory manager, and garbage collection mechanisms like reference counting and the generational garbage collector.
Example answer:
Python uses a private heap for memory management. Allocation is handled by the memory manager. Garbage collection uses reference counting to immediately reclaim memory for objects with no references, and a cyclic garbage collector handles reference cycles.
9. What are args and *kwargs in Python?
Why you might get asked this:
Checks your ability to write flexible functions that can accept a variable number of arguments, a common pattern in Python libraries and applications.
How to answer:
Explain that args collects non-keyword arguments into a tuple, and *kwargs collects keyword arguments into a dictionary.
Example answer:
args allows a function to accept an arbitrary number of positional arguments, collected into a tuple. *kwargs allows a function to accept an arbitrary number of keyword arguments, collected into a dictionary.
10. What is the difference between range() and xrange()?
Why you might get asked this:
Tests your knowledge of Python 2 vs. Python 3 differences, specifically concerning iterable generation and memory efficiency for loops. (Note: xrange is Python 2 only).
How to answer:
Explain that range() (in Python 2) returns a list, while xrange() (Python 2) returns an iterator. Clarify that Python 3's range() behaves like Python 2's xrange().
Example answer:
In Python 2, range() created a list, potentially consuming significant memory for large ranges. xrange() created an iterator, yielding numbers one by one, which was memory efficient. In Python 3, range() is an iterator, like Python 2's xrange().
11. What is the purpose of the zip() function?
Why you might get asked this:
Evaluates your familiarity with built-in functions useful for working with multiple iterables simultaneously.
How to answer:
Describe how zip() pairs elements from multiple iterables based on their index, returning an iterator of tuples.
Example answer:
The zip() function takes multiple iterables and returns an iterator of tuples. Each tuple contains elements from the input iterables corresponding to the same index, stopping when the shortest input iterable is exhausted.
12. What is inheritance in Python?
Why you might get asked this:
Checks your understanding of a fundamental concept in object-oriented programming: code reuse and establishing relationships between classes.
How to answer:
Define inheritance as one class (child/derived) acquiring attributes and methods from another class (parent/base). Mention its benefits like code reusability.
Example answer:
Inheritance is an OOP mechanism where a new class (child class) derives properties (attributes and methods) from an existing class (parent class). It promotes code reuse and allows building hierarchical relationships between classes.
13. What are generators in Python?
Why you might get asked this:
Tests your knowledge of memory-efficient ways to work with sequences, especially large ones, by generating values on the fly rather than storing them all.
How to answer:
Define a generator as a function using the yield keyword. Explain that they produce an iterator and generate values one at a time, saving memory.
Example answer:
Generators are functions that use the yield keyword. They return an iterator and generate values lazily, meaning they produce items one at a time as requested by the iterator, making them very memory efficient for large sequences.
14. What is the Global Interpreter Lock (GIL)?
Why you might get asked this:
Probes your understanding of Python's concurrency model and its limitations, particularly relevant for multi-threaded CPU-bound applications.
How to answer:
Define the GIL as a mutex protecting access to Python objects, preventing multiple native threads from executing Python bytecode simultaneously in CPython. Mention its impact on multi-threading performance.
Example answer:
The GIL is a mutex in CPython that protects Python objects, preventing multiple threads from executing Python bytecode at the exact same time within a single process. While it simplifies memory management, it can limit the performance of CPU-bound multi-threaded programs.
15. What are docstrings in Python?
Why you might get asked this:
Assesses your understanding of good coding practices, specifically how to document functions, classes, modules, and methods for clarity and discoverability.
How to answer:
Define docstrings as string literals used for documentation, placed immediately after definition lines. Explain how they can be accessed (e.g., doc).
Example answer:
Docstrings are multiline string literals used to document Python code (modules, classes, functions, methods). They are placed immediately after the definition line and are accessible at runtime via the doc attribute or help() function.
16. How can you capitalize the first letter of a string in Python?
Why you might get asked this:
A simple, practical question testing your knowledge of built-in string methods.
How to answer:
Provide the specific string method used for this purpose.
Example answer:
You can use the .capitalize() string method. It returns a new string with the first character capitalized and the rest lowercase. For example, "hello".capitalize() returns "Hello".
