100+ Real-time Python Interview Questions and Answers [2023]

Python has become one of the most popular programming languages today with widespread use in fields like data analysis, machine learning, web development and more. As Python continues to grow in popularity, so does demand for Python developers.

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Acing your Python interview is key to landing your next dream job. This comprehensive guide covers 100+ real-world Python interview questions on various topics to help you thoroughly prepare.

We‘ve organized the questions logically by difficulty level – beginning with basic concepts before progressing to more advanced questions on complex data structures, OOP, web frameworks and more. Detailed explanations follow each question to explain the working and logic behind the concepts.

Let‘s begin!

Table of Contents

Python Basics

Q1. What is Python?

Python is an interpreted, high-level, general-purpose programming language that emphasizes code readability with its clear and concise syntax. Guido van Rossum created Python in 1991.

Q2. What are the key features of Python?

Some of Python‘s key features include:

  • Dynamically typed language (no need to declare types)
  • Automatic memory management (garbage collection)
  • Supports multiple programming paradigms (OOP, structured, functional)
  • Vast standard library and open-source ecosystem
  • Portable and can run on many platforms
  • Interpreted language allowing for rapid prototyping
  • Integrates well with other languages

Q3. What type of language is Python?

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics.

Q4. Is Python case-sensitive?

Yes, Python is case-sensitive – myfile, MyFile, and myfile are three distinct identifiers in Python.

Q5. What is PEP 8 and why is it important?

PEP 8 is Python‘s official style guide. It provides guidelines and best practices for how to format Python code to improve consistency, readability and maintainability. Adhering to PEP 8 makes code easier to understand for other Python developers.

Strings

Q6. How do you concatenate two strings in Python?

The + operator can concatenate strings in Python:

str1 = "Hello" 
str2 = "World"
str3 = str1 + " " + str2
print(str3) # "Hello World"

Q7. How are strings represented in Python?

Strings in Python are sequences of Unicode characters. They are immutable sequences. This means that when a string is created, the sequence of characters cannot be changed. We can simply reassign new strings to the same variable name.

Internally, Python optimizes strings by storing commonly used characters in a lookup table and reusing existing strings rather than creating new strings when possible.

Q8. How to format strings in Python?

Python provides powerful string formatting capabilities through the str.format() method:

name = "John"
greeting = "Hello {}!".format(name) 
print(greeting) # "Hello John!"

str.format() inserts values at placeholders marked by curly braces {}.

We can also use f-strings for string interpolation:

name = "Mary"
print(f"Hello {name}!") # "Hello Mary!"

Lists

Q9. What are some ways to create a list in Python?

Some ways to create lists in Python include:

# Empty list
my_list = []  

# List with initial values
another_list = [1, 2, 3]  

# List constructor  
yet_another = list((4, 5, 6)) 

# List comprehension 
a_list = [x for x in range(7)]

Q10. What are the common methods available on list objects?

Python provides many built-in methods that allow you to manipulate and access items in lists:

  • append() – adds item to end of list
  • extend() – adds another list‘s items to current list
  • insert() – inserts item at index
  • remove() – remove first occurrence of item
  • pop() – removes item at index (defaults to last item)
  • index() – returns first index matching item
  • count() – counts occurrences of item
  • sort()– sorts list
  • reverse() – reverses order of list

And more!

Q11. How do you traverse through all elements in a list?

To iterate through each item in a list, use Python‘s for in construct: 

colors = ["red", "green", "blue"]

for color in colors:
    print(color)

This loops through and prints each color string.

Q12. How to create a copy of a list in Python?

We can use the copy() or list() method to create a new copy of a list so that when we modify new_list, original_list remains unchanged.

For example:

original_list = [1, 2, 3]
new_list = original_list.copy() # or list(original_list) 

new_list.append(4) 

print(original_list) # [1, 2, 3]  
print(new_list) # [1, 2, 3, 4]

Dictionaries

Q13. What are Python dictionaries?

Dictionaries in Python provide an unordered collection of objects indexed by unique keys. They are mutable, meaning the contents can be modified after creation. Dictionaries are defined within braces {} and contain keys mapped to values:

point = {"x": 1, "y": 2}

Q14. How to add or update key/value pairs in a dictionary?

We can add a new key/value pair to a dictionary by assigning values to a new key: 

point = {} # empty dict
point["z"] = 3 # add new key/value
print(point) # {"z": 3}

And we can update values for a key using index notation:

point = {"x": 1, "y": 2}  
point["x"] = 0 # update x
print(point) # {"x": 0, "y": 2}

Tuples

Q15. How are tuples different from lists?

