Python is one of the leading and most widely sought-after programming languages. The language is preferred for its easy syntax and wide-ranging applications, especially in the development of modern technology tools including Artificial Intelligence, Machine learning, Computer Vision, and others.

However, with the high demand for professional Python developers, there’s also steep competition. If you are looking to prepare for your next job interview, make sure to go prepared with detailed Python interview questions. Here in this blog, we have come up with the most comprehensive list of Python interview questions and answers, to serve as your one-stop resource for interview preparation. For better readability and robust preparation, we have segregated the Python interview questions concerning the experience levels including; python interview questions for fresh graduates, mid-career professionals, and for experienced professions.

So, let’s not waste any more time and start our comprehensive Python interview questions and answers resource.

Top Python Interview Questions and Answers for Fresh Graduates

Q1. Explain the difference between list and tuples in Python?

Ans.

LIST	TUPLES
In python, Lists are editable or mutable	Tuples in Python are not editable or immutable
Generally, Lists are slower as compared to Tuples	Tuples are fasters in comparison to Lists

Q2. What are Python’s key features?

• Python is a leading programming language. It’s an interpreted language, which means that it doesn’t need to be compiled before running (unlike C, and its variant languages). Some of the other examples of interpreted language include PHP and Ruby
• The language can be typed “Dynamically”, which means that users aren’t required to state the types of variables at the time of declaration. For instance, users can do things like A = 123, and then again A = “john” without any errors
• Python is highly compatible / well-suited to object-oriented programming. The language enables the easy definition of classes, as well as, inheritance and composition. The language doesn’t come with access to specifiers unlike some of the other languages (C++, etc.)
• As “first-class objects”, functions can be assigned to variables in Python
• In Python, classes are also “first-class objects”
• As a high-level language, writing codes in Python is much faster than various other compiled languages. However, funning the Python programs is often slower as compared to compiled languages
• Python allows integration of C-based extensions, which can be used to optimize the running of Python programs (Numpy package of Python is a great example)
• Python is widely used across various advanced fields including; scientific modeling, artificial intelligence, machine learning, computer vision, big data, web application, automation, and others

Q3. Is Python a programming language or scripting language?

Ans. Python is a general-purpose programming language, however, it also has the capability to be used as a scripting language. The Python Scripting Tutorial can be used to know more about Python capabilities as a scripting language.

Q4. Is Python an interpreted Language?

Ans. Yes. Python is an interpreted language, as it doesn’t need to be compiled before running.

Q5. What is pep 8?

Ans. PEP or Python Enhancement Proposal refers to the set of rules in Python that details the formatting of Python codes for better readability.

Q6. Explain memory management in Python?

Ans: The Memory in Python is managed by “Python Private Heap Space”, where all the data structures and objects of the language are located. The private heap space is managed by the Python interpreter, whereas, the programmer doesn’t have access to it.

– The heap space for Python memory management is taken care of by Python’s memory manager. Whereas programmers are given limited access to tools through core API to write codes

– The garbage collector in Python takes care of all the deleted, unused memory by recycling or removing the items, so as to ensure the availability of heap space

Q7. Explain namespace in Python?

Ans. Namespace is python refers to the naming system. The Namespace function of the language ensures that there are no naming conflicts

Q8, Explain PythonPath?

Ans. Python Path refers to an environment variable. It is mostly used to check the availability of imported modules in multiple directories. PythonPath variable is also used by the interpreter to determine the module to be loaded

Q9. Name some of the commonly used modules in Python?

Ans. Python modules represent files with python codes. The modules are .py files and comprise executable codes. The module may comprise variable or function classes. Some of the more commonly used Python modules include; 

• JSON
• Sys
• Random
• Data time
• Math
• OS

Q10. Explain global and local variables in Python?

Local Variables

– Local variables are variables declared inside a function. These variables are not present in the global space, rather only in local space

Global Variables

Global variables are variables declared outside a function (global space). These variables can be accessed through any function in the code

Q11. Is python case sensitive?

Ans. Yes. Python is a case sensitive language

Q12. Explain the type conversion in Python?

Ans. In Python, the conversion of one type of data into another type is known as type conversion.

Some of the common type conversion functions in Python includes;

Tuple () – A type function used for conversion to a tuple

Int () – used for conversion of any data type into an integer

Set () – A function used to covert to set

List () – A function used to convert any data type into a list

Q13. How to install Python on Windows?