17. What is the difference between / (division) and // (floor division) operators in Python?
Why you might get asked this:
Tests your understanding of arithmetic operators, specifically how Python handles division and integer results.
How to answer:
Explain that / performs true division (returns a float) and // performs floor division (returns an integer, rounding down).
Example answer:
The / operator performs true division and always returns a float result (e.g., 10 / 3 is 3.33...). The // operator performs floor division, returning the largest integer less than or equal to the result (e.g., 10 // 3 is 3).
18. What is a Python decorator?
Why you might get asked this:
Probes your knowledge of advanced Python features used for metaprogramming and modifying the behavior of functions or methods concisely.
How to answer:
Define a decorator as a function that wraps another function to extend or modify its behavior without permanently altering it. Mention the @ syntax.
Example answer:
A decorator is a design pattern used to modify the behavior of a function or method. It's typically a function that takes another function as an argument, adds some functionality, and returns the modified function. The @decorator_name syntax is syntactic sugar for this.
19. What is list comprehension?
Why you might get asked this:
Tests your familiarity with Pythonic idioms for creating lists concisely, demonstrating efficiency and readability.
How to answer:
Define list comprehension as a compact way to create lists. Explain its syntax and typical use for transforming or filtering sequences.
Example answer:
List comprehension is a concise syntax to create lists. It's a powerful way to build a new list by applying an expression to each item in an iterable and optionally filtering elements. Example: [x*2 for x in range(5) if x % 2 == 0].
20. What are Python modules and packages?
Why you might get asked this:
Assesses your understanding of how Python code is organized, reused, and distributed.
How to answer:
Define a module as a single file (.py). Define a package as a directory containing modules and an init.py file to organize them hierarchically.
Example answer:
A module is a single Python file (.py) containing code (functions, classes, variables). A package is a directory containing multiple modules and a special init.py file, used to structure modules hierarchically and make them importable.
21. How do you handle exceptions in Python?
Why you might get asked this:
Fundamental question about error handling and writing robust code that can gracefully handle unexpected situations.
How to answer:
Describe the try, except, else, and finally blocks and their roles in catching and managing errors.
Example answer:
Exceptions are handled using try...except blocks. Code that might raise an error goes in try. except catches specific exceptions. else runs if no exception occurs. finally always runs, used for cleanup.
22. What is the difference between deep copy and shallow copy?
Why you might get asked this:
Tests your understanding of how complex objects are copied and the potential pitfalls with nested data structures, crucial for avoiding unintended side effects.
How to answer:
Explain that a shallow copy copies object references, while a deep copy recursively copies nested objects. Mention the copy module.
Example answer:
A shallow copy creates a new object, but inserts references to the original nested objects. A deep copy creates a new object and recursively copies all objects found in the original, resulting in a completely independent copy.
23. How can you make a Python script executable on Unix?
Why you might get asked this:
A practical question relevant for deployment and command-line scripting in Unix-like environments.
How to answer:
Explain the two steps: adding the shebang line and setting executable permissions using chmod.
Example answer:
Add a shebang line #!/usr/bin/env python3 (or your Python path) as the first line of the script. Then, grant execute permissions using chmod +x script_name.py in the terminal.
24. What are Python's key data types?
Why you might get asked this:
A basic knowledge check of the built-in data structures and primitives Python provides.
How to answer:
List the primary built-in data types, perhaps categorizing them (numeric, sequence, set, mapping).
Example answer:
Key built-in data types include Numeric (int, float, complex), Sequence (str, list, tuple, range), Set (set, frozenset), Mapping (dict), and Boolean (bool).
25. What is the difference between a set and a list?
Why you might get asked this:
Reinforces your understanding of distinct collection types, focusing on the properties of order and uniqueness.
How to answer:
Highlight the main differences: sets are unordered and contain unique elements, while lists are ordered and can contain duplicates.
Example answer:
Lists are ordered collections that can contain duplicate elements and are accessed by index ([]). Sets are unordered collections where all elements must be unique, useful for membership testing or removing duplicates ({}).
26. How do you manage package dependencies in Python?
Why you might get asked this:
Practical question about tooling and workflow in real-world Python projects, focusing on using external libraries.
