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TCS Python Interview Questions

Last Updated on July 20, 2023 by Mayank Dham

TCS asks Python interview questions because it is a popular programming language and a skill in high demand. Python is a versatile programming language that can be used for a variety of tasks including web development, machine learning, scientific computing, and artificial intelligence. As a result, TCS and many other companies are looking for Python experts who can solve complex problems and build scalable and robust software systems. TCS can assess a candidate’s knowledge of the language and ability to apply it to real-world problems by asking Python interview questions, which helps to ensure that they are hiring talented and capable software developers.

What is Python ?

Python is a general-purpose, high-level, interpreted programming language that is widely used for web development, data analysis, scientific computing, and artificial intelligence applications. Python was developed in the late 1980s and has since become one of the world’s most popular programming languages.

TCS (Tata Consultancy Services) choose to work with Python for several reasons, including

  • Versatility: Python is a powerful programming language that can be used for a wide range of activities such as web development, data analysis, scientific computing, and artificial intelligence.
  • Large community: Python has a large and active community of developers who create and share libraries and tools that can be leveraged by organizations like TCS.
  • High demand: There is high demand for Python skills in the job market, and many organizations are looking for developers who have experience with Python.
  • Ease of use: Python is a relatively easy language to learn and use, making it accessible to a wider range of developers.
  • Productivity: Python’s concise and readable syntax can increase developer productivity and help organizations like TCS deliver projects faster.

By using Python, TCS can leverage its versatility and popularity to build a variety of applications and solve complex problems for its clients. Additionally, with a large pool of developers and a high demand for Python skills, TCS can find and retain the talent it needs to continue growing and delivering value to its clients.

TCS Python Interview Questions

Here is a list of TCS Python interview questions that were recently asked of candidates. These questions are meant for both new and experienced professionals.

Q1 – How is Python an interpreted language?
Answer – Python is considered an interpreted language because the source code is executed line by line, at runtime, by an interpreter, rather than being compiled to a machine-readable format ahead of time like in compiled languages. This allows for greater flexibility and easier testing and debugging, but can result in slower execution times.

Q2 – How do you handle exceptions in Python?
Answer – In Python, exceptions can be handled using a try-except block. You write the code that might raise an exception in the try block and specify how to handle it in the except block. Here’s an example:

   result = 10 / 0
except ZeroDivisionError:
   print("Can't divide by zero")

You can also include an optional else block after the except block, which will be executed if no exception was raised in the try block.

You can catch multiple exceptions in one except block using parentheses, like this:

   result = 10 / 0
except (ZeroDivisionError, TypeError):
   print("An error occurred")

In Python, it’s also possible to raise an exception manually using the raise statement.

Q3 – What is the difference between a list and a tuple in Python?
Answer – In Python, a list is an ordered, mutable, and dynamic collection of elements, while a tuple is an ordered, immutable, and fixed-size collection of elements.

This means that:

  • Lists allow you to add, remove, and modify elements, while tuples do not.
  • Lists can grow or shrink in size, while tuples have a fixed number of elements that cannot be changed after they are created.
  • Lists are defined using square brackets [], while tuples use parentheses ().

Tuples are often used to return multiple values from a function, for instance. Because tuples are immutable, they are also often used for cases where data should not be changed, such as coordinate pairs or other data that should have a fixed relationship.

Q4 – Can you explain how Python implements dynamic typing?
Answer – Variables in Python do not have a predefined data type. A variable’s type is determined at runtime based on the value it holds. This is called dynamic typing.

For example,

x = 10

x = "hello"


In this example, the same variable x holds an integer value and then a string value, and its type changes dynamically based on the values it holds.

Dynamic typing makes Python very flexible and easy to use because you don’t have to specify the data type of a variable when you create it. The type of a variable is determined automatically based on the value you assign to it. This also makes it possible to write more generic functions that can work with multiple types of data.

However, this flexibility can also lead to runtime errors if you try to use a variable in a way that is incompatible with its type. For example

x = "hello"
print(x + 10) # This will result in a TypeError.

Dynamic typing in Python is often considered one of its strengths, as it allows for rapid prototyping and exploration, but it also requires that you pay more attention to the types of values your code is working with.