Ans. Following steps can be followed to install Python on Windows;

– Download python from the website

– Installation of the language on the PC (to check out the location of Python installation on your PC, write “CMD Python” in the command prompt

– Once installed, go to the advanced system settings and add a new variable named Python_Name. Now, paste the “installation location” of Python to the Python_Name variable

– Select the Python_Name variable and choose “edit”. Then insert a semicolon at the end of the value (in case it’s not present already) and lastly type “%Python_HOME%”

Q14. Do Python Programs need indentation?

Ans. Yes. Indentations are compulsive for Python programs and are used to specify a coding block. An indented block comprises all the functions, classes, and codes within loops. The indentation is usually done using four space character. Without precise indentation, a python program may through errors or not execute properly. 

Q15. Explain differences between Arrays and Lists in Python?

Ans. Arrays and Lists are used to store data in Python. While both of them have the same data storage ways, arrays are only capable to hold a single data type element, whereas, Lists are capable to hold multiple data type elements.

Q16. What are the functions in Python?

Ans. In Python, “Function” represents a block of code that can be executed only upon calling. The “Def” keyword is used to define the Function in Python.

Q17. Define _Init_ in Python?

Ans. In Python, _init_ is a constructor or method. The _init_ is used to allocated memory in any case where a new object is created.

Q18. Explain Lambda function in Python?

Ans. Lambda is also known as an anonymous function in Python. The Lambda function can only have one statement, along with any number of parameters.

Q19. Explain Self in Python?

Ans. Self represents an object or instance of a class, which unlike java (where it’s only an optional parameter) is explicitly included as the first parameter. The Self function enables easy differentiation for class methods and attributes with local variables

Q20. Explain the working of break, continue, and pass in Python?

Ans. 

Break:

Break enable loop termination, in case a specific condition is met and the control is passed on to the next statement.

Continue:

The function enables skipping part of the loop in case some specific condition is met, and the control is reverted to the beginning of the loop

Pass:

Pass is a null operation that is used to keep a block of code syntactically, however, skipping its execution.

Q21. Explain [::-1}?

Ans: [::-1] is used to reverse the order of a sequence or an array

Q22. Explain Python iterators?

Ans. In Python, iterators referred to the objects which can be iterated upon or traversed through.

Q23. Explain the process of generating random numbers in Python?

Ans. Random numbers can be generated by using “Random Module”, which is a standard module in Python.

Q24. How can you generate random numbers in Python?

Ans: Random module is the standard module that is used to generate a random number. The method is defined as:

Q25. Explain the difference between range and xrange?

Ans. In Python, range and xrange are much similar in terms of functionality. Both range and xrange enable the generation of integers to be used, however, you like. However, the difference between the two is that with “range” a “python list object” is returned, whereas, “xrange” returns a “xrange object”.

This means that unlike lists generated by range, the integers generated by xrange aren’t static lists. Contrarily, xrange generates values as needed by the programmer by using a specific technique “yielding”, which uses a specific type of object called “generators”. This means that xrange is the right function to be used when you are looking to generate a list of massive range (say one billion).

Best Python Interview Questions and Answers for Intermediate level

Ok, now that we are done with Python interview questions and answers for fresh graduates, let’s pull the bar a little higher. Let’s now move on to Python interview questions and answers for Intermediate level (mid-career professionals)

Q1. How would you write a comment in Python?

Ans. In Python, comments can be inserted by writing the “#” character at the beginning of the sentence. However, comments can also be added in Python using docstrings.

Q2. Explain pickling and unpickling in Python?

Ans. The process of pickling includes taking up a python object (any object) and dumping it to a file after converting it into a string. The pickling process is done using the “Pickle Module”.

The Unpickling process includes retrieval of “original python objects” from the stored strings.

Q3. Explain generators in Python?

Ans. Generator in Python represents functions that return an iterable set of items

Q4. How to capitalize the first letter of a string in Python?

Ans. The capitalize () method is used in Python to capitalize the first letter of the string. In the case where a string is already started with a capital letter, the method returns the original string.

Q5. How to convert a string into all lowercase in Python?

Ans. The lower () function is used in Python to convert a string to all lowercase

Q6. Explain the method of commenting multiple lines in Python?

