50 Most Asked Python Interview Questions | Python Interview Questions & Answers

Introduction

This tutorial compiles the most commonly asked Python interview questions, categorized into beginner, intermediate, and advanced levels. It's designed to help you prepare effectively for your Python interviews by providing clear explanations and practical insights.

Step 1: Understanding Beginner-Level Questions

Familiarize yourself with the fundamental concepts of Python that are often covered in interviews.

1. Difference between a module and a package

   • A module is a single file (with a .py extension) containing Python code, whereas a package is a directory that can contain multiple modules and an __init__.py file.

2. Compiled vs. Interpreted Language

   • Python is an interpreted language, meaning code is executed line-by-line at runtime.

3. Benefits of Python

   • Easy to learn and use.
   • Extensive libraries and frameworks.
   • Strong community support.
   • Versatile for various applications, including web development, data analysis, and artificial intelligence.

4. Global, protected, and private attributes

   • Global attributes are accessible anywhere.
   • Protected attributes (prefix with _) are meant to be accessed within the class and its subclasses.
   • Private attributes (prefix with __) are accessible only within the class.

5. Case sensitivity

   • Yes, Python is case-sensitive; Variable and variable are different.

6. What is Pandas?

   • A powerful library for data manipulation and analysis, providing data structures like DataFrames.

7. Exception handling

   • Use try, except, and finally blocks to manage exceptions.

   try:
       # Code that may raise an exception
   except ExceptionType:
       # Code to handle the exception
   finally:
       # Code that runs regardless of an exception
   

8. For loop vs. while loop

   • for loop iterates over a sequence, while while loop continues until a condition is false.

9. Indentation in Python

   • Yes, indentation is required to define blocks of code.

10. Use of self in Python

    • self refers to the instance of the class and is used to access variables within the class.

Step 2: Intermediate-Level Questions

Build on your foundation with more complex concepts and practical applications.

11. Memory management in Python

    • Python uses reference counting and garbage collection to manage memory automatically.

12. Multiple inheritance

    • Yes, Python supports multiple inheritance, allowing a class to inherit from multiple base classes.

13. Deleting a file

    import os
    os.remove("filename.txt")
    

14. Sorting techniques

    • The sort() and sorted() functions use Timsort, which is efficient and stable.

15. List vs. Tuple

    • Lists are mutable (can be changed), while tuples are immutable (cannot be changed).

16. Slicing in Python

    • Extracting a portion of a list or string using the syntax list[start:end].

17. Multithreading

    • Achieved using the threading module to run multiple threads simultaneously.

18. Performance: List vs. Numpy Arrays

    • Numpy arrays are faster and more memory efficient for numerical data compared to Python lists.

19. Inheritance in Python

    • A mechanism allowing one class to inherit attributes and methods from another.

20. Creating classes

    class MyClass:
        def __init__(self, value):
            self.value = value
    

21. Fibonacci series program

    def fibonacci(n):
        a, b = 0, 1
        for _ in range(n):
            yield a
            a, b = b, a + b
    

22. Shallow copy vs. deep copy

    • Shallow copy creates a new object but inserts references into it, while deep copy creates a new object and recursively copies all objects.

23. Compilation and linking

    • Python compiles code to bytecode before execution, linking happens at runtime.

24. Break, continue, and pass

    • break exits a loop, continue skips to the next iteration, and pass is a no-operation placeholder.

25. PEP 8

    • The style guide for Python code, promoting readable and consistent code.

26. Expression in Python

    • A combination of values and operators that evaluates to a value.

27. Equality operator (==)

    • Used to compare two values for equality.

28. Type conversion

    • Converting one data type to another, e.g., int(), str().

29. Commonly used built-in modules

    • os, sys, math, datetime.

Step 3: Advanced-Level Questions

Dive into more sophisticated topics that may come up in interviews.

31. Difference between xrange and range

    • xrange (in Python 2) returns an iterator, while range returns a list. In Python 3, range behaves like xrange.

32. Zip function

    • Combines two or more iterables into tuples.

    zipped = zip([1, 2, 3], ['a', 'b', 'c'])
    

33. Django Architecture

    • Django follows the MTV (Model-Template-View) architecture to separate data, presentation, and business logic.

34. Runtime errors

    • Yes, runtime errors can occur during execution, e.g., division by zero.

35. Docstrings

    • Multi-line comments used to document functions, classes, and modules.

36. Capitalizing a string

    string = "hello"
    capitalized = string.capitalize()
    

37. Generators

    • Functions that return an iterable set of values, using the yield statement.

38. Comments in Python

    • Use # for single-line comments and triple quotes for multi-line comments.

39. Global Interpreter Lock (GIL)

    • A mutex that protects access to Python objects, preventing multi-threaded programs from executing multiple threads simultaneously.

40. Django vs. Flask

    • Django is a full-fledged framework, while Flask is lightweight and flexible.

41. Flask benefits

    • Easy to use and simple to get started with; great for small applications.

42. PIP

    • A package manager for installing Python packages.

43. Code compatibility

    • Use six library or write code considering both Python 2 and 3 differences.

44. Difference in operators

    • % gives the remainder, / gives a float result, and // gives the floor division result.

45. Memory deallocation

    • Python may not deallocate all memory upon exit due to unreferenced objects still being held.

46. Sets

    • Sets are unordered collections of unique elements and are mutable.

47. DataFrames vs. Series

    • DataFrames are two-dimensional, while Series are one-dimensional arrays.

48. len() function

    • Returns the number of items in an object.

Conclusion

This guide provides a comprehensive overview of Python interview questions across all levels. To enhance your understanding, consider practicing coding examples and exploring each topic further. Good luck with your Python interview preparation!