TOP 21 Python Interview Questions & Answers | Freshers & Experienced Candidates | Crack Interviews

did you know python has been around for more than 30 years and yet it is one of the most popular programming languages in the world so it is no wonder that most companies even man companies ask questions on python India interviews and if you are someone who is looking for a job as a data analyst data scientist or even as a developer then this video is for you in this video we'll cover top 21 python conceptual questions that are often asked in Python interviews this video is part of our new series on interview preparation where we'll bring to you valuable material on programming data science and generative AI so do subscribe to our channel so that you get free access to all of our learning material that is coming to you as part of the series on this note let's begin our discussion on the top 21 python interview questions all right our first question is why is python called an interpreted language interpreted language means any programming language which executes instructions directly and line by line it means it does not compile the program like C plus plus or Java does rather it directly runs the complete program all at once and while running the program wherever it encounters an error it stops and if you think about it this makes python easier to debug because you get to know exactly where the error occurred in your code now python doesn't need a separate compilation step like C plus plus or Java you can just write python code and run it directly here's what it means C plus plus or Java is required to be built and linked building process involves using a compiler to translate the human related source code into machine readable object code files the linking process combines these object code files together into a final executable program these steps are necessary in languages like C plus plus or Java to produce an executable program that a computer can thereafter run on the other hand in Python you can directly run the code without going into any of these separate steps you can just write python code and run it directly this is the precise reason why python is fast to develop as well now let's move on to our next question do we need indentation in Python the obvious answer is yes you need indentation because it is part of the language's syntax now let's understand why indentation helps in reading the code better and that is why python has made it compulsory every programming language provides mechanism to manage and control how the coding blocks are written in Python it is indentation and it is different in Java for example in Java when we need to construct a for Loop we have to put the blocks or statements inside the for Loop within the braces and the statements inside the for Loop need node B indented it can be in the same line but when it comes to python the print statement inside the for Loop should have spaces that is four spaces that is how indentation Works in Python all right now let's move on to the third question what are built-in data types in Python in Python a data type defines the kind of values a piece of data can have and what operations can be performed on it let's understand in this way imagine different kinds of containers a jar a jug a box and a basket now each container is suitable for holding different kinds of things you wouldn't put water in a basket right it's for things like fruits similarly in Python you use different data types to hold different kinds of values like integers or strings now let us look at various data types we have in Python we have text type we have numeric types sequence types map types set types Boolean type binary types and none type and in Python in case you want to know the data type of a variable just use the type function let's see how it works now in output you will see the data type of the variable the type function basically takes the variable as an argument and gives the data type of the variable all right let's move on to our fourth question what are classes and objects in Python in Python a class is a blueprint for creating objects on the other hand an object is an instance of a class what do I mean by this well class can be considered to be your blueprint and objects are real world entities which are defined or created from classes let's take an example here this is a blueprint of a house the blueprint defines the layout of the house the number of rooms the type of rooms including kitchen bathroom bedroom Etc the material used Etc and now with this blueprint we can create an unlimited number of houses an object on the other hand is an instance of a class it's a real tangible thing that you create using the blueprint over here it is house one house two and house three uh are in fact objects actual houses created from the house class which is the blueprint they have the structure defined by the house class now let's move on to our fifth question what is a dictionary in Python dictionary is an unordered collection of elements in other words a dictionary in Python is a built-in data structure for storing collections of objects or values these elements in our dictionary are stored as key value pairs this means there is a specific key and there is a value which is assigned to a key this is pretty much like a real live dictionary where you look up a word known as the key to get its definition on a specific page which is known as the value for example in the dictionary my dictionary over here the key is name and the value for the key is John in this example name age city are the keys and John 30 and New York are their respective values this dictionary represents a person and we can use it to look up details about the person like their name age and city by the way dictionaries are mutable in nature you can modify the dictionary by adding changing or removing key value pairs as shown in this example all right let's move on to question number six what are python functions and how do they help in code optimization a function is a block of code that can be called by other parts of your program in other words it's a piece of reusable code that you can run whenever you need it instead of writing the same code multiple times so how do you write a function first you define functions using the def keyword followed by the function name parenthesis and a colon followed by it the code block within every function is indented and this is how a function looks like in this example add numbers is a function that takes two parameters