Ans. To comment multiple lines (lines that appear in more than one line) needs to be prefixed by “#”. Another shortcut method that can be used to comment multi-lines in Python includes; holding “CTRL Key” and left-click on every place where you need to add comment and type “#” only one time. This way, “#” will be included at all lines where you need to insert the comment.

Q7. Explain docstrings in Python?

Ans. Docstrings may appear to be similar to comments, however, in essence, these are documentation strings and can be inserted within triple quotes. Since Docstrings can’t be assigned to any variable, thereby at times these can also be used for comments.

Q8. Explain the purpose of “is”, “not, and “in” operators?

Ans. Operators in Python are special functions that are able to take-up single or multiple values to generate corresponding results.

• Is: the “is” operator returns “true” in case 2 “operands” are true
• Not: the “not” operator returns the inverse of the Boolean value
• In: the “In” operator is used to check the presence of specific elements in a sequence

Q9. Explain the use of Dir () and help () in Python?

Ans. Int () and Dir () functions in Python are used to view the consolidated dump of built-in functions and can be accessed through the Python Interpreter.

• Help () function: the function is primarily used to display the Docstring (documentation strings), however, at times it also enables programmers to access help related to attributes, modules, keywords, and others
• Dir () function: the dir () function is primarily used to display the defined symbols

Q10. Why the entire memory isn’t de-allocated when Python exits?

Ans: 

• At any time when Python exits the memory isn’t completely de-allocated or freed especially modules with circular references to objects referenced from the global namespace or other objects
• The portions of memory that are reserved by the C library are impossible to de-allocate or freed
• Apart from the above-mentioned parts, the inner cleanup mechanism of Python will de-allocate and free all other objects from the memory

Q11. What is a dictionary in Python?

Ans. Dictionary in Python represents the one-on-one relationship between keys and values and is comprised of built-in data types. The dictionary in Python will comprise of keys and their corresponding values.

Q12. Explain the usage of ternary operators in Python?

Ans. Ternary operators in Python are used to show conditional statements. These operators comprise of “True” or “False” values along with a statement that has to be evaluated for the given condition.

Q13. What are the meaning and use of *args, **kwargs?

Ans. *args in Python is used in instances where the number of arguments that will be passed to a function isn’t quantified or when a store list or tuple has to pass to a function.

**kwargs is used in instances when the number of keyword arguments to be passed to a function is not quantified. It can also be used to pass the dictionary values as keyword arguments.

While args and kwargs are convention identifiers and you may also use others like *john or *Sophia for that purpose, however, those aren’t recommended.

Q14. Explain Len ()?

Ans. In Python, Len () is used to determine the length of an array, string, or others.

Q15. What are Split (), Sub (), and subn () methods in Python?

Ans. Python’s re-module offers three different methods to modify the strings including;

• Split () – this method “split” any given string into a list using a regex pattern
• Sub () – is used to identify and replace all the substrings with regex pattern matches with different string
• Subn () – similar to sub (), this method identifies, replace, and return the new string

Q16. Explain negative indexes in Python?

Ans. In Python, the sequences are indexes as strings that can be positive or negative. Positive indexes start with “0” as the first index followed by “1” as the second index and it keeps going on infinitely.

For negative strings, the index with “-1”, represents the last string, followed by “-2” that represents the “penultimate” index and the sequence carry forward infinitely.

The negative index in Python is mostly used to remove new line spaces, as well as, to represent in string in the correct order.

Q17. What are Python packages?

Ans. In Python, namespaces are packages that comprise multiple modules

Q18. How to delete the files in Python?

Ans. To delete files in Python, you would have to import the OS module and use the os.remove() function.

Q19. List the built-in types of Python?

Ans. Some of the built-in types in Python includes;

• Boolean
• Complex numbers
• Integers
• Built-in functions
• Floating point
• Strings

Q20. What’s the benefit of NumPy over “nested” Python lists?

Ans. 

• Python lists may be efficient general-purpose containers, however, they come with certain limitations like not support “vectorized” operations (elementwise multiplication, addition, etc.). Also, the Python lists have to store type information for every element, as well as, perform type dispatching code during execution of each element. All of this makes Python lists inefficient
• In comparison, the NumPy comes with greater efficiency and convenience. The NumPy supports the vector and matrix operations, essentially enabling programmers to avoid unnecessary work
• Moreover, NumPy is also faster and give you access to fast searching, linear algebra, convolution, FFTs, and others

Q21. How values can be added to Python arrays?

