50 Python Interview Questions Every Developer Should Know in 2024

Python is the most popular programming languages even in 2024, according to the latest TIOBE Index, that every developer should be familiar with and adept with. Its simplicity and scalability make it the easiest-to-use programming language currently.

Developers who want to get rid of remembering countless hashtags and thousands of lines of code with countless function ‘loops’, should learn Python.

Most top-notch companies are also looking for Developers efficient in the Python language. So, in this article, we will provide you with 50 Python Interview questions that will not only make you completely flexible with Python but also bolster you enough to crack any job interview and land your dream job. These will help you crack several interviews and land your dream jobs!

50 Python Interview Questions for Freshers

Some of these questions are very easy, some are difficult, some are very common, and some are very new. Here are the 50 most-asked interview questions for a Python developer job:

1) What is Python? What are the benefits of using Python?

Python is an interpretable, general-purpose, high-level programming language. With the appropriate tools and libraries, this general-purpose language may be used to create nearly any kind of application.

Python also has support for objects, modules, threads, exception handling, and intelligent memory management, all of which are useful for modelling real-world issues and developing apps to address them.

The following are the benefits that come with using Python:

• Python is a general-purpose programming language with an emphasis on readability and an easy-to-learn syntax that lowers program maintenance costs. In addition, the language enables third-party packages that promote modularity and code reuse, are fully open-source, and have scripting capabilities.
• Python’s dynamic typing and binding, along with its high-level data structures, draw a large developer community for rapid application development and deployment.

2) What are the key features of Python?

Here are the key features of Python:

• The Python language is interpreted. This means that Python does not require compilation before it can be run, in contrast to languages like C and its derivatives.
• Because Python is dynamically typed, there is no need to specify the types of variables when you declare them or conduct any other similar task. Things like y=343 and y=”You are a string” can be done without making mistakes.
• Python is well suited to object-orientated 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. Learn more about Big Data and its applications from the Azure data engineer training course.

3) What is an Interpreted language?

Line by line, an Interpreted language puts its statements into action. Languages like Python, Javascript, R, PHP, and Ruby are excellent instances of languages that are interpretive. Interpreted programs execute straight from the source code; there is no need for a compilation stage in between.

4) Is Python a compiled language or an interpreted language?

Python is a partially interpreted and partially compiled language. When we run our code, the compilation process begins. This generates byte code internally, which the Python virtual machine then converts to the appropriate format depending on the underlying platform consisting of the computer and operating system.

5) What is PEP 8 and why is it important?

Python Enhancement Proposal is referred to as PEP. A PEP is an official design document that describes a new feature for Python or its processes, or it serves as information for the Python community.

Given that it contains the style rules for Python code, PEP 8 is particularly significant. It ensures that adhering to these style requirements truly and rigorously is a requirement for contributing to the Python open-source community.

6) What is Scope in Python?

In Python, each object operates inside a scope. In Python, a scope is a section of code where an object is still relevant. Namespaces provide each object inside a program with a distinct identity.

But there’s also a scope established for these namespaces where you can utilize their objects without a prefix. Here are a few instances of scope that Python creates while executing code:

• The local objects that are available in the current function are referred to as a local scope.
• The items that have been accessible since the beginning of code execution are referred to as the global scope.
• The global objects of the current module that are accessible within the program are referred to as a module-level scope.
• All of the program’s built-in names that can be called are referred to as the outermost scope. The name mentioned is found by searching the items in this scope at the last.

7) What are decorators in Python?

A function can have some design patterns added to it without having to change its structure by using decorators. In most cases, decorators are defined before the function they are improving. The decorator function must be defined before a decorator may be applied. Next, we write the function to which it is applied, and we just need to add the decorator function above the function to which it has to be applied. We utilize the @ sign in front of the decorator for this.

8) What are lists and tuples? What is the key difference between the two?

In Python, the data structures that hold and manage a group of elements are called lists and tuples. Both are used to store the data, while indexes are used to retrieve the values that are kept. However, the primary distinction between the two is that tuples are immutable whereas lists are mutable.

One way to organize different data types is into lists. These can include integers, floats, texts, objects, and more.

