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Python Interview Questions

100 Interview Questions for Freshers 1 -2 Experienced Candidates

Python Interview Questions

Q1. What is the difference between list and tuples in Python?


              LIST                                                                                         TUPLES

Lists are mutable i.e they can be edited. Tuples are immutable (tuples are      

                                                                                      lists which can’t be edited).  

Lists are slower than tuples.                       Tuples are faster than lists.

Syntax: list_1 = [10, ‘Chelsea’, 20]             Syntax: tup_1 = (10, ‘Chelsea’ , 20)

Q2. What are the key features of Python?

Ans: Python is an interpreted language. That means that, unlike languages like C and its variants, Python does not need to be compiled before it is run. Other interpreted languages include PHP and Ruby.

Python is dynamically typed, which means that you don’t need to state the types of variables when you declare them or anything like that. You can do things like x=111 and then x=”I’m a string” without an error

Python is well suited to object-oriented programming in that it allows the definition of classes along with composition and inheritance. Python does not have access specifiers (like C++’s public, or private).

In Python, functions are first-class objects. This means that they can be assigned to variables, returned from other functions, and passed into functions. Classes are also first-class objects

Writing Python code is quick but running it is often slower than compiled languages. Fortunately, Python allows the inclusion of C-based extensions so bottlenecks can be optimized away and often are.

The NumPy package is a good example of this, it’s quite quick because a lot of the number-crunching it does isn’t done by Python

Python finds use in many spheres – web applications, automation, scientific modeling, big data applications, and many more. It’s also often used as “glue” code to get other languages and components to play nice.

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Q3. What type of language is python? Programming or scripting?

Ans: Python is capable of scripting, but in general sense, it is considered as a general-purpose programming language. To know more about Scripting, you can refer to the Python Scripting Tutorial.

Q4.What are the benefits of using Python?

Java language was developed in such a way that it does not depend on any hardware or software due to the fact that the compiler compiles the code and then converts it to platform-independent bytecode which can be run on multiple systems.

  • The only condition to run that byte code is for the machine to have a runtime environment (JRE) installed in it

Q5.What is pep 8?

Ans: PEP stands for Python Enhancement Proposal. It is a set of rules that specify how to format Python code for maximum readability.

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Q6.Python is an interpreted language. Explain.

Ans: An interpreted language is any programming language which is not in machine-level code before runtime. Therefore, Python is an interpreted

Q7.What are Python namespaces?

Ans: A namespace in python refers to the name which is assigned to each object in python. The objects are variables and functions. As each object is created, its name along with space(the address of the outer function in which the object is), gets created.

The namespaces are maintained in python like a dictionary where the key is the namespace and the value is the address of the object. There 4 types of namespace in python-

Built-in namespace– These namespaces contain all the built-in objects in python and are available whenever python is running.

Global namespace– These are namespaces for all the objects created at the level of the main program.

Enclosing namespaces– These namespaces are at the higher level or outer function.

Local namespaces– These namespaces are at the local or inner function.

Q8.What are decorators in Python?

Ans: Decorators are used to adding some design patterns to a function without changing its structure. Decorators generally are defined before the function they are enhancing.

To apply a decorator we first define the decorator function. Then we write the function it is applied to and simply add the decorator function above the function it has to be applied to. For this, we use the @ symbol before the decorator.

Q9.What are Dict and List comprehensions?

Ans: Dictionary and list comprehensions are just another concise way to define dictionaries and lists.

Example of list comprehension is-

x=[i for i in range(5)]

The above code creates a list as below-



Example of dictionary comprehension is-

x=[i : i+2 for i in range(5)]

The above code creates a list as below-

[0: 2, 1: 3, 2: 4, 3: 5, 4: 6]

Q10.What are the common built-in data types in Python?

Ans: The common built-in data types in python are-

Numbers– They include integers, floating-point numbers, and complex numbers. eg. 1, 7.9,3+4i

List– An ordered sequence of items is called a list. The elements of a list may belong to different data types. Eg. [5,’market’,2.4]

Tuple– It is also an ordered sequence of elements. Unlike lists , tuples are immutable, which means they can’t be changed. Eg. (3,’tool’,1)

String– A sequence of characters is called a string. They are declared within single or double-quotes. Eg. “Sana”, ‘She is going to the market’, etc.

Set– Sets are a collection of unique items that are not in order. Eg. {7,6,8}

Dictionary– A dictionary stores values in key and value pairs where each value can be accessed through its key. The order of items is not important. Eg. {1:’apple’,2:’mango}

Boolean– There are 2 boolean values- True and False.