Ans. Append (), insert (I,x), and extend () functions can be used to add elements to a Python array.

Q22. How values can be removed from a Python array?

Ans. Pop () or remove () functions can be sued to remove elements from python arrays. The pop () function returns the deleted value, whereas, the remove () function doesn’t.

Q23. Is there an Oops concept in Python?

Ans. As an object-oriented programming language, Python can be used to solve any program using object models. However, Python can’t just be classified as an “object-oriented programming language” but can also be treated as a structural or procedural language.

Q24. Explain the difference between shallow and deep copy?

Ans. Shallow copy is more often used in case a new instance type is created. Shallow copy maintains the copied values in the new instance and can also be used to copy the reference pointers.

The deep copy doesn’t allow copying of reference pointers to the objects and is used to store already copied values.

Q25. How to achieve multithreading in Python?

Ans:

• Python comes with a multi-threading package. However, using this to speed up the code isn’t recommended
• The Python’s Global Interpreter Lock (GIL) is used for multi-threading. The GIL enables the execution of a “single” thread at a time. The process includes acquiring GIL by one thread and passing it on to the next thread after its task is completed
• The tasks performed by GIL are very quick, which to human eyes may seem like being performed in parallel.  However, essentially the execution is being performed stepwise using the same CPU core
• And since the passing of Gil from thread to thread adds to the execution overhead, thereby, using a threading package to fasten up the execution process of the code isn’t a good idea

Best Python Questions and Answers for Advanced level

We already have gone through much of the Python interview questions and answers. However, there’s still a lot to cover. So, now let’s move on to the next level and see some Python interview questions and answers for advanced level professionals.

Q1. Explain the process of compilation and linking in Python?

Ans. The compiling process enables the compilation of new extensions without any error. Whereas, the linking is only achieved once the new extensions passed through the compilation process. The process of compilation and linking includes;

• Creation and naming of a file in one of the many languages that are supported by the compiler of the system
• Placing the files within the directory of the distribution being used
• Adding “setup.local” line in the file
• Executing the file using Spam file.o
• Rebuilding the interpreter after successful execution of the file using top-level directory
• Use the command “rebuildMakefile” using the “make Makefile” in case the file is changed

Q2. Name few Python libraries?

Ans. Python comes with various libraries, which are essentially the collection of Python packages. Some of the more commonly used Python libraries include;

• Numpy
• Scikit-Learn
• Matplotlib
• Pandas

Q3. What is the use of split?

Ans. The Split () function in Python is meant to separate the string

Q4. How can you import Python Modules?

Ans. To import Python modules, you would use “Import” keywords. Modules can be imported in three ways;

• Import array
• Import array as arr
• From array import *

Q5. What does “inheritance” mean in Python?

Ans. The inheritance function in Python enables users to copy all the members (attributes and methods) of one class to another class. The function also enables code reusability, thus making it convenient for coders to develop and maintain applications. In “inheritance” the class from where the members are being copied is called “superclass”, whereas, the call to which the members are inherited is called “derived/child class”.

Q6. How can we create classes in Python?

Ans. In Python, classes can be created using the keyword “class”.

Q7. Explain monkey patching in Python.

Ans. In Python, the dynamic modification of a module or class in run-time is referred to as monkey patching.

Q8. Is there support for multiple inheritance in Python?

Ans. Yes. Unlike Java, Python does allow for multiple inheritance, where a child class can inherit members of multiple parent classes.

Q9. Explain Polymorphism in Python?

Ans. Python does support polymorphism, which enables the child classes to have the same name but different parameters and variables as the parent classes.

Q10. Explain the term encapsulation in Python?

Ans. The term encapsulation refers to the process of binding data and code together. Python is one example of encapsulation.

Q11. Explain data abstraction in Python?

Ans. In data abstraction, the process of code execution is hidden from the world, whereby, only limited details are shown. Abstract and interface classes can be used in Python to achieve data abstraction.

Q12. How can we create an empty class in Python?