number one and number two adds them together and Returns the result when we call add numbers 3 comma 5 it executes the code within the function and Returns the sum of 3 and 5 which is 8. so how does it help in code optimization well functions allow you to reuse code by encapsulating it in a single place and calling it multiple times from different parts of your program in this example say hello is a function that doesn't take any parameters when we call say hello uh it simply prints hello world and what else well functions give improved readability to your program by dividing your code into logical blocks functions can make your code more readable and easier to understand it also reduces redundancy of your code and makes it cleaner and readable functions also make code easier for testing functions allow you to test individual blocks of code separately so you can debug individual functions independently of the rest of the code it also provides improved performance functions can also help to improve the performance of your code by allowing you to use optimized code libraries or by allowing the python interpreter to optimize the code more effectively now let's move on to question number seven what are python sets explain some of the properties of sets in Python a set is an unordered collection of unique objects sets are defined using curly braces each and every value is separated by commas and you know what is more interesting it is not ordered for example we give input apple banana cherry and while giving output the order is changed so as you can see it is not ordered similarly sets are often used to store a collection of distinct objects that means they automatically remove duplicate values for example over here we have defined a set having elements apple banana Cherry orange and if we add another element to this set in the output you will see apple is not repeated twice now sets are also used to perform membership tests that is to check if an object is indeed present in a set and this is how it is done and for this piece of code the output is yes because banana is definitely present in the fruit set now let's move on to the properties of sets first one is sets are unordered as I explained secondly sets are unique third is sets are mutable so you can add or remove elements from a set using the add and remove methods and fourthly sets are not indexed sets do not support indexing or slicing so you cannot access individual elements of a set using an index all right now let's move on to question number eight what is the difference between list and a tuple list and Tuple are essentially data structures so let's first understand what data structures are in Python data structures are a way of storing and organizing data efficiently why is this important when you store your data in an unorganized manner this will allow you to easily access and perform operations on the data now you will want to store data in different ways to cater to the need of Dr maybe you want to store all data types together or you want to store data in such a manner which will help in Faster retrieval or maybe in some ways that stores only distinct they data items luckily python has a host of inbuilt data structures out of all less than Tuple are two types of built-in data structures that are used to store collections of data now let's look at the differences first is mutability lists are mutable they can be modified after creation so you can do adding removing changing items Etc whereas tuples are immutable once they are created their content cannot be changed second difference is syntax lists are defined using square brackets as you can see and tuples are defined using parentheses again you can see third key difference is performance lists take up more memory due to their ability to change and grow whereas tuples are more memory efficient and usually faster because they are immutable and this is how a list looks like and this is how a tuple looks like all right now let's move on to our question number nine what is the difference between a module and a package now this is a very common question asked during interviews modules and packages in Python are responsible for implementing the modular programming Paradigm first let's see what a module is module in Python is simply a DOT py file containing python code it can contain any number of functions classes and variables it is a very common practice to put together a set of related functionalities together so that you can reuse them whenever you want now how do you do that once a module is created it can be imported and used in another python script using the import statement once you use this syntax this will import all the functions classes and variables that are present inside that module let's see how our module is used first we'll create a file called math.py this will contain functions of arithmetic operations that is addition then multiplication subtraction and division then we create another file called arithmetic dot py where we import the maths dot py file at the very beginning we do that by writing import maths as you can see now let's see how it works we assign a value of 2 to X and 3 to Y and then after we call add and multiply functions from the math module and as you can see the output we get is what is expected 5 and 6. now what if I want to add more complex functionalities for that I need to create another file and import it as another module but just imagine how repetitive it would be if we have to import 10 such modules uh now there is a solution for that uh we put together all the related modules inside our directory and we call it a package so a package in simple terms is a collection of modules it is a way of organizing related python modules into a directory basically it's a directory that contains multiple module files along with a standard file called init.py which tells python that the directory is indeed a package now let's move on to our question number 10 what is indexing and what is negative indexing we need to understand the concept of eye tables first before we get into indexing it is a special type of object in Python that can iterate over what do I mean by that well you can cross or go through all the different elements or entities contained within the object and the object could be a list a tuple a string dictionary Etc are all eye treble in Python and yes the iteration part could easily be achieved with the help of for Loops so in simple words itables are something you can Loop over now when we understand what