Top Python interview questions and answers

In this article, we’ll explore some of the top Python interview questions that may arise during job interviews and their answers to help you prepare and excel in your next Python interview. 

Whether you’re a beginner or an experienced Python developer, these questions and answers will be a valuable resource to help you brush up on your Python knowledge and showcase your expertise to potential employers.

Why are Python developers in demand? 

Python is one of the most popular programming languages, widely used for applications such as web development, data analysis, artificial intelligence, and scientific computing. Due to its versatility, simplicity, and readability, Python has become a preferred language for many software developers and engineers.

Python developers are always in demand because of the following reasons:

Ease of use

Python is a reasonably straightforward language to learn and use, with many modules and frameworks that make it simple to develop complex applications with a small amount of code. 

Versatility

Python’s versatility makes it suitable for various tasks, including web development, data analysis, machine learning, and scientific computing.

Popularity

Python is one of the most widely used programming languages in the world. In addition, a huge and vibrant developer community means that many tools and assistance are accessible.

Employment opportunities

There is a great need for proficient Python developers across various industries, including technology, finance, healthcare, and government, so there are numerous job openings and competitive pay rates for qualified candidates.

Python interview coding questions

Basic

1. What are the current two most popular versions of Python? The two most popular Python versions that are presently in use are Python 2 and Python 3.
2. What does a Python comment mean? A line of text the Python interpreter ignores is a comment. It’s employed to provide explanatory notes in code.
3. What does a Python variable mean? In Python, a variable is a specifically designated region in memory where a value is kept.
4. In Python, how do you declare and initialise a variable? You define and initialise a variable in Python by assigning a value to it using the = operator. For instance, x = 5.
5. What does a Python if statement mean? If a specific condition is met, a code block is executed in Python using an if statement. The if keyword is used, followed by the condition, a colon, and the indented section of the executable code.
6. What does a Python for loop do? In Python, a for loop is used to repeatedly iterate over a list of items or a string. The for keyword is used, followed by a variable name, the in keyword, the sequence to be iterated through, a colon, and the block of indented code that will be performed.
7. What does a Python function do? A Python function is a section of code that completes a certain task. To run its code and return a result, it can be called from other program areas.
8. How do you define a function? You use the def keyword, the function name, a pair of parentheses, and a colon to define a function. The indented block of code that makes up the function is then written.
9. What does a Python module mean? A file containing Python code that specifies functions, variables, and other objects that may be used in other sections of a program is known as a module in the language.
10. In Python, how do you import a module? In Python, you import a module by using the import keyword and the module name. For example, import math.

Intermediate

1. What is a list comprehension in Python? A list comprehension is a succinct method for building a new list from an iterable that already exists, like a list or a range.
2. What does a Python set mean? In Python, a set is an unordered grouping of distinct elements.
3. What does a Python dictionary mean? In Python, a dictionary is a set of key-value pairings where each key uniquely identifies a value.
4. What exactly are pickling and unpickling? The Python object is accepted by the Pickle module, which then uses the dump method to transform it into a string representation and store it in a file. Pickling is the name of this procedure. On the other side, unpickling refers to the act of obtaining the original Python objects from the string representation.
5. What does a Python object mean? In Python, an object is a class instance. It has a unique set of properties and methods that may be accessed and modified.
6. What is inheritance? In Python, inheritance is a mechanism that allows a new class to be based on an existing class and inherit its characteristics and methods.
7. What exactly is polymorphism in Python? Polymorphism is a Python concept that states that objects of various classes can be utilised interchangeably if they have the same methods and properties.
8. What is the distinction between Python’s __init__() and __new__() methods? The __init__() method is used to initialise an object’s attributes once it has been constructed. The __new__() method is used before an object is formed.
9. Is Python capable of supporting multiple inheritance? Absolutely, Python offers users a wide range of support for inheritance and its application, unlike Java. When a class is created from more than one distinct parent class, this is referred to as multiple inheritance. This offers users a lot of functionality and benefits.
10. What is scope resolution?

In Python, a scope is a section of code where an object is still applicable. Every single Python object has a certain scope within which it operates. Although namespaces are used to uniquely identify each object in a program, these namespaces also have a defined scope where their objects may be used without a prefix. It establishes how long a variable is accessible.