Q5 – How will you remove duplicate elements from a list?
Problem Statement – Given a list, the task is to remove the duplicate elements from the list.


Input: [1, 1, 2, 2, 2]
Output: [1,2]
Input: [1, 2, 3, 1, 2, 4, 5, 6, 5]
Output: [1, 2, 3, 4, 5, 6]

Answer – You can remove duplicate elements from a list in Python using the set data structure, which only stores unique elements. Here’s the python code for this:

numbers = [1, 1, 2, 2, 2]
unique_numbers = set(numbers)
unique_numbers = list(unique_numbers)



Another way to remove duplicates from a list is to use a loop and check if an element is already in a new list. If it is not, add it to the new list. Here’s the python code for this:

numbers = [1, 2, 3, 1, 2, 4, 5, 6, 5]
unique_numbers = []
for number in numbers:
   if number not in unique_numbers:


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

Q6 – What are local variables and global variables in Python?
Answer – Local variables and global variables are two types of variables in Python. Local variables are only accessible within a specific function, and they are created when the function is called and destroyed when the function returns. Global variables, on the other hand, can be accessed from any part of the code and are created when the program starts and destroyed when the program ends. It’s generally a good idea to use local variables whenever possible, as they promote modularity and prevent unintended side effects. However, global variables can be useful when you need to share data between functions or across different parts of your code. If you want to modify a global variable from inside a function, you need to use the global keyword to indicate that you want to access the global scope.

Q7 – Can you explain how Python handles memory management?
Answer – Python has a built-in memory manager that automatically handles the allocation and deallocation of memory. The memory manager keeps track of all the objects in your program and automatically frees up memory that is no longer being used. This process is called garbage collection.

The memory manager also manages a heap, which is a block of memory that is used to store objects. When you create an object in Python, the memory manager allocates space for that object on the heap. When the object is no longer being used, the memory manager automatically frees up the memory that was used by that object.

In Python, all objects have a reference count, which is the number of references to the object that exists in the program. When the reference count of an object drops to zero, the memory manager knows that the object is no longer being used and frees up the memory used by that object.

This automatic memory management makes it easy to write Python code, as you don’t need to worry about freeing up memory manually. However, it’s important to be aware of the memory usage of your program, especially when working with large amounts of data, as it can impact the performance of your program.

Additionally, Python provides tools for manual memory management, such as the gc module, which provides access to the garbage collector and allows you to control the collection of unreachable objects. However, these tools should be used sparingly, as they can be complex and can impact the performance of your program if used incorrectly.

Q8 – How to overload constructors or methods in Python?
Answer – In Python, there is no direct way to overload constructors or methods like in some other programming languages. However, you can achieve a similar effect by using default arguments.

For example, you can have multiple constructors with different sets of arguments by using default values for some of the arguments. Here’s an example:

class Rectangle:
    def __init__(self, width=0, height=0):
        self.width = width
        self.height = height

rect1 = Rectangle(10, 20)
rect2 = Rectangle(15)
rect3 = Rectangle()

In this example, the init method acts as multiple constructors, as it can be called with different sets of arguments, and the default values for width and height ensure that the objects are created even if the arguments are not specified.

Similarly, you can achieve method overloading by using default arguments. For example,

class Calculator:
    def add(self, a, b=0):
        return a + b

calculator = Calculator()
result = calculator.add(10, 20)
result = calculator.add(10)

In this example, the add method acts as multiple methods, as it can be called with different sets of arguments, and the default value for b ensures that the method can be called even if b is not specified.

Q9 – What is the purpose of Python modules and packages?
Answer – In Python, modules and packages are used to organize and structure code into reusable and easily maintainable components.

A module is a single file that contains a collection of related functions, classes, and variables. Modules allow you to break your code into smaller, manageable pieces and to share code across different parts of your program. Modules can be imported into other parts of your program using the import statement. For example, the math module provides mathematical functions such as sin, cos, and sqrt, and you can use these functions in your program by importing the math module and then calling the functions math.sin(x), math.cos(x), etc.

