Google Python Interview Questions You Should Prepare

Python is an easy-to-learn, high-level, indentation-sensitive, general-purpose programming language. Its design philosophy is big on readability and supports an object-oriented approach. We can often solve coding questions based on data structures and algorithms quite succinctly and cleanly in Python. Given the popularity and importance of Python, you can expect high-quality Python interview questions in your Google interview.

What Do Experts Say?

"I chose Python as a working title for the project, being in a slightly irreverent mood, and a big fan of Monty Python's Flying Circus."

- Guido van Rossum

(Creator of Python)

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This article focuses on Google Python interview questions to help you prepare for your next Python interview at Google. Read ahead to learn more!

In this article, we’ll cover:

• Top Google Python Interview Questions and Answers
• Sample Google Python Interview Questions for Practice
• Google Python Interview Questions for Experienced Professionals
• Google Python Coding Interview Questions
• FAQs About Google Python Interview Questions

Top Google Python Interview Questions and Answers

We’ll begin with some sample Google Python interview questions and answers to get a basic idea of what to expect.

Q1. How would you convert a string to all lowercase or uppercase? How would you capitalize the first letter of the string?

We can use the lower() function to convert a string to lowercase. And for converting a string to uppercase, we can use the upper() function. Lastly, we can use the capitalize() method to capitalize the first letter of a string.

Q2. What do you know about self in Python?

Self is an instance/object of a class and is explicitly included in Python as the first parameter, unlike in Java, where it’s optional. In the init method, self refers to the newly created object. In methods other than init, self refers to the object whose method was called.

Q3. Define a lambda function, an iterator, and a generator in Python.

A lambda function refers to an anonymous function with any number of parameters but can only have a single statement. An iterator is an object that we can iterate upon/traverse through. Lastly, a generator is a function that returns an iterable set of items.

Q4. What is __init__?

__init__  represents a method/constructor in Python, and all classes have an __init__ method. This __init__ method is automatically called to allocate memory whenever a new object or instance of a class is created.

Q5. How would you delete files in Python? What are Python Packages?

To delete a file in Python, we can import the OS Module and then use the os.remove() function to delete the files. Python packages represent namespaces that contain several modules.

Recommended Reading:How to Crack Python Coding Interviews

Sample Google Python Interview Questions for Practice

Here are some Google Python interview questions. Ensure you can solve them before your interview:

1. What is the difference between lists and tuples in Python?
2. What are the key features of Python?
3. What type of language is Python?
4. How is Python an interpreted language?
5. What do you know about pep 8?
6. How is memory managed in Python?
7. Describe the usage of the strip() function in Python.
8. What do you know about namespace in Python?
9. What do you know about Python PATH?
10. Describe the usage of the replace() function in Python.
11. What are Python modules?
12. Describe the usage of the eval() function in Python.
13. What are local and global variables in Python?
14. What do you know about the map function in Python?
15. What are the min() and max() functions in Python? What do they do?
16. Describe the usage of the join() function in Python.
17. What do you know about pickling and unpickling?
18. How would you generate random numbers in Python?
19. Explain split(), sub(), subn() methods of “re” module in Python.
20. Describe the usage of the getattr() function in Python.
21. How would you capitalize the first letter of string?
22. What are the upper() and lower() functions in Python?
23. What do you know about using help() and dir() functions in Python?
24. Describe the usage of the reduce() function in Python.
25. What are docstrings in Python?
26. How would you convert a string to all lowercase?
27. Describe the usage of the round() function in Python.
28. How would you randomize the items of a list in place in Python?
29. Describe the usage of the sorted() function in Python.
30. What are Python iterators?
31. How does break, continue and pass work?
32. What do you know about the difference between range & xrange?
33. Describe the usage of the split() function in Python.
34. What do you know about the difference between Python Arrays and lists?
35. Is indentation required in Python?

Learn about the Top 16 Functions in Python you should know

Google Python Interview Questions for Experienced Professionals

Let’s move a step further with some advanced Google Python interview questions for experienced developers:

1. How would you install Python on Windows and set the path variable?
2. What do you know about the difference between deep and shallow copy?
3. What are the benefits of using NumPy arrays over nested Python lists?
4. What are the built-in types of Python?
5. What are negative indexes, and why are they used?
6. What do you know about self in Python?
7. What do you know about a lambda function?
8. What do you know about __init__?
9. How would you get data from websites with Python web scraping?
10. Talk about the experience you have had for the last few years in Python?
11. Algorithms and Data Structures, Pythons Dicts - MultiValue Dicts, Range and Xrange, Iterators and Generators, Decorators
12. How would you use the ternary operators in Python?
13. Why isn’t all the memory de-allocated when Python exits?
14. Is Python NumPy better than lists?
15. Explain what Flask is and its benefits?
16. Is Django better than Flask?
17. Mention the differences between Django, Pyramid, and Flask.
18. Discuss Django architecture.
19. What do you know about the difference between NumPy and SciPy?
20. What do you know about monkey patching in Python?
21. Explain Inheritance in Python with an example.
22. What do you know about split used for?
23. What do you know about the process of compilation and linking in Python?
24. Explain split(), sub(), subn() methods of “re” module in Python.
25. What do *args, **kwargs mean, and why do we use them?

Here are some more Advanced Python Interview Questions and Answers for you to practice.

Google Python Coding Interview Questions

Lastly, here are some technical Google Python interview questions. Ensure you can solve them before your coding interview:

1. You are required to scrap data from IMDb's top 150 movies page with only the fields movie name, year, and rating.
2. Write code to check if a number is prime in Python.
3. Give an example of how you can write a view in Django?
4. Write code to execute the Bubble sort algorithm in Python.
5. Write a sorting algorithm for a numerical dataset in Python.
6. Write code to produce the Fibonacci series in Python.
7. How do you calculate percentiles with Python/ NumPy?
8. Write code to produce a star triangle in Python.
9. Write a one-line code that works even if the file is too big for the memory and counts the number of capital letters in a file.
10. Write code to check if a sequence is a Palindrome in Python.
11. How would you make 3D plots/visualizations using NumPy/SciPy?
12. Given its URL address, how would you save an image locally using Python?
13. How would you get the Google cache age of any URL or web page?
14. How would you get indices of N maximum values in a NumPy array?

These are some Advanced Python Coding Challenges that you can solve to nail your coding interview.

We hope that this list of Google Python interview questions will help you crack your tech interview. Practice some mock interviews and read our guide to 12 key preparation tips to crack an interview to prepare better.

FAQs About Google Python Interview Questions

Q1. Can I use Python in Google interviews?

Yes, you can use Python in your Google interview. Python can help you convey some comprehension and approach checkpoints faster in an interview.

Q2. How to prepare for the Google Python interview?

You can start by learning about the Google interview process to see what they’re looking for and what they value. Then, train yourself in that direction. You can start your training by designing your plan based on your starting point, how much time you have, and the areas that require most of your attention. Following this, the standard advice of practicing DSA coding questions, resting as needed, taking mock interviews, etc., applies well.

Q3. Are Google interviews hard?

Yes, you can expect Google coding interviews to be more challenging than average and the questions to use a wide range of topics. The questions are unique to Google and test your understanding. So the questions often don’t precisely follow a standard question pattern you can memorize. Note that with good preparation, challenging questions feel like engaging questions.

Q4. What do Google interviewers look for?

Google interviewers look for and grade you on their four principles of cognitive ability, leadership, role-related knowledge, and Googleyness.

Q5. What are some ML algorithms used in Python?

ML algorithms commonly used in Python include linear regression, logistic regression, naive Bayes, decision tree, and Support Vector Machines (SVM).

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