Advanced

1. What does a Python decorator do? In Python, a decorator is a function that accepts an input function and outputs a new function with modified behaviour. Decorators are frequently employed to extend the functionality of already-written functions or methods without altering the original source code.
2. What does a Python closure mean? A closure in Python is a function object that has access to variables in its enclosing lexical scope, even after that scope has been closed. Closures are often used to create function factories or to create functions with a persistent state.
3. What is a generator in Python? A generator in Python is a special type of iterator that generates values on-the-fly rather than storing them in memory. Generators are often used to process large datasets or to create infinite sequences.
4. What is the asyncio module in Python? The asyncio module in Python is a library for writing concurrent code using coroutines and event loops. It is often used for networking and web programming.
5. What is the typing module in Python? Python’s typing module contains a collection of classes and procedures for specifying and enforcing type annotations in Python code. It is frequently used to create more resilient and maintainable code.
6. What is the Python pickle module? The pickle module in Python is a module for serialising and deserialising Python objects into a stream of bytes. It is often used to save and load Python objects to and from a disk or network.
7. What is a context manager in Python? A context manager in Python is an object that defines a __enter__() method and a __exit__() method, which is used to set up and tear down a context for a block of code. Context managers are often used for resource allocation and cleanup, such as opening and closing files or acquiring and releasing locks.
8. What does a Python metaclass do? In Python, a class that specifies the behaviour of other classes is known as a metaclass. The behaviour of class formation, such as adding or modifying class attributes or methods, is frequently modified using metaclasses.
9. What does the Python GIL mean? One thread at a time can only execute Python bytecode thanks to the Python GIL, or Global Interpreter Lock, mechanism. This can make creating concurrent code easier and also limits the performance of multi-threaded Python apps. 
10. What distinguishes Python’s asyncio from threading? asyncio is a library for writing concurrent code using coroutines and event loops, while threading is a built-in module for creating and managing threads in Python. asyncio is often used for networking and web programming, while threading is often used for parallelism and concurrent I/O operations. Unlike threading, asyncio can use a single thread to handle multiple I/O operations, which can be more efficient in some cases.

Scenario based   

Python function

You are given a list of numbers, and you need to write a Python function to return the sum of all the even numbers in the list. Write the function.

def sum_of_evens(lst):
    even_sum = 0
    for num in lst:
        if num % 2 == 0:
            even_sum += num
    return even_sum

Python library

You’re working on a web application project that calls for you to send emails to users. To send emails in Python, which Python library would you use?

Python’s smtplib package is used to send emails.

Pandas DataFrame

You’re working on a data science project that requires you to import a CSV file into a Pandas DataFrame. Create the code that will read the CSV file.

import pandas as pd
df = pd.read_csv('filename.csv')

Dictionary

You have a dictionary in which the keys represent names and the values indicate ages. Create a Python function that returns the name of the dictionary’s oldest individual.

def oldest_person(dictionary):
    oldest_age = 0
    oldest_name = ''
    for name, age in dictionary.items():
        if age > oldest_age:
            oldest_age = age
            oldest_name = name
    return oldest_name

Training and testing sets

You are developing a machine learning model and must divide your data into training and testing sets. Which Python library would you recommend for this task?

In Python, the scikit-learn module is often used to divide data into training and testing sets.

Flask Framework

You’re developing a web application with the Flask framework and need to show a webpage with a form that accepts user input. To display the form, write the Flask code.

from flask import Flask, render_template, request
app = Flask(__name__)
@app.route('/')
def form():
    return render_template('form.html')
@app.route('/submit', methods=['POST'])
def submit():
    input_value = request.form['input_name']
    return f'The user input is: {input_value}'

CSV file

Consider the following scenario: You are writing a Python script that receives data from a database and publishes it to a CSV file. To write data to a CSV file, which Python module would you use?

In Python, the csv library is extensively used for reading and writing data to CSV files.

Generate random numbers

Assume you’re working on a project that requires you to generate random numbers. Which Python library would you use in Python to create random numbers?

In Python, the random library is used to generate random numbers.

List Median

You have a list of numbers and need to develop a Python function to return the list’s median. Make the function.

def median(lst):
    lst.sort()
    n = len(lst)
    if n % 2 == 0:
        return (lst[n//2 - 1] + lst[n//2]) / 2
    else:
        return lst[n//2]

Strings

You have a list of strings and need to sort the list by the length of each string. Write the Python code to sort the list.

lst = ['apple', 'orange', 'banana', 'kiwi']
sorted_lst = sorted(lst, key=len)
print(sorted_lst) # Output: ['kiwi', 'apple', 'banana', 'orange']

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Tips for preparing for a Python interview

Here are some tips for preparing for a Python interview:

Review the basics

Make sure you have a strong foundation in Python basics, such as data types, variables, functions, loops, and conditional statements. Review Python syntax and understand how to write clean, readable code.

Study data structures and algorithms

Data structures and algorithms are essential components of many Python applications. Study common data structures such as lists, dictionaries, and sets, and practice implementing algorithms such as sorting and searching.

Practice with coding challenges

To build your coding skills, practice coding challenges on sites like LeetCode, HackerRank, and CodeWars. These platforms offer a variety of coding challenges at different difficulty levels that will help you improve your coding skills and boost your confidence.

Understand Object-Oriented Programming

Object-oriented programming (OOP) is a fundamental concept in Python. Study OOP concepts such as classes, objects, inheritance, and polymorphism, and practice implementing OOP principles in your code.

Learn popular Python libraries and frameworks

Familiarise yourself with popular Python libraries and frameworks, such as NumPy, Pandas, Matplotlib, Flask, and Django. Understand how these libraries and frameworks work and their use cases.