List items are stored in square brackets [], with commas used to divide them. Lists have ordered items (indexed elements) and are mutable (i.e., elements can be changed after formation). Between the first element (index = 0) and the last element (index = number of items – 1) in the list, the index operates. Eg: my_list = [‘Apple’, 17, 11, 0.67]

Tuples are a type of data structure in Python that is similar to lists, but they vary in that their elements cannot be changed once they are created. Tuples are frequently employed in Python applications where immutability, order preservation, and data integrity are crucial.

Tuples keep the order of its elements, making index manipulation and access simple. Any type of data, including texts, numbers, Boolean values, and even other tuples, can be stored in it. Eg: my_tuple = (‘Apple’, 17, 11, 0.67)

9) What does the ‘#’ symbol do in Python?

‘#’ is used to leave a comment on any subsequent text on the line.

10) What are the common built-in data types in Python?

The following are the common built-in data types in Python:

• Numbers: They include integers, floating-point numbers, and complex numbers. Eg: 5, 4.2, 7 + 3i
• List: An ordered sequence of items is called a list. The elements of a list may belong to different data types. Eg: [8,’Apples’,7.9]
• Tuple: It is an elemental sequence that is also ordered. Tuples are immutable, which means they cannot be altered, in contrast to lists. Eg: (‘Apple’, 17, 11, 0.67)
• String: A string is a collection of characters. They are stated in single or double quotation marks. Eg: “I am good at Python”.
• Set: Sets are a collection of unique items that are not in order. Eg: {2,3,9}
• Boolean: There are 2 boolean values- True and False.
• Dictionary: A dictionary is a collection of values that are kept in key-value pairs, each of which is accessible via its key. It doesn’t matter what comes in what order. Eg: {1:’Red’,2:’Blue’}

11) What is a pass in Python?

In Python, a null operation is represented by the pass keyword. Generally speaking, it’s used to fill in blank code blocks that need to be written but may run during runtime. We can encounter certain issues when executing the code if the pass statement is absent from the following code.

def myEmptyFunc():
   # do nothing
    pass
myEmptyFunc()    # nothing happens
## Without the pass keyword
# File "<stdin>", line 3
# IndentationError: expected an indented bloc

12) What is the difference between .py and .pyc files?

The source code for Python is contained in the .py files. The bytecode of the Python files is contained in the .pyc files, which are generated when code is imported from another source. Time is saved when the interpreter changes the original .py files to .pyc files.

13) What is type conversion in Python?

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

• int() – converts any data type into an integer type
• float() – converts any data type into float type
• ord() – converts characters into integer
• hex() – converts integers to hexadecimal
• oct() – converts an 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) number.

14) What is the difference between a Mutable datatype and an Immutable data type?

Data types that are mutable can be altered or changed at runtime. Such as a dictionary, list, etc.

Immutable data types are unchangeable at runtime, meaning they cannot be modified. For example, tuple, string, etc.

15) What are modules and packages in Python?

Python modular programming is made possible by two mechanisms: packages and modules. There are various benefits of modularizing:

• Simplicity: Working on a single module helps you focus on a relatively small portion of the problem at hand. This makes development easier and less error-prone.
• Maintainability: Modules are designed to enforce logical boundaries between different problem domains. If they are written in a manner that reduces interdependency, it is less likely that modifications in a module might impact other parts of the program.
• Reusability: Functions defined in a module can be easily reused by other parts of the application.
• Scoping: Modules typically define a separate namespace, which helps avoid confusion between identifiers from other parts of the program.

Generally speaking, modules are just Python files with a.py extension that include a set of declared and implemented variables, classes, or functions. The ‘import’ statement can be used to import them and initialize them once. Use the ‘from foo import bar’ to import the necessary classes or functions if only a portion of the functionality is required.

Packages enable the module namespace to be organized hierarchically using dot notation. Packages prevent conflicts between module names in the same way that modules prevent conflicts between global variable names.

Because a package leverages the system’s built-in file structure, creating one is simple. Simply place the modules into a folder, and the folder name will serve as the package name. When importing a module or its contents, the module name and the package name must be connected by a dot.

16) What is the difference between a Set and a Dictionary?

The set is an unordered, changeable, iterable collection of data types without duplicates.

In Python, a dictionary is an ordered set of data values that is similar to a map in terms of storage.

17) What are Keywords in Python?

