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Most Asked Python Interview Questions & Answers

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27th Jan, 2022
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Most Asked Python Interview Questions & Answers

Python is considered one of the easiest programming languages. It is widely used for web development, gaming applications, data analytics and visualization, and AI and machine learning. Since Python is used for multiple purposes, Python developers enjoy a massive market demand. 

If you plan to build a career in Python, you will have to prepare well for interviews. This blog has a list of the most commonly asked Python interview questions and answers.

Python Basic Questions for Freshers

Freshers are usually not asked too technical questions in the interview. The recruiter will ask you general questions about the Python language to know all theoretical concepts.

1. What is Python?

Python is an object-oriented programming language compatible with different platforms like Mac, Windows, Linux, Raspberry, etc. Python is an interpreted language which means we can execute Python codes immediately after writing them.

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2. What are the benefits of using Python language?

  • Python is a general-purpose programming language with a simple syntax. It enhances the readability of the code.
  • Since Python is an interpreted language, we can execute the instructions directly without compiling the code.
  • Another significant benefit of Python is that it is an open-source platform that anyone can freely download.
  • Moreover, the built-in data structures in Python like a dictionary, list, and tuple enhance code readability.

3. What are the different scopes in Python?

There are four different scope types in Python: local, global, module-level, and the outermost scope. The first one has local objects within it that are being used at the moment. The global scope has objects that can be accessed anytime during the code execution. The global objects in the current module come within the module-level scope. Lastly, outermost scope refers to all the built-in objects that can be called during the program.

4. What is the meaning of break, continue and pass in Python?

We use the break statement in Python to terminate the loop or exit from it. The statements after the break get the control. However, the continue statement in Python enables the continuation or execution of the next iterations. The pass statement is used when we do not want any command or code to be executed. It adds a statement for the syntax purpose but does not execute it.

5. What are the keywords in Python?

The reserved words in Python like functions, identifiers, or variables are termed as keywords. They are essential for maintaining the syntax of the programming language. Python 3.7 version has 33 keywords, including none, true, and class, continue, def, return, lambda, pass, etc.

6. Explain the difference between lists and tuples.

Both lists and tuples are a class of data structure in Python. Lists are used to store different data sets simultaneously. Similar to the arrays, the list is declared in a different language. These are dynamic. On the other hand, tuples also comprise data types separated by commas. They are static.

7. Explain different literals in Python.

Literals in Python refer to the data that is available in the form of variables and constants. There are mainly four different types of literals in Python: string, boolean, numeric, and special literals. String literals involve a sequence of characters in the code, whereas numeric literals comprise integer or float values. Boolean literals represent true and false with only two values: zero and one, respectively. Special literals are used to represent fields that have not been classified. They are represented by ‘none’ value.

Python Questions for Experienced Candidates

Interviewers ask technical Python interview questions from experienced candidates. 

1. Explain Decorators in Python.

Decorators in Python allow the extension of an already existing function. A decorator itself is a function that uses another function as an argument and returns a third function. Developers use decorators in the Python language to modify the function of a class without altering the source code. In simple terms, coders use decorators to change the behavior of a function by extending it but do not allow modification of the original function.

2. Explain the use of lambda in Python.

The Lambda function in Python is used to declare those functions in Python that do not have a name, also called Anonymous functions. We use the lambda function whenever we require the nameless function for a short interval while executing the code. Moreover, the lambda function reduces the length of the code because they are usually written in a single line.

3. Explain the difference between NumPy and SciPy.

NumPy means Numerical Python. It comprises the array data type, basic element functions like sorting, reshaping, and indexing. SpicyPy means scientific Python. It comprises various sub-packages and a collection of functions.

4. How do we copy a file in Python?

We use the copy module to copy a file or an object in Python in two ways. The first method is shallow copy that prepares a replica of the values in the original object. Shallow copy is used to keep the values when a new instance gets created. The second method is deep copy that is used to copy information from the source to the target object. Deep copy stores already copied values and offer reference to the object.

5. Explain the process of compilation and linking in Python.

We use compiling and Linking in Python to compile new extensions. In compilation, the source code is saved as a .py file and compiled into bytecode, saved as a .pyc file. Linking is the process wherein all functions with their definitions are linked together.

6. How is memory managed in Python?

Memory management in Python occurs in the private heap space that comprises all Python objects and data structures. The programmers do not have access to the private heap space. It is only available to interpreters.

Tips to Prepare for Python Interview Questions and Answers

Along with asking you theoretical questions related to Python in the interview, the recruiter might also ask you to write down a practical code on a piece of paper. They might also give a situation, ask you to analyze the same, and offer a practical solution with the help of Python. 

  • You must know how to write Python code on paper or whiteboard. Even if you are being interviewed for a fresher position, it is best to practice simple Python codes on a sheet of paper. Many companies might not offer a technical setup to the candidates during the interview. Therefore, they can ask you to write the code on paper or whiteboard.
  • If you have worked on some practical Python projects, plug it subtly while answering the questions. You can explain your answer with the help of examples or personal experiences. It helps the interviewer realize that you have problem-solving skills that make you a suitable candidate for the job.
  • Another crucial tip for Python interview questions is that you should know about the various Python data types like strings, sets, and tuples and when to use each one of them.
  • While preparing for a Python interview question, you should also go through the purpose of generators in Python and how to use them. Also, focus on Python algorithms and data structures.

How to Prepare For Python Interview Questions and answers?

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Python interviews can be tough to crack due to the vast number of technicalities the interviewer might ask you. The best approach to cracking Python interview questions is to first focus on the concepts and then on practical learning. 

You can learn both theoretical and practical aspects of Python with upGrad’s Professional Certificate in Data Science and Business Analytics from the University of Maryland. This course helps you learn Python from scratch. Even if you are new to programming and coding, upGrad will offer you a two-week preparatory course so that you can pick up on the basics of programming. you will learn about various tools like Python, SQL,, while working on multiple industry projects.

Check out our other data science courses at upGrad. We hope this helps!

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Pavan Vadapalli

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Director of Engineering @ upGrad. Motivated to leverage technology to solve problems. Seasoned leader for startups and fast moving orgs. Working on solving problems of scale and long term technology strategy.
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