itables are now let's focus on indexing indexing is basically a way to access individual elements or groups of elements in an iterable by their position in other words you can access a specific element of your choice within an i treble such as a list and do your operations with it depending on your needs let me show you how I have this list of strings with the various fruit names in the very beginning python allocates memory for the list and each element is indexed this way in Python indexing starts from 0 as you can see so if you have a list called my list having elements like apple banana Cherry the index of Apple is 0 banana is one and Cherry is two and this indexing that we have discussed is the one which is generally used and is called positive indexing now what is negative indexing negative indexing simply means the last element of the collection has an index of -1 and the second last has minus 2 and so on now let's move on to question number 11 which is explain the logical operators in Python in Python The Logical operators and or and not can be used to perform Boolean operations this is done in order to determine whether a condition is true or false what do I mean by this well in Python there can be situations where there are two or more conditions and we need to check which condition is true and which is false and for these situations we use logical operations there are three types of logical operators and or and not the and operator returns true if both operands are true if either condition is false it returns false like this then or operator returns true if at least one of the operand is true if both conditions are false it returns false all right thereafter not operator Returns the opposite of operand if the condition is true it returns false and if the condition is false it returns true logical operators are often used in control flow constructs such as if LF and while statements to combine conditions and make decisions based on multiple criteria now let's move on to our question number 12 explain the use of Lambda expression in Python and when is it useful well the Lambda expression or function is used to define a function without a name in Python it is also known as Anonymous function because it doesn't have a name like regular functions too the difference is that in a regular function you have to define the function Lambda is useful in situation where you need a small temporary function that you want uh need to use elsewhere in your code and this is how Lambda function looks Lambda function can have any number of arguments but can contain only a single expression this means you have to write the entire thing in one line one of the foremost use cases of Lambda is in functional programming wherein it allows you to supply a function as a parameter to a different function for example map filter Etc now let's move on to question number 13 explain slicing in Python slicing in Python is a feature that allows you to access a subset or a slice of a list or a sequence in other words slicing a list gives you another list instead of a single element this means each object in the list has a specific index slice specifies a start index and an end index of a list for example in the list Apple has an index of 0 banana has an index of one Cherry has index of two and so on now I want the fruit banana cherry and date from the list we would need to slice it out from the list so we slice it out over here by the way keep in mind that The sublist Returned will contain the elements starting from the start index but will exclude the end index element so we see the output is basically banana cherry and date one more thing if you leave out the start index it will assume it to be zero and if you leave out the end index again the output will be the entire length of the list all right now let's move on to question number 14 explain the difference between mutable and immutable objects in Python for this let's first understand what an object is in Python in Python almost everything is an object including numbers strings lists dictionaries functions and even modules now objects can be of two types mutable and immutable if you remember correctly we have already talked about this when we were talking about list being mutable and Tuple being immutable now let me talk about this in detail so what does mutable means these are objects whose content or state can be changed after they are created we have seen an example of a list which is a mutable object before we have seen an example of a list which is a mutable object now let's see a different example with a dictionary in this example we have a dictionary called student and we modify the value associated with the key age from 25 to 26. we also add a new key value pair gender female to the dictionary because the dictionary is mutable so its content can be changed and updated as needed moving on what are immutable objects well these are objects whose content or state cannot be changed after they are created if you try to change the state you will actually create a new object we have seen how a tuple looks like another example of a mutable object is a string as you can see in this code trying to directly change the character at index 0 in the string name will raise a type error because strings are immutable instead we need to create a new string modified name with the desired change which is replacing the first character with M now let's move on to question number 15 what is the use of pass keyword in Python so pass is a null statement that basically does nothing it is often used as a placeholder where a statement is required syntactically but no action needs to be taken so basically it's just there to ensure your code runs without syntax error until you are ready to write the real code for that blog let me show you how in this case pass allows you to define the function my function without any actual code this can be useful when you are sketching out a program and aren't ready to write the function yet now let's move on to question number 16 what are generators tell about their use in Python suppose you want to make a huge list of numbers from 1 to a billion if you create a list for this it will consume a lot of your computer's memory which is not efficient at all instead what you can do is you can create a generator that produces these numbers one at a time and only when they are needed this way you only need memory for one number at a time not all billion numbers together well the official definition goes something like this a generator