A package is a collection of modules. Packages allow you to organize your code into subdirectories and distribute your code across multiple files. Packages also allow you to namespace your code, so you can avoid naming collisions between different parts of your program. To create a package, you need to create a directory with the same name as the package and then create an file inside the directory. The file can be empty or can contain code that is executed when the package is imported.

In summary, modules and packages are important tools for organizing and structuring code in Python, and they make it easier to create reusable and maintainable code.

Q10 – How is Multithreading achieved in Python?
Answer – Multithreading in Python is achieved using the threading module. The threading module provides a Thread class that can be used to create and run threads in your program.

A thread is a separate execution context that runs concurrently with other threads in your program. By using multiple threads, you can divide your program into smaller, more manageable tasks, and run these tasks in parallel. This can help to improve the performance of your program and make it more responsive.

Here’s the syntax of how to create and run a thread in Python:

import threading

def worker():
    print("Thread started")

thread = threading.Thread(target=worker)

In this example, the worker function is defined and then passed as the target argument to the Thread constructor. The start method is called to start the thread, and the worker function is executed in a separate thread.

It’s important to be aware of the Global Interpreter Lock (GIL) when using threads in Python. The GIL is a mechanism that ensures that only one thread can execute Python bytecode at a time, even on multi-core systems. This means that multithreading in Python is not as efficient as in other programming languages, and you may need to use other techniques, such as multiprocessing, to achieve parallelism in your program.

Q11 – write code to reverse a string in Python.
Here is the python code for this:

def reverse_string(s):
    return s[::-1]

input_string = input()
reversed_string = reverse_string(input_string)
print(f"The reversed string is: {reversed_string}")





Q12 – What is the difference between the / and //operators in Python?
Answer – The / and // operators are both used for division in Python, but they behave differently.

The / operator performs true division, which returns a floating-point number that represents the exact result of the division. For example,

>>> 10 / 3

The // operator performs floor division, which rounds the result down to the nearest integer. For example,

>>> 10 // 3

So, the difference between the / and // operators is that the / operator returns a floating-point number, while the // operator returns an integer. The // operator is useful when you want to round down the result of a division, while the / operator is useful when you need to perform an exact division and keep the fractional part.

Q13 – What is slicing in Python?
Answer – Slicing in Python refers to extracting a portion of a sequence (such as a string, list, or tuple) and creating a new sequence from that portion. In Python, sequences can be sliced using square brackets [] and a colon : operator.



where the sequence is the original sequence, start is the index of the first element to be included in the slice (defaults to 0), and end is the index of the first element that should not be included in the slice (defaults to the length of the sequence).

For example, the following code creates a slice of the first three elements of a list:

numbers = [0, 1, 2, 3, 4, 5]
first_three = numbers[0:3]


[0, 1, 2]

Slicing can also include an optional step value, which is the number of elements to skip between each element in the slice. For example, the following code creates a slice that includes every second element of a list:

numbers = [0, 1, 2, 3, 4, 5]
every_second = numbers[0:6:2]


[0, 2, 4]

Slicing is a convenient and powerful way to extract and manipulate portions of sequences in Python.

Q14 – Write a Python program that determines whether or not a given string is a palindrome without using an iterative method.
Here is the python code for this:

def is_palindrome(string):
    return string == string[::-1]

string = input()
if is_palindrome(string):
    print(f"{string} is a palindrome")
    print(f"{string} is not a palindrome")





Q15 – What is self in Python?
Answer – In Python, self is a special parameter that is used to refer to the instance of an object within a class method. When you create an instance of a class, you can use the instance to call its methods, and the self parameter allows you to access the instance’s attributes and methods within the class.

Here’s an example that demonstrates the use of self in a class method:

class Rectangle:
    def __init__(self, width, height):
        self.width = width
        self.height = height

    def area(self):
        return self.width * self.height

rect = Rectangle(10, 20)
result = rect.area()

In this example, the Rectangle class has a init method that initializes the width and height of the rectangle and an area method that calculates the area of the rectangle. When you call rect.area(), the area method is executed, and self refers to the rect instance. The self.width and self.height expressions access the width and height attributes of the rect instance, and the return statement returns the calculated area.

The self parameter is not explicitly passed when you call a method on an instance, as it is automatically passed by