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Q11.What is the difference between .py and .pyc files?

Ans: The .py files are the python source code files. While the .pyc files contain the bytecode of the python files. .pyc files are created when the code is imported from some other source.

The interpreter converts the source .py files to .pyc files which helps by saving time. You can get a better understanding of the Data Engineering Course in Washington.

Q12.What is slicing in Python?

Ans: Slicing is used to access parts of sequences like lists, tuples, and strings. The syntax of slicing is-[start:end: step]. The step can be omitted as well.

When we write [start: end] this returns all the elements of the sequence from the start (inclusive) till the end-1 element. If the start or end element is negative I, it means the ith element from the end.

The step indicates the jump or how many elements have to be skipped. Eg. if there is a list- [1,2,3,4,5,6,7,8]. Then [-1:2:2] will return elements starting from the last element till the third element by printing every second element.i.e. [8,6,4].

Q13.What are Keywords in Python?

Ans: Keywords in python are reserved words that have special meaning.They are generally used to define types of variables. Keywords cannot be used for variable or function names. There are following 33 keywords in python-


































Q14.What are Literals in Python and explain about different Literals

Ans: A literal in python source code represents a fixed value for primitive data types. There are 5 types of literals in python-

String literals– A string literal is created by assigning some text enclosed in single or double quotes to a variable. To create multiline literals, assign the multiline text enclosed in triple quotes.”Tanya”

A character literal– It is created by assigning a single character enclosed in double quotes. Eg. a=’t’

Numeric literals include numeric values that can be either integer, floating point value, or a complex number. Eg. a=50

Boolean literals– These can be 2 values- either True or False.

Literal Collections– These are of 4 types-

  1. a) List collections-Eg. a=[1,2,3,’Amit’]
  2. b) Tuple literals- Eg. a=(5,6,7,8)
  3. c) Dictionary literals- Eg. dict={1: ’apple’, 2: ’mango, 3: ’banana`’}
  4. d) Set literals- Eg. {“Tanya”, “Rohit”, “Mohan”}
  5. Special literal- Python has 1 special literal None which is used to return a null variable.

Q15.How to combine dataframes in pandas?

Ans: The dataframes in python can be combined in the following ways-

Concatenating them by stacking the 2 data frames vertically.

Concatenating them by stacking the 2 data frames horizontally.

Combining them on a common column. This is referred to as joining.

The concat() function is used to concatenate two dataframes. Its syntax is- pd.concat([dataframe1, dataframe2]).

Dataframes are joined together on a common column called a key. When we combine all the rows in the dataframe it is union and the join used is outer join. While, when we combine the common rows or intersection, the join used is the inner join. Its syntax is- pd.concat([dataframe1, dataframe2], axis=’axis’, join=’type_of_join)

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Q16.What are the new features added in Python version?

Ans: The new features in Python version are-

 New Dictionary functions Merge(|) and Update(|=)

New String Methods to Remove Prefixes and Suffixes

Type Hinting Generics in Standard Collections

New Parser based on PEG rather than LL1

New modules like zoneinfo and graphlib

Improved Modules like ast, asyncio, etc.

Optimizations such as optimized idiom for assignment, signal handling, optimized python built-ins, etc.

Deprecated functions and commands such as deprecated parser and symbol modules, deprecated functions, etc.

Removal of erroneous methods, functions, etc.

Q17. How is memory managed in Python?

Ans: Memory is managed in Python in the following ways:

Memory management in python is managed by Python private heap space. All Python objects and data structures are located in a private heap. The programmer does not have access to this private heap. The python interpreter takes care of this instead.

The allocation of heap space for Python objects is done by Python’s memory manager. The core API gives access to some tools for the programmer to code.

Python also has an inbuilt garbage collector, which recycles all the unused memory and so that it can be made available to the heap space.

Q18. What is namespace in Python?

Ans: A namespace is a naming system used to make sure that names are unique to avoid naming conflicts.

Q19. What is PYTHONPATH?

Ans: It is an environment variable that is used when a module is imported. Whenever a module is imported, PYTHONPATH is also looked up to check for the presence of the imported modules in various directories.

The interpreter uses it to determine which module to load.

Q20. What are python modules? Name some commonly used built-in modules in Python?

Ans: Python modules are files containing Python code. This code can either be functions, classes or variables. A Python module is a .py file containing executable code.

Some of the commonly used built-in modules are:





data time


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Q21.What are local variables and global variables in Python?

Global Variables:

Variables declared outside a function or in global space are called global variables. These variables can be accessed by any function in the program.