Practice interview questions

Review common Python interview questions and practice answering them. Use online resources and books to better understand what to expect in a Python interview.

Showcase your projects

Prepare a portfolio of your Python projects to show the interviewer. This will give them a better idea of your skills and experience and demonstrate your passion for Python.

Be prepared to talk about soft skills

In addition to technical skills, employers are looking for candidates with strong soft skills, such as communication, teamwork, and problem-solving. Be prepared to discuss how you used these skills in your previous work experience or projects.

Be confident and positive

Remember to be confident and positive during the interview. Show enthusiasm for Python and the company you are interviewing for. Be prepared to ask questions and demonstrate your interest in the company and the role.

By following these tips, you will be well-prepared for your Python interview and have a better chance of impressing the interviewer and landing the job.

Resources to prepare for Python interview 

Preparing for a Python interview can be daunting, but here are some resources that can help you get started:

Brush up on your Python programming language fundamentals 

Make sure to review all the core concepts of coding with Python, including control structures, functions and object-oriented principles such as classes & instances.

Get hands-on practice through tutorials & challenges 

To gain confidence in writing programs, it’s important to work on yourself via online courses or platforms such as Code Institute.

These offer step-by-step guidance to master certain areas of Python development.

Reading material is essential 

Staying updated will definitely come in handy during an actual session, so try finding relevant books related to different aspects of coding, like algorithms and data structure learning, which may include popular titles like “Problem Solving with Algorithms and Data Structures” by Miller and Ranum.

Other materials could include tech blogs from influential authors within the industry discussing trending topics about machine learning etc., accompanied often by example code snippets for better understanding too!

Video lectures 

Video lectures on specialised topics might also prove useful since they present information from different angles than text formats. There’s plenty available across various websites depending upon what field interests you most likely pertaining.

Practising mock tests 

Practising mock tests always helps prepare one mentally, and making note of any commonly asked questions would go a long way later when addressing real outcomes before getting into technical details.

Tricky question types & strategies for answering them

Tricky questions can be difficult to answer, often requiring thinking quickly and creatively. Here are some strategies to help when answering tricky questions:

Take a moment before responding 

Try not to immediately jump into an answer without assessing the question. It’s usually best practice to pause for at least five seconds, or however long is necessary, to better understand what the asker is really after with the question.

Ask clarifying questions 

If something about the question confuses you or isn’t clear, it can be helpful to inquire further via additional questioning. This lets your interviewer know that you care about providing the most accurate response and demonstrate this through the use of active listening skills.

Break down complex topics

When faced with wide open-end questions such as specific “explain X topic in depth,” break down the information by focusing on one particular aspect at a time in a complex phenomenon so you don’t become overwhelmed. 

Provide one key point per sentence, allowing yourself a chance for an additional explanation if needed. Then, end each thought with structure and closure, which directs your thinking forward while keeping track of limiting time constraints on the formal, polite address. 

Common mistakes during a Python interview

Some common mistakes one should avoid during a Python interview are: 

Failing to explain your code properly

It is important to articulate clearly the logic behind any solution you provide and talk through potential problems or edge cases.

Not being familiar with available libraries 

Having a good understanding of commonly used Python packages can help minimise coding time and prevent unnecessary errors due to unfamiliarity with library APIs, methods etc.

Poor algorithm implementation 

While speed may not always be essential during an interview, providing a basic solution in the shortest amount of time without compromising its correctness will demonstrate your problem-solving skills and familiarity with algorithms that might help solve various scenarios quickly and efficiently.

Having a weak grasp on Object Oriented Programming (OOP)

Using OOP principles such as encapsulation, inheritance, polymorphism, composition etc., can result in more efficient implementations since they allow for easier reusability and scalability by creating smaller chunks of better-organised code blocks

Being unable to debug errors quickly  

Developing debugging techniques and getting comfortable locating subtle mistakes within code are extremely useful skills which go beyond just writing working solutions.

Not studying enough 

Ensure you brush up on the language fundamentals and read through all relevant documentation before your interview. Don’t rely on memorising existing code examples, as that won’t give any insight into how well you know Python.

Poor time management 

During a coding-oriented job interview, it is essential to manage your time properly during problem-solving tasks or coding challenges so that you can complete them in an efficient manner without rushing them at the end of the session.

Incorrect or incomplete answers

Ensure that once problems are solved, you take extra caution when testing out and debugging codes for mistakes or errors before handing over results to your interviewer – this will demonstrate proper diligence from start to finish!

Conclusion

Interviewing with confidence and brilliance is a skill. You may be an excellent programmer, but that is only a tiny aspect of the picture. You may not pass a few interviews, but following a solid strategy will help you in the long run. 

Being enthusiastic is a key factor that will significantly impact your interview results. Practice is also important. Practice is always beneficial. Brush up on all the common interview concepts before practising various Python interview questions and answers. 

Interviewers can also assist you if you can talk and get along properly. Always ask questions and discuss both brute-force and optimised solutions.

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