Python-reserved words with specific meanings are called keywords. Typically, they are employed to specify the kind of variables. Variable and function names are not permitted to contain keywords. The 33 Python keywords are as follows:

• And
• Or
• Not
• If
• Elif
• Else
• For
• While
• Break
• As
• Def
• Lambda
• Pass
• Return
• True
• False
• Try
• With
• Assert
• Class
• Continue
• Del
• Except
• Finally
• From
• Global
• Import
• In
• Is
• None
• Nonlocal
• Raise
• Yield

18) What are global, protected, and private attributes in Python?

Global variables are public variables that are defined in the global scope. To use the variable in the global scope inside a function, we use the global keyword.

Protected attributes are attributes defined with an underscore prefixed to their identifier eg. _apple. They can still be accessed and modified from outside the class they are defined in but a responsible developer should refrain from doing so.

Private attributes are attributes with a double underscore prefixed to their identifier eg. __mango. They cannot be accessed or modified from the outside directly and will result in an AttributeError if such an attempt is made.

19) How is Exceptional handling done in Python?

Try, except, and finally are the three primary keywords that are used to capture exceptions and adjust the recovering mechanism accordingly. The code block called “try” is the one that is checked for mistakes. The except block is executed in the event of an error.

The final block’s charm lies in its ability to run the code after attempting an error. Whether an error happened or not, this block still runs. Lastly, blocks are utilized to do the necessary cleanup tasks for variables and objects.

20) What are the new features added in the Python 3.9.0.0 version?

The new features in the Python 3.9.0.0 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.

21) What is the swapcase function in Python?

This function changes all uppercase characters to lowercase and vice versa within a string. It’s employed to modify the string’s current case. A replica of the string with every character in the swap case is produced by this procedure. For example:

original_string = "PyThOn iS aWeSoMe!"
modified_string = original_string.swapcase()
print(modified_string)

Output: pYtHoN Is AwEsOmE!

22) What is the use of self in Python?

The class instance is represented by the variable self. In Python, you can use this keyword to access the class’s methods and attributes. It connects the characteristics to the supplied arguments. Self is frequently considered a keyword and is used in a variety of contexts. However, in Python, self is not a keyword, in contrast to C++.

23) What is __init__?

__init__ is a constructor method in Python and is automatically called to allocate memory when a new object/instance is created. All classes have a __init__ method associated with them. It helps in distinguishing methods and attributes of a class from local variables.

Here is an example of a class Car that will clarify the functioning of __init__().

class ParentClass:
	def _init_(self):
		print("Parent Class")
        
class Child(ParentClass):
	def _init_(self):
		ParentClass._init_(self)
        print('Child Class')
        
obj = Child()

Output:

Parent Class
Child Class

24) Difference between for loop and while loop in Python

It is common practice to iterate through the items of different collection types, such as List, Tuple, Set, and Dictionary, using the “for” loop. When creating a “for” loop, developers provide the criteria at the beginning and the end.

On the other hand, the real looping functionality found in all other programming languages is the “while” loop. Python while loops are used by programmers, who only have access to the end conditions.

25) How is memory managed in Python?

Memory is managed in Python in the following ways:

Python’s private heap space is used to manage memory use. A private heap is where all Python data structures and objects are kept. This secret heap is not accessible to the programmer. This is handled by the Python interpreter instead.

The memory management of Python is responsible for allocating heap space to Python objects. Some coding tools are accessible through the core API.

Additionally, Python includes an integrated garbage collector that recycles all unused memory and releases it into the heap.

26) What is break and continue in Python?

Break: The break statement immediately ends the loop, and the control moves to the statement that follows the loop’s body.

Continue: The continue statement ends the current iteration of the statement moves the control to the subsequent iteration of the loop and skips the remaining code in the current iteration.

27) What is PYTHONPATH?

When a module is imported, the PYTHONPATH environment variable is used. It is also checked whenever a module is imported to see if the imported modules are present in any other folders. It is used by the interpreter to choose which module to load.

28) Is Python a case-sensitive language?

Yes, Python is a case-sensitive language.

29) What is the difference between Python Arrays and lists?

Python arrays are limited to having elements of the same data type; that is, an array’s data type must be homogeneous. Arrays in the C language are thinly wrapped in this wrapper, which uses a lot less memory than lists.