Local Variables:

Any variable declared inside a function is known as a local variable. This variable is present in the local space and not in the global space.



def add():





Output: 5

When you try to access the local variable outside the function add(), it will throw an error.

Q22. Is the python case sensitive?

Ans: Yes. Python is a case sensitive language.

Q23.What is type conversion in Python?

Ans: Type conversion refers to the conversion of one data type into another.

int() – converts any data type into integer type

float() – converts any data type into float type

ord() – converts characters into integer

hex() – converts integers to hexadecimal

oct() – converts integer to octal

tuple() – This function is used to convert to a tuple.

set() – This function returns the type after converting to set.

list() – This function is used to convert any data type to a list type.

dict() – This function is used to convert a tuple of order (key, value) into a dictionary.

str() – Used to convert an integer into a string.

complex(real,imag) – This function converts real numbers to complex(real,imag) numbers.

Q24. How to install Python on Windows and set path variables?

Ans: To install Python on Windows, follow the below steps:


Install python from this link:

After this, install it on your PC. Look for the location where PYTHON has been installed on your PC using the following command on your command prompt: cmd python. 

Then go to advanced system settings and add a new variable and name it as PYTHON_NAME and paste the copied path.

Look for the path variable, select its value and select ‘edit’.

Add a semicolon towards the end of the value if it’s not present and then type %PYTHON_HOME% 

Q25. Is indentation required in python?

Ans: Indentation is necessary for Python. It specifies a block of code. All code within loops, classes, functions, etc is specified within an indented block.

It is usually done using four space characters. If your code is not indented necessarily, it will not execute accurately and will throw errors as well.

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Q26. What is the difference between Python Arrays and lists?

Ans: Arrays and lists, in Python, have the same way of storing data. But, arrays can hold only a single data type element whereas lists can hold any data type elements.


import array as arr






array(‘i’, [1, 2, 3, 4]) [1, ‘abc’, 1.2]

Q27. What are functions in Python?

Ans: A function is a block of code which is executed only when it is called. To define a Python function, the def keyword is used.


def Newfunc():

print(“Hi, Welcome to Edureka”)

Newfunc(); #calling the function

Output: Hi, Welcome to Edureka

Q28.What is __init__?

Ans: __init__ is a method or constructor in Python. This method is automatically called to allocate memory when a new object/ instance of a class is created. All classes have the __init__ method.

Here is an example of how to use it.

class Employee:

def __init__(self, name, age,salary): = name

self.age = age

self.salary = 20000

E1 = Employee(“XYZ”, 23, 20000)

# E1 is the instance of class Employee.

#__init__ allocates memory for E1.








Q29.What is a lambda function?

Ans: An anonymous function is known as a lambda function. This function can have any number of parameters but can have just one statement.


a = lambda x,y : x+y

print(a(5, 6))

Output: 11

Q30. What is self in Python?

Ans: Self is an instance or an object of a class. In Python, this is explicitly included as the first parameter. However, this is not the case in Java where it’s optional.  It helps to differentiate between the methods and attributes of a class with local variables.

The self variable in the init method refers to the newly created object while in other methods, it refers to the object whose method was called.

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Q31. How does break, continue and pass work?

Ans: Break Allows loop termination when some condition is met and the control is transferred to the next statement.

Continue Allows skipping some part of a loop when some specific condition is met and the control is transferred to the beginning of the loop

Pass Used when you need some block of code syntactically, but you want to skip its execution. This is basically a null operation. Nothing happens when this is executed.

Q32. What does [::-1} do?

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

For example:

import array as arr



Output: array(‘i’, [5, 4, 3, 2, 1])

[::-1] reprints a reversed copy of ordered data structures such as an array or a list. the original array or list remains unchanged.

Q33. How can you randomize the items of a list in place in Python?

Ans: Consider the example shown below:

from random import shuffle

x = [‘Keep’, ‘The’, ‘Blue’, ‘Flag’, ‘Flying’, ‘High’]



The output of the following code is as below.

[‘Flying’, ‘Keep’, ‘Blue’, ‘High’, ‘The’, ‘Flag’]

Q34. What are python iterators?

Ans: Iterators are objects which can be traversed though or iterated upon.

Q35. 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:

import random


The statement random.random() method returns the floating-point number that is in the range of [0, 1). The function generates random float numbers. The methods that are used with the random class are the bound methods of the hidden instances. The instances of the Random can be done to show the multithreading programs that create a different instance of individual threads. The other random generators that are used in this are:

randrange(a, b): it chooses an integer and defines the range in-between [a, b). It returns the elements by selecting it randomly from the range that is specified. It doesn’t build a range object.

uniform(a, b): it chooses a floating point number that is defined in the range of [a,b).Iyt returns the floating point number

normalvariate(mean, sdev): it is used for the normal distribution where the mu is a mean and the sdev is a sigma that is used for standard deviation.