in Python returns an iterator that produces sequences of values one at a time we use the yield keyword to produce values now let's see how it works in this example count up 2 is a generator that counts from 1 up to the value of n the yield keyword is used to specify what value the generator should produce when it's iterated over then it pauses the function until the next value is needed the function State including local variable is saved between yields so it can pick up where it left off when you use the generator in a for loop with count up to let's say 10 it prints the number 1 to 10 one at a time it generates each number as the for Loop ask for the next number rather than generating all the numbers at once which would be less memory efficient moving on to question number 17 what is shallow copy and deep copy in Python well in Python deep copy and shallow copy are methods used to copy objects when we use the equal operator it only creates a new variable that shares the reference of the original output in order to create real copies or clones of these objects we can use the copy module in Python they are of two types shallow copy and deep copy now let's focus on shallow copy first a shallow copy is a copy of an object that stores the reference of the original elements the simple way to understand this is uh it's like making a list of items you own if any of those items is a box with more stuff inside your list just mentions the Box not the stuff inside so if you change the content of the box it will be changed in both the original and the copy now let's come to deep copy a deep copy is a process where we create a new object and copy elements recursively the independent copy is created of the original object and its entire set of elements changes made in one object do not affect the other what do I mean by this it's like making a detailed list of items you own if you have a box with more stuff inside of it you list down all the stuff in the Box too so even if you change the contents of the box in the original list it won't change in the copy let's move on to question number 18 what is inheritance in Python also what is the difference between single and multiple inheritance well in Python inheritance is a way to define a new class also called a child class that takes on attributes and methods from an access testing parent class what do I mean by this imagine a family where a child inherits traits from their parents like their hair color or height in Python inheritance work similarly a child class can inherit characteristics and behaviors from a parent class now there are two types of inheritance single inheritance and multiple inheritance single inheritance is when a class inherits from a single superclass or a parent class think of it as a child who inherits trades from one parent let me show you how in this code child is inheriting from the parent it means child class has all the methods that parent has plus any additional methods as defined now let's see what multiple inheritance is multiple inheritances when a class can inherit from more than one superclass or parent class in our analogy imagine a child who can inherit rates from both parents in this case child is inheriting both from the mother and the father so it has access so it has access to the methods from both classes the order of inheritance matters in multiple inheritance so if both mother and father had a method with the same name the method from mother would be used because mother appears first now let's move on to question number 19 what is exception handling and how is it done in Python well exception handling in Python involves using special blocks of code so that it can catch and handle errors or exceptions that occur when your program runs basically it is done to help your program keep running even when something unexpected happens the main keywords for exception handling in Python are try except finally and race at this point let me show you how it works in this code if you enter a valid integer it prints the number and this gets executed no matter what whereas if you enter something thing that's not a valid integer like a string or a float it raises a value error the exception that moves to the accept block prints that's not a valid number and then this gets executed no matter what the finally block is optional and is used for code that you want to be executed no matter whether an exception occurred or not now let's move on to question number 20 what is the use of decorators in Python in Python decorators are a special kind of function that add extra functionality to another function what do I mean by this well they provide a way to wrap a function with another function which can add functionality before or after the original function is called without permanently modifying it let me show you how when you call say hello it's not directly called anymore it's now wrapped with the wrapper function inside my decorator the my decorator syntax is just an easier way of saying say hello equal to my decorator say hello now let's look at the output in this example my decorator is a decorator that takes a function as input and defines a new function wrapper that adds some code before and after calling function the at the rate my decorator line in Python's decorator Syntax for applying The Decorator to the say hello function all right now we come to our last question which is explain the difference between is and the equality operator in Python the equality operator checks for Value equality it compares the values of the two objects and returns true if they are equal and false if they are not equal it is basically a comparison operator that checks for equality it compares the value of the two objects to determine if they are equal in this case list 1 and list 2 are two different objects but they have the same value therefore list one is equal to list 2 is actually true now s checks for identity it returns true if both variables point to the same object and Falls otherwise basically it checks whether the two variables point to the same object in memory not their content in this case list 1 and list 2 are pointing to the same object in memory so list one is list two is true so guys that's all we had for this video for you I hope you like that content if you did give it a thumbs up uh and do subscribe to our channel for more interesting data Tech content good luck to you bye

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Id: IT9A6ZtR_9s

Length: 29min 14sec (1754 seconds)

Published: Sun Aug 27 2023