How to answer:
Mention PIP (Python Package Index) as the standard package installer. Briefly touch upon dependency files like requirements.txt.
Example answer:
The standard tool is PIP (Python Package Index). You install packages using pip install package_name. Dependencies for a project are typically listed in a requirements.txt file, which can be installed using pip install -r requirements.txt.
27. What is the difference between mutable and immutable types?
Why you might get asked this:
Crucial concept impacting how variables behave and how objects are handled in memory. It affects functions, assignments, and data structure operations.
How to answer:
Define each type based on whether their state can be changed after creation. Provide examples for each.
Example answer:
Mutable types (like lists, dictionaries, sets) can be changed after creation without creating a new object. Immutable types (like strings, tuples, numbers) cannot be changed; any modification results in a new object.
28. What is the Python with statement?
Why you might get asked this:
Tests your knowledge of context managers and resource management, a Pythonic way to ensure resources are properly handled (e.g., files closed).
How to answer:
Explain its purpose in simplifying resource management (like file handling) by ensuring setup and teardown actions are automatically performed, even if errors occur.
Example answer:
The with statement is used for resource management, ensuring that setup and teardown code (like opening and closing files) is executed correctly, even if exceptions are raised. It relies on context managers implementing enter and exit methods.
29. How can Python code be written to be compatible with both Python 2 and 3?
Why you might get asked this:
Relevant if working on legacy code or projects needing broader compatibility. Shows awareness of version differences and migration strategies.
How to answer:
Mention using compatibility libraries (like six), avoiding Python 2-only syntax (print statement vs. print() function), and leveraging tools for porting code.
Example answer:
Use the future module imports (like from future import print_function), avoid deprecated Python 2 features, and write code that uses syntax valid in both versions. Libraries like six can help bridge differences.
30. What is a Python dictionary?
Why you might get asked this:
Fundamental data structure question. Dictionaries are central to many Python tasks and understanding them is key.
How to answer:
Define a dictionary as a collection of key-value pairs. Mention its unordered nature (in recent Python versions) and the requirements for keys (immutable).
Example answer:
A dictionary is an unordered collection of key-value pairs. Keys must be unique and immutable (like strings, numbers, tuples), while values can be any data type. Dictionaries provide fast lookups based on keys.
Other Tips to Prepare for a interview questions about python
Beyond memorizing answers to common interview questions about Python, effective preparation involves practice and strategy. Start by coding regularly. Work on small projects, contribute to open source, or solve problems on platforms like LeetCode or HackerRank using Python. This hands-on experience solidifies your understanding and helps you apply theoretical knowledge. As the saying goes, "The only way to learn a new programming language is by writing programs in it." Review Python's standard library documentation; knowing common modules like os, sys, collections, and re is often beneficial. Practice explaining your code and your thought process out loud. Behavioral questions are also a part of most interviews, so prepare examples demonstrating teamwork, problem-solving under pressure, and handling conflicts. Consider using tools like the Verve AI Interview Copilot to practice explaining technical concepts and get feedback on your delivery and clarity before the real interview. Verve AI Interview Copilot at https://vervecopilot.com can simulate interview scenarios, helping you refine your responses to both technical and behavioral questions. Preparing with the Verve AI Interview Copilot allows you to identify areas where your explanations might be unclear or incomplete, giving you a competitive edge.
Frequently Asked Questions
Q1: Are these questions sufficient for any Python interview?
A1: They cover common fundamentals, but interviews can include coding challenges and domain-specific questions.
Q2: Should I memorize code snippets for these questions?
A2: Focus on understanding the concepts. Be ready to write simple examples if asked, but don't just memorize.
Q3: How deep should my answers be?
A3: Provide clear, concise answers. If the interviewer asks for more detail, be prepared to elaborate.
Q4: How can I practice answering these questions?
A4: Practice explaining concepts to a friend, colleague, or use an AI tool like Verve AI Interview Copilot.
Q5: Are Python 2 vs 3 questions still relevant?
A5: Less common now, but understanding key differences like range/xrange or print is still valuable context.
Q6: What if I don't know an answer?
A6: It's okay to admit you don't know, but offer your best guess or explain how you would find the answer.