The Random class that is used and instantiated creates independent multiple random number generators.

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Q36. What is the difference between range & xrange?

Ans: For the most part, range and range are the same in terms of functionality. They both provide a way to generate a list of integers for you to use, however you please.

The only difference is that range returns a Python list object and x range returns an xrange object.

This means that xrange doesn’t generate a static list at run-time as the range does. It creates the values as you need them with a special technique called yielding. This technique is used with a type of object known as generators.

That means that if you have a really gigantic range you’d like to generate a list for, say one billion, xrange is the function to use.

This is especially true if you have a real memory-sensitive system such as a cell phone that you are working, as the range will use as much memory as it can to create your array of integers, which can result in a Memory Error and crash your program. It’s a memory hungry beast.

Q37. How do you write comments in python?

Ans: Comments in Python start with a # character. However, alternatively at times, commenting is done using docstrings(strings enclosed within triple quotes).




<span data-mce-type=”bookmark” style=”display: inline-block; width: 0px; overflow: hidden; line-height: 0;” class=”mce_SELRES_end”></span>

<pre><span>#Comments in Python start like this

print(“Comments in Python start with a #”)

Output:  Comments in Python start with a #

Q38. What is pickling and unpickling?

Ans: The pickle module accepts any Python object and converts it into a string representation and dumps it into a file by using the dump function, this process is called pickling.

While the process of retrieving original Python objects from the stored string representation is called unpickling.

Q39. What are the generators in python?

Ans: Functions that return an iterable set of items are called generators.

Q40. How will you capitalize the first letter of the string?

Ans: In Python, the capitalize() method capitalizes the first letter of a string. If the string already consists of a capital letter at the beginning, then, it returns the original string.

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Q41. How will you convert a string to all lowercase?

Ans: To convert a string to lowercase, lower() function can be used.




Output: abcd

Q42. How to comment multiple lines in python?

Ans: Multi-line comments appear in more than one line. All the lines to be commented on are to be prefixed by a #. You can also use a very good shortcut method to comment on multiple lines.

All you need to do is hold the ctrl key and left-click in every place wherever you want to include a # character and type a # just once. This will comment on all the lines where you introduced your cursor.

Q43.What are docstrings in Python?

Ans: Docstrings are not actually comments, but they are documentation strings. These docstrings are within triple quotes. They are not assigned to any variable and therefore, at times, serve the purpose of comments as well.



Using docstring as a comment.

This code divides 2 numbers






Output: 2.0

Q44. What is the purpose of ‘is’, ‘not’ and ‘in’ operators?

Ans: Operators are special functions. They take one or more values and produce a corresponding result.

is: returns true when 2 operands are true  (Example: “a” is ‘a’)

not: returns the inverse of the boolean value

in: checks if some element is present in some sequence

Q45. What is the usage of help() and dir() functions in Python?

Ans: Help() and dir() both functions are accessible from the Python interpreter and used for viewing a consolidated dump of built-in functions. 


Help() function: The help() function is used to display the documentation string and also facilitates you to see the help related to modules, keywords, attributes, etc.

Dir() function: The dir() function is used to display the defined symbols.

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Q46. Whenever Python exits, why isn’t all the memory deallocated?

Ans: Whenever Python exists, especially those Python modules which are having circular references to other objects or the objects that are referenced from the global namespaces are not always de-allocated or freed.

It is impossible to de-allocate those portions of memory that are reserved by the C library.

On exit, because of having its own efficient clean up mechanism, Python would try to de-allocate/destroy every other object.

Q47. What is a dictionary in Python?

Ans: The built-in datatypes in Python are called dictionaries. It defines a one-to-one relationship between keys and values. Dictionaries contain pairs of keys and their corresponding values. Dictionaries are indexed by keys.


Let’s take an example:


The following example contains some keys. Country, Capital & PM. Their corresponding values are India, Delhi and Modi respectively.



print dict[Country]


print dict[Capital]


print dict[PM]


Q48. How can the ternary operators be used in python?

Ans: The Ternary operator is the operator that is used to show the conditional statements. This consists of the true or false values with a statement that has to be evaluated for it.


The Ternary operator will be given as:

[on_true] if [expression] else [on_false]x, y = 25, 50 big = x if x < y else y


The expression gets evaluated like if x<y else y, in this case if x<y is true then the value is returned as big=x and if it is incorrect then big=y will be sent as a result.