Ans. An empty class refers to a class that doesn’t comprise any code in its block. In Python, empty classes can be created by using the “Pass” keyword. “Pass” is a null statement in Python and does nothing when executed.

Q13. Write down the use of object ()?

Ans. Object () is used to create a featureless object in Python. The function doesn’t take any parameters, however, the featureless object created is the base for all classes.

Q14. What is flask in Python?

Ans. Flask is the web microframework for Python. In Python, Flask makes the framework light, whereas, it comes with fewer bugs and little dependency on updates.

Q15. Which is better; Flask or Django?

Ans. Both Django and Flask are used in Python to map the URLs typed in the web browsers.

Flask is easier than Django, however, it also has limited functionality. This means that users are required to specify the details when using Flask. Contrarily, Django may be a little complicated as compared to Flask, however, it achieves much more for the user, leaving little to do on the users’ end. Flask requires users to write their codes, whereas, Django comes with prewritten codes.

Technically, both Flask and Django are handy tools with their own set of strengths and limitations. 

A16. What’s the difference between Flask, Pyramid, and Django?

Ans.

• Flask refers to the “microframework” for Python and is essentially meant for small applications with few requirements. Flasks don’t come with prewritten codes, and users are expected to use external libraries
• Django is primarily meant for larger applications with complex requirements and also includes an ORM
• Pyramid like Django is meant for larger applications. It offers additional flexibility that enables developers; assisting them in choosing the right tools for the project.

Q17. What are the different inheritance styles in Django?

Ans. Django offers three different inheritance styles including;

–         Abstract Base Classes

This inheritance style is used when developers only want to copy specific members of the parent class to the child class which they don’t want to type out

– Multi-Table Inheritance

This inheritance style is used when developers want to create sub-classes of an existing model while requiring an individual database table for each model.

– Proxy Models

This inheritance model is used when the developer wants to modify the Python level behavior of the model

Q18. Explain the Map Function in Python?

Ans. Map function runs the first argument across all the elements of the iterable mentioned as the second argument. In the case where there is more than one argument, multiple iterables may be given.

Q19. Is Numpy better than lists?

Ans. Numpy is better than Python lists for reasons mentioned below;

• Convenient
• Fast
• Less Memory 

Q19. Write down the steps to get indices of N maximum values in the NumPy array?

Ans. Following steps may be used to get indices of N maximum values in NumPy array;

• Import NumPy as np
• Arr = np.array ([2,3,5,7,9])
• Print (arr.argsort()[-3:][::-2])

Output

[ 7 3 2 ]

Q20. Write down the differences between SciPy and NumPy?

Ans.

• NumPy in an ideal world comprises only on array data type, along with the most basic operations like; reshaping, indexing, etc.
• NumPy may contain some basic mathematics functions, however, the same would reside in SciPy
• SciPy comprise of all the numerical code
• SciPy comprise of all advanced functions of linear algebra, and other numerical algorithms
• Both Packages may be installed for scientific computing

Q21. How to make 3D plots using NumPy/SciPy?

Ans. Users would have to integrate packages to integrate with NumPy to create 3D plots, which is essentially beyond the scope of NumPy and SciPy both. One particular package is Matplotlib, which enables 3D plotting in the mplot3D subpackage.

Q22. Choose the Python statement/s that can be used to create the dictionary?

a) x = (40:”Ana”, 45:”50”)

b) x = {}

c) x = {40:”Ana”, 45:”Victor”}

d) x = {“Ana”:40, “Victor”:45}

Answer: a, c & d. 

Q23. Choose the one that is floor division?

1. %
2. //
3. /
4. None of the above

Answer. B (//)

Q24. Which one is the maximum possible length of an identifier?

1. 79 characters
2. 31 Characters
3. 69 Characters
4. None of the above

Ans. D (there is no character limit for identifier)

Q25.Which one is an invalid statement?

1. XYZ = 1,000,000
2. X_Y_Z = 1,000,000
3. X Y Z = 1000 2000 3000
4. X,Y,Z = 1000 2000 3000

Ans. B (X Y Z = 1000 2000 3000)

Concluding

Congrats you have completed one of the most comprehensive Python Interview questions and answers guide. We really hope that you would have learned some quick insights into the Python Interview Questions and would be better prepared for the next interview.

Do you have a specific question? Feel free to mention any query in the comments and we shall get back to you ASAP.