Python lists can hold elements of many data types or heterogeneous data types. Its enormous memory use is a drawback.

import array
a = array.array('i', [1, 2, 3])
for i in a:
    print(i, end=' ')    #OUTPUT: 1 2 3
a = array.array('i', [1, 2, 'string'])    #OUTPUT: TypeError: an integer is required (got type str)
a = [1, 2, 'string']
for i in a:
   print(i, end=' ')    #OUTPUT: 1 2 string

30) What is docstring in Python?

A Python docstring is a string that is used to describe a Python module, class, function, or method so that programmers don’t have to study the implementation details to understand what the module does.

Additionally, it is standard procedure to use docstrings to automatically generate online (HTML) documentation. The docstring should describe what the function or method does.

31) What are *args and *kwargs?

You can use the unique syntax *args and **kwargs in the function specification to pass a variable number of arguments to a Python function. It is used to pass an argument list that is keyword-free and of variable length.

Using the * makes the variable we associate with the * iterable, enabling you to perform operations on it, including higher-order operations like map and filter, as well as iterating over it.

32) Is indentation required in Python?

Running a code in Python language requires an indentation. It designates a coding block. Every line of code in functions, classes, loops, and other structures is enclosed in an indented block. Usually, four space characters are used for it. Your code will not execute correctly and will generate errors if it is not indented.

33) What is a lambda function?

A lambda function is an anonymous function. This function can have any number of parameters but, can have just one statement. For Example:

str1 = 'FavTutor'
 
upper = lambda string: string.upper()
print(upper(str1))

Output: FAVTUTOR

34) What is the difference between xrange and range functions?

In terms of functionality, range, and xrange are nearly identical. Both of them provide you the option to create an integer list that you may utilize however you see fit. The main distinction is that while x range returns an xrange object, range returns a Python list object.

This indicates that, unlike range, xrange does not truly create a static list at run-time. It uses a unique method known as yielding to generate the values as needed. This method is applied to a class of objects called generators. This means that xrange is the function to use if you have an extremely large range and would like to build a huge list.

This is particularly true if you are working with a device that is extremely memory-sensitive, like a cell phone. range will utilize all of the memory it has to generate your integer array, which could cause a Memory Error and cause your program to crash. It demands memory like anything.

35) What is the usage of help() and dir() function in Python?

The Python interpreter provides access to the help() and dir() functions, which are used to inspect a combined 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.

36) How are arguments passed by value or by reference in Python?

Pass by value: The real object is supplied as a copy. The value of the original object remains unchanged if the duplicate of the object is altered.

Pass via reference: The real object is supplied as a reference. The value of the original object will change if the value of the new object changes. Python allows parameters to be passed by reference, meaning that an actual object’s reference is passed.

37) How do you debug a Python program?

We can debug a Python program with the following code:

$ python -m pdb python-script.py

38) Explain split() and join() functions in Python?

When you need to split a string into substrings, you can use the split() method.The split() method acts on a string and returns a list of substrings. The syntax is:

<string>.split(sep,maxsplit)

In the above syntax:

• <string> is any valid Python string,
• sep is the separator that you’d like to split on. It should be specified as a string.

For example, if you’d like to split <string> on the occurrence of a comma, you can set sep = “,”.

• sep is an optional argument. By default, this method splits strings on whitespaces.
• maxsplit is an optional argument indicating the number of times you’d like to split <string>.
• maxsplit has a default value of -1, which splits the string on all occurrences of sep.

The join() method is used to form substrings into a single string. You can use the join() function to join a list of strings based on a delimiter to give a single string. The syntax of Python’s join() method is:

<sep>.join(<iterable>)

Here,

<iterable> is any Python iterable containing the substrings, say, a list or a tuple, and

<sep> is the separator that you’d like to join the substrings on.

In essence, the join() method joins all items in <iterable> using <sep> as the separator.

Example code:

string = "This is a string."
string_list = string.split(' ') #delimiter is 'space' character or ' '
print(string_list) #output: ['This', 'is', 'a', 'string.']
print(' '.join(string_list)) #output: This is a string.

39) What are negative indexes and why are they used?

Python sequences are indexed and comprise both positive and negative integers. The procedure continues in this manner for positive values, where “0” is used as the first index and “1” as the second.