Q49. What does this mean: *args, **kwargs? And why would we use it?

Ans: We use *args when we aren’t sure how many arguments are going to be passed to a function, or if we want to pass a stored list or tuple of arguments to a function.

**kwargs is used when we don’t know how many keyword arguments will be passed to a function, or it can be used to pass the values of a dictionary as keyword arguments.

The identifiers args and kwargs are a convention, you could also use *bob and **billy but that would not be wise.

Q50. What does len() do?

Ans: It is used to determine the length of a string, a list, an array, etc.





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Q51. Explain split(), sub(), subn() methods of the “re” module in Python.

Ans: To modify the strings, Python’s “re” module is providing 3 methods. They are:


split() – uses a regex pattern to “split” a given string into a list.

sub() – finds all substrings where the regex pattern matches and then replace them with a different string

subn() – it is similar to sub() and also returns the new string along with the no. of replacements.

Q52. What are negative indexes and why are they used?

Ans: The sequences in Python are indexed and it consists of the positive as well as negative numbers. The numbers that are positive use ‘0’ that is used as the first index and ‘1’ as the second index and the process goes on like that.


The index for the negative number starts from ‘-1’ that represents the last index in the sequence and ‘-2’ as the penultimate index and the sequence carries forward like the positive number.


The negative index is used to remove any new-line spaces from the string and allow the string to accept the last character that is given as S[:-1]. The negative index is also used to show the index to represent the string in correct order.

Q53. What are Python packages?

Ans: Python packages are namespaces containing multiple modules.

Q54.How can files be deleted in Python?

Ans: To delete a file in Python, you need to import the OS Module. After that, you need to use the os.remove() function.


import os


Q55. What are the built-in types of python?

Ans: Built-in types in Python are as follows –



Complex numbers



Built-in functions

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Q56. What advantages do NumPy arrays offer over (nested) Python lists?

Ans: Python’s lists are efficient general-purpose containers. They support (fairly) efficient insertion, deletion, appending, and concatenation, and Python’s list comprehensions make them easy to construct and manipulate.

They have certain limitations: they don’t support “vectorized” operations like eelement-wiseaddition and multiplication, and the fact that they can contain objects of differing types mmeansthat Python must store type information for every element, and must execute type dispatching code when operating on each element.

NumPy is not just more efficient; it is also more convenient. You get a lot of vector and matrix operations for free, which sometimes allows one to avoid unnecessary work. And they are also efficiently implemented.

NumPy array is faster and You get a lot built-in with NumPy, FFTs, convolutions, fast searching, basic statistics, linear algebra, histograms, etc. 

Q57. How to add values to a python array?

Ans: Elements can be added to an array using the append(), extend() and the insert (i,x) functions.


a=arr.array(‘d’, [1.1 , 2.1 ,3.1] )








array(‘d’, [1.1, 2.1, 3.1, 3.4])

array(‘d’, [1.1, 2.1, 3.1, 3.4, 4.5, 6.3, 6.8])

array(‘d’, [1.1, 2.1, 3.8, 3.1, 3.4, 4.5, 6.3, 6.8])

Q58. How to remove values to a python array?

Ans: Array elements can be removed using pop() or remove() method. The difference between these two functions is that the former returns the deleted value whereas the latter does not.


a=arr.array(‘d’, [1.1, 2.2, 3.8, 3.1, 3.7, 1.2, 4.6])








array(‘d’, [2.2, 3.8, 3.7, 1.2])

Q59. Does Python have OOps concepts?

Ans: Python is an object-oriented programming language. This means that any program can be solved in python by creating an object model. However, Python can be treated as a procedural as well as structural language.

Q60. What is the difference between deep and shallow copy?

Ans: Shallow copy is used when a new instance type gets created and it keeps the values that are copied in the new instance. Shallow copy is used to copy the reference pointers just like it copies the values.

These references point to the original objects and the changes made by any member of the class will also affect the original copy of it. A shallow copy allows faster execution of the program and it depends on the size of the data that is used.

Deep copy is used to store the values that are already copied. Deep copy doesn’t copy the reference pointers to the objects. It refers to an object and the new object that is pointed by some other object gets stored.

The changes made in the original copy won’t affect any other copy that uses the object. Deep copy makes the execution of the program slower due to making certain copies for each object that is being called.

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Q61. How is Multithreading achieved in Python?


Python has a multi-threading package but if you want to multi-thread to speed your code up, then it’s usually not a good idea to use it.

Python has a construct called the Global Interpreter Lock (GIL). The GIL makes sure that only one of your ‘threads’ can execute at any one time. A thread acquires the GIL, does a little work, then passes the GIL onto the next thread.