The key differences between tuples and lists are:

  • Tuples are defined using () round brackets
  • Tuples are immutable meaning they cannot be updated
  • Lists are defined using [] square brackets
  • Lists are mutable – values can be added/removed

Q16. How do you access values in a tuple?

We can use index notation to access values in a tuple:

 song = ("Bohemian Rhapsody", 1975, "Queen")

title = song[0] 
year = song[1]
band = song[2]

print(title) # "Bohemian Rhapsody"
print(year) # 1975

The first item has index 0, next has index 1 etc.

Sets

Q17. When might you use a set instead of a list?

Sets are useful over lists in cases where:

  • You want to avoid duplicate elements
  • You want to check for membership efficiently
  • The order of elements doesn‘t matter

Operations like contains checks (x in set) and removals are faster with sets due to their optimized implementations.

Q18. How are sets different from tuples and lists?

  • Sets are unordered collections of unique elements
  • Sets are mutable unlike tuples
  • Sets cannot contain duplicate elements unlike lists

Also, sets support set operations like unions and intersections.

OOP Concepts

Q19. How do you define a class in Python?

We use the class keyword to define a class in Python. A simple class looks like: 

class Person:
    pass

Q20. How do you instantiate a class?

We can create instances from a class using the class name like a function. For example: 

class Person:
    pass   

person = Person() # Instantiate Person class

This creates person as an instance of the Person class which can access attributes and methods defined in the class.

Q21. What is inheritance?

Inheritance allows a new derived class to reuse code from a parent base class. It sets up a hierarchical relationship allowing multiple classes to share common behavior generalized in the parent class.

For example, a Student class can inherit from a base Person class to automatically have access to generalized attributes like name, age etc.

Q22. What does the self keyword refer to?

Self refers to an instance being called in a class method. By convention, self is always the first parameter passed to any method in the class. It gives access to attributes and other methods on that specific instance object.

Web Frameworks

Q23. Explain Django architecture.

Django follows the Model-View-Template architectural pattern:

  • Model – Handles database access and business logic
  • View – Handles presentation logic and data formatting
  • Template – Defines visual HTML layout

Additional components include:

  • Forms (processes data input)
  • URLs (routes URLs to views)
  • Middleware (hooks into request process)

Q24. What is Flask?

Flask is a micro Python web framework. It is a minimal framework that focuses on core functionality like routing, request handling etc. but allows flexibility to choose other components like template engine and ORM. Some of its advantages are:

  • Lightweight without unnecessary components
  • Expandability through extensions
  • Embedded server for testing during development

Databases

Q25. How can I connect Python to a database like MySQL?

Python can connect to databases through SQLite which comes built-in or 3rd party connectors like mysql-connector for MySQL:

import mysql.connector

db = mysql.connector.connect(
  host="localhost",
  user="root",  
  password="password",
  database="mydatabase"
) 

cursor = db.cursor()
cursor.execute("SELECT * FROM mytable")

Parameters like host, user, password will vary depending on your database setup.

Multithreading

Q26. Why is multithreading useful in Python?

Python uses a GIL or Global Interpreter Lock which limits execution to one thread at a time even in a multi-threaded architecture. Multithreading is still useful in Python because:

  • Threads run concurrently so GIL switches between them allowing parallelized IO operations
  • Blocking operations like file reads/writes can run in parallel
  • Simpler synchronous code instead of async/await logic

This enables measurable speedups for IO-heavy tasks.

Q27. How do you create a thread in Python?

We can create and start threads using Python‘s Thread module: 

from threading import Thread

# Thread function
def func():
    print("Hello from thread")

t1 = Thread(target=func) 
t1.start() # start thread

The target parameter assigns the function func() to the thread.

Testing

Q28. What are unit tests in Python?

Unit tests are automated tests written and run by developers to ensure that a section of an application called the "unit" meets its design and requirements and works as intended.

In Python, unit testing frameworks like unittest allow for:

  • Automating testing procedures
  • Testing units in isolation away from the main application
  • Repeating and batch executing tests
  • Checking various outputs and code branches

Q29. What are some Python testing frameworks?

Some popular Python testing frameworks include:

  • Unittest – Python‘s built-in unit testing framework
  • pytest – Full-featured Python testing framework
  • Nosetests – Extension of Unittest
  • Selenium – UI testing for web apps
  • Robot Framework – Acceptance test framework

And more!

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