The sequence for the negative number continues forward like the positive number, with the index for the negative number beginning at “-1,” which stands for the last index in the series, and ending at “-2,” which is the penultimate index.

The string can be made to accept the final character, which is indicated as S[:-1], by using the negative index to eliminate any new-line spaces from it. To display the index to represent the string in the proper sequence, the negative index is also employed.

40) What is monkey patching in Python?

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

import inspect  
  
  
class MonkeyPatch:  
    def __init__(self, n1):  
        self.n1 = n1  
  
    def add(self, other):  
        return (self.n1 + other)  
  
  
obj1 = MonkeyPatch(10)  
obj1.add(20)  
print(inspect.getmembers(obj1, predicate=inspect.ismethod))  

Output:

41) How do you access parent members in the child class?

Following are the ways using which you can access parent class members within a child class:

Using the Parent class name: As demonstrated in the example below, you may access the characteristics by using the parent class name.

class Parent(object):
  #Constructor
  def _init_(self, name):
    self.name = name
    
class Child(Parent):
  #Constructor
  def _init_(self, name, age):
    Parent.name = name
    self.age = age
    
  def display(self):
    print(Parent.name, self.age)
    
 #DriverCode
obj = Child("Interviewbit", 6)
obj.display()

Using super(): The super keyword in a child class allows access to the members of the parent class.

class Parent(object):
   # Constructor
  def __init__(self, name):
       self.name = name    
      
class Child(Parent):
   # Constructor
  def __init__(self, name, age):         
    ''' 
    In Python 3.x, we can also use super().__init__(name)
    ''' 
    super(Child, self).__init__(name)
    self.age = age
  
  def display(self):
    #Note that Parent.name can't be used
    #here since super() is used in the constructor
    print(self.name, self.age)
  
# Driver Code
obj = Child("FavTutor", 6)
obj.display()

42) How is an empty class created in Python?

There are no defined members in an empty class in Python. The pass keyword is used to generate it. The pass command in Python has no effect. Outside of the class, we can construct objects for this class.

class EmptyClassDemo:
   pass
obj=EmptyClassDemo()
obj.name="FavTutor"
print("Name created= ",obj.name)

Output:

Name created = FavTutor

43) What is the Python Global Interpreter Lock (GIL)?

Python uses the Global Interpreter Lock (GIL) type of process lock anytime it interacts with processes. Python typically employs a single thread to carry out the collection of typed statements. Because of Python’s GIL, the performance of both single- and multi-threaded processes will be equal. Python lacks multithreading because of a global interpreter lock that limits the number of threads and makes each thread function as a single thread.

44) Write a code to display the current time in Python.

currenttime= time.localtime(time.time())

print ("Current time is", currenttime)

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

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 elementwise addition and multiplication, and the fact that they can contain objects of differing types mean that 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 allow 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.

46) How can the ternary operators be used in Python?

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.

Syntax:

The Ternary operator will be given as:

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

Example:

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.

47) How will you check if a class is a child of another class?

This is done by using a method called issubclass() provided by python. The method tells us if any class is a child of another class by returning true or false accordingly.

For example:

class Parent(object):
   pass   

class Child(Parent):
   pass   
  
#Driver Code
print(issubclass(Child, Parent))    #True
print(issubclass(Parent, Child))    #False

The isinstance() method can be used to determine whether an object is an instance of a class:

obj1 = Child()
obj2 = Parent()
print(isinstance(obj2, Child))    #False 
print(isinstance(obj2, Parent))   #True 

48) What is Polymorphism and Encapsulation in Python?

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.

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

49) How do you floor a number in Python?

The Python math module includes a method that can be used to calculate the floor of a number.

floor() method in Python returns the floor of x i.e., the largest integer not greater than x.

Also, The method ceil(x) in Python returns a ceiling value of x i.e., the smallest integer greater than or equal to x.

50) How to delete a file using Python?

We can delete a file using Python by the following two methods: os.remove() and os.unlink().

Now, you can check some popular C++ Interview Questions also!

Conclusion

The above Python questions and solutions have been designed and chosen to guide you and provide you with the best knowledge across important topics. We are also here if you need any help with your Python homework to solve such questions!