This happens very quickly so to the human eye it may seem like your threads are executing in parallel, but they are really just taking turns using the same CPU core.

All this GIL passing adds overhead to execution. This means that if you want to make your code run faster then using the threading package often isn’t a good idea.

Q62. What is the process of compilation and linking in python?

Ans: The compiling and linking allow the new extensions to be compiled properly without any error and the linking can be done only when it passes the compiled procedure.

If dynamic loading is used then it depends on the style that is being provided with the system. The python interpreter can be used to provide the dynamic loading of the configuration setup files and will rebuild the interpreter.

The steps that are required in this are as:

Create a file with any name and in any language that is supported by the compiler of your system. For example file. c or file.CPP

Place this file in the Modules/ directory of the distribution which is getting used.

Add a line in the file Setup. local that is present in the Modules/ directory.

Run the file using a spam file.o

After a successful run of this rebuild the interpreter by using the make command on the top-level directory.

If the file is changed then run rebuildMakefile by using the command as ‘make Makefile’.

Q63. What are Python libraries? Name a few of them.

Python libraries are a collection of Python packages. Some of the majorly used python libraries are – Numpy, Pandas, Matplotlib, Scikit-learn and many more.

Q64. What is split used for?

The split() method is used to separate a given String in Python.


a=”edureka python”


Output:  [‘edureka’, ‘python’]

Q65. How to import modules in python?

Modules can be imported using the import keyword.  You can import modules in three ways-


import array #importing using the original module name

import array as arr # importing using an alias name

from array import * #imports everything present in the array module

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Q66. Explain Inheritance in Python with an example.

Ans: Inheritance allows One class to gain all the members(say attributes and methods) of another class. Inheritance provides code reusability and makes it easier to create and maintain an application.

The class from which we are inheriting is called a superclass and the class that is inherited is called a derived / child class.

They are different types of inheritance supported by Python:

Single Inheritance – where a derived class acquires the members of a single superclass.

Multilevel inheritance – a derived class d1 is inherited from base class base1, and d2 is inherited from base2.

Hierarchical inheritance – from one base class you can inherit any number of child classes

Multiple inheritances – a derived class is inherited from more than one base class.

Q67. How are classes created in Python?

Ans: Class in Python is created using the class keyword.




class Employee:

def __init__(self, name): = name



Output: abc

Q68. What is monkey patching in Python?

Ans: In Python, the term monkey patch only refers to dynamic modifications of a class or module at run-time.

Consider the below example:


class MyClass:

def f(self):

print “f()”

We can then run the monkey-patch testing like this:

import m

def monkey_f(self):

print “monkey_f()”


m.MyClass.f = monkey_f

obj = m.MyClass()


The output will be as below:


As we can see, we did make some changes in the behavior of f() in MyClass using the function we defined, monkey_f(), outside of the module m.

Q69. Does python support multiple inheritance?

Ans: Multiple inheritance means that a class can be derived from more than one parent class. Python does support multiple inheritance, unlike Java.

Q70. What is Polymorphism in Python?

Ans: Polymorphism means the ability to take multiple forms. So, for instance, if the parent class has a method named ABC then the child class also can have a method with the same name ABC having its parameters and variables. Python allows polymorphism.

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Q71. Define encapsulation in Python?

Ans: Encapsulation means binding the code and the data together. A Python class in an example of encapsulation.

Q72. How do you do data abstraction in Python?

Ans: Data Abstraction is providing only the required details and hiding the implementation from the world. It can be achieved in Python by using interfaces and abstract classes.

Q73.Does python make use of access specifiers?

Ans: Python does not deprive access to an instance variable or function. Python lays down the concept of prefixing the name of the variable, function or method with a single or double underscore to imitate the behavior of protected and private access specifiers.  

Q74. How to create an empty class in Python?

Ans: An empty class is a class that does not have any code defined within its block. It can be created using the pass keyword. However, you can create objects of this class outside the class itself. IN PYTHON THE PASS command does nothing when it’s executed. it’s a null statement. 

For example-

class a:



print(“Name = “,


Name = xyz

Q75. What does an object() do?

Ans: It returns a featureless object that is a base for all classes. Also, it does not take any parameters.

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Q76. Write a program in Python to execute the Bubble sort algorithm.

def bs(a):

# a = name of list


# minus 1 because we always compare 2 adjacent values

for x in range(b):

for y in range(b-x):





Output:  [3, 5, 6, 7, 32, 54, 87]


Q77. Write a program in Python to produce Star triangle.

def myfunc(r):

for x in range(r):

print(‘ ‘*(r-x-1)+’*’*(2*x+1))














Q78. Write a program to produce Fibonacci series in Python.

Ans: # Enter number of terms needed nbsp;#0,1,1,2,3,5….

a=int(input(“Enter the terms”))

f=0;#first element of series

s=1#second element of series

if a=0:

print(“The requested series is”,f)


print(f,s,end=” “)

for x in range(2,a):

print(next,end=” “)



Output: Enter the terms 5 0 1 1 2 3

Q79. Write a program in Python to check if a number is prime.

a=int(input(“enter number”))

if a=1:

for x in range(2,a):


print(“not prime”)





print(“not prime”)


enter number 3



Q80. Write a program in Python to check if a sequence is a Palindrome.

a=input(“enter sequence”)


if a==b:



print(“Not a Palindrome”)



enter sequence 323 palindrome

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Q81. Write a one-liner that will count the number of capital letters in a file. Your code should work even if the file is too big to fit in memory.

  • Ans:  Let us first write a multiple line solution and then convert it to one-liner code.

    with open(SOME_LARGE_FILE) as fh:

    count = 0

    text =

    for character in text:

    if character.isupper():

    count += 1

    We will now try to transform this into a single line.

    count sum(1 for line in fh for character in line if character.isupper())

Q82. Write a sorting algorithm for a numerical dataset in Python.

Ans: The following code can be used to sort a list in Python:

list = [“1”, “4”, “0”, “6”, “9”]

list = [int(i) for i in list]


print (list)

Q83. Looking at the below code, write down the final values of A0, A1, …An.

A0 = dict(zip((‘a’,’b’,’c’,’d’,’e’),(1,2,3,4,5)))

A1 = range(10)A2 = sorted([i for i in A1 if i in A0])

A3 = sorted([A0[s] for s in A0])

A4 = [i for i in A1 if i in A3]

A5 = {i:i*i for i in A1}

A6 = [[i,i*i] for i in A1]


Ans:  The following will be the final outputs of A0, A1, … A6

A0 = {‘a’: 1, ‘c’: 3, ‘b’: 2, ‘e’: 5, ‘d’: 4} # the order may vary

A1 = range(0, 10)

A2 = []

A3 = [1, 2, 3, 4, 5]

A4 = [1, 2, 3, 4, 5]

A5 = {0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81}

A6 = [[0, 0], [1, 1], [2, 4], [3, 9], [4, 16], [5, 25], [6, 36], [7, 49], [8, 64], [9, 81]]

Q84. Explain what Flask is and its benefits?

Ans: Flask is a web microframework for Python based on “Werkzeug, Jinja2 and good intentions” BSD license. Werkzeug and Jinja2 are two of their dependencies.

This means it will have little to no dependencies on external libraries.  It makes the framework light while there is little dependency to update and fewer security bugs.

A session allows you to remember information from one request to another. In a flask, a session uses a signed cookie so the user can look at the session contents and modify them. The user can modify the session if only it has the secret key Flask.secret_key.

Q85. Is Django better than Flask?

Ans: Django and Flask map the URLs or addresses typed in the web browsers to functions in Python. 

Flask is much simpler compared to Django but, Flask does not do a lot for you meaning you will need to specify the details, whereas Django does a lot for you wherein you would not need to do much work.

Django consists of prewritten code, which the user will need to analyze whereas Flask gives the users to create their code, therefore, making it simpler to understand the code. Technically both are equally good and both contain their pros and cons.

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Q86. Mention the differences between Django, Pyramid and Flask.


Flask is a “microframework” primarily built for a small application with simpler requirements. In flask, you have to use external libraries. Flask is ready to use.

Pyramid is built for larger applications. It provides flexibility and lets the developer use the right tools for their project. The developer can choose the database, URL structure, templating style and more. Pyramid is heavily configurable.

Django can also be used for larger applications just like Pyramid. It includes an ORM.

Q87. Explain how you can set up the Database in Django.

Ans: You can use the command edit mysite/, it is a normal python module with module level representing Django settings.


Django uses SQLite by default; it is easy for Django users as such it won’t require any other type of installation. In the case your database choice is different, you have to use the following keys in the DATABASE ‘default’ item to match your database connection settings.


Engines: you can change the database by using ‘django.db.backends.sqlite3’ , ‘django.db.backeneds.mysql’, ‘django.db.backends.postgresql_psycopg2’, ‘’ and so on

Name: The name of your database. In the case if you are using SQLite as your database, in that case, the database will be a file on your computer, Name should be a full absolute path, including the file name of that file.

If you are not choosing SQLite as your database then settings like Password, Host, User, etc. must be added.

Django uses SQLite as a default database, it stores data as a single file in the filesystem. If you do have a database server—PostgreSQL, MySQL, Oracle, MSSQL—and want to use it rather than SQLite, then use your database’s administration tools to create a new database for your Django project. Either way, with your (empty) database in place, all that remains is to tell Django how to use it. This is where your project’s file comes in.


We will add the following lines of code to the file:



‘default’: {

‘ENGINE’ : ‘django.db.backends.sqlite3’,

‘NAME’ : os.path.join(BASE_DIR, ‘db.sqlite3’),



Q88. Give an example how you can write a VIEW in Django?

Ans: This is how we can use write a view in Django:


from django.http import HttpResponse

import datetime


def Current_datetime(request):

now =

html = “It is now %s/body/html % now

return HttpResponse(html)

Returns the current date and time, as an HTML document

Q89. Mention what the Django templates consist of.

Ans: The template is a simple text file.  It can create any text-based format like XML, CSV, HTML, etc.  A template contains variables that get replaced with values when the template is evaluated and tags (% tag %) that control the logic of the template.

Django Template – Python Interview Questions – Edureka

Figure: Python Interview Questions – Django Template

Q90. Explain the use of sessions in the Django framework?

Ans: Django provides a session that lets you store and retrieve data on a per-site-visitor basis. Django abstracts the process of sending and receiving cookies, by placing a session ID cookie on the client side, and storing all the related data on the server side.

Django Framework – Python Interview Questions – Edureka

Figure: Python Interview Questions – Django Framework


So the data itself is not stored client side. This is nice from a security perspective.

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Q91. List out the inheritance styles in Django.

Ans: In Django, there are three possible inheritance styles:


Abstract Base Classes: This style is used when you only want a parent’s class to hold information that you don’t want to type out for each child model.

Multi-table Inheritance: This style is used If you are subclassing an existing model and need each model to have its own database table.

Proxy models: You can use this model, If you only want to modify the Python level behavior of the model, without changing the model’s fields.

Next in this Python Interview Question blog, let’s have a look at questions related to Web Scraping

Web Scraping – Python Interview Questions

Q92. How To Save An Image Locally Using Python Whose URL Address I Already Know?

Ans: We will use the following code to save an image locally from an URL address

import urllib.request

urllib.request.urlretrieve(“URL”, “local-filename.jpg”)

Q93. You are required to scrape data from IMDb top 250 movies page. It should only have fields movie name, year, and rating.

Ans: We will use the following lines of code:

from bs4 import BeautifulSoup

import requests

import sys

url = ‘’

response = requests.get(url)

soup = BeautifulSoup(response.text)

tr = soup.findChildren(“tr”)

tr = iter(tr)


for movie in tr:

title = movie.find(‘td’, {‘class’: ‘titleColumn’} ).find(‘a’).contents[0]

year = movie.find(‘td’, {‘class’: ‘titleColumn’} ).find(‘span’, {‘class’: ‘secondaryInfo’}).contents[0]

rating = movie.find(‘td’, {‘class’: ‘ratingColumn imdbRating’} ).find(‘strong’).contents[0]

row = title + ‘ – ‘ + year + ‘ ‘ + ‘ ‘ + rating



Q94. What is a map function in Python?

Ans: map function executes the function given as the first argument on all the elements of the iterable given as the second argument. If the function given takes in more than 1 arguments, then many iterables are given. #Follow the link to know more similar functions.

Q95. Is python numpy better than lists?

Ans: We use python numpy array instead of a list because of the below three reasons:


Less Memory



For more information on these parameters, you can refer to this section – Numpy Vs List.

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Q96. How to get indices of N maximum values in a NumPy array?

Ans: We can get the indices of N maximum values in a NumPy array using the below code:


import numpy as np

arr = np.array([1, 3, 2, 4, 5])



[ 4 3 1 ]

Q97. How do you calculate percentiles with Python/ NumPy?

Ans: We can calculate percentiles with the following code


import numpy as np

a = np.array([1,2,3,4,5])

p = np.percentile(a, 50) #Returns 50th percentile, e.g. median



Q98. What is the difference between NumPy and SciPy?


NumPy SciPy

It refers to Numerical python. It refers to Scientific python.

It has fewer new scientific computing features. Most new scientific computing features belong in SciPy.

It contains less linear algebra functions. It has more fully-featured versions of the linear algebra modules, as well as many other numerical algorithms.

NumPy has a faster processing speed. SciPy on the other hand has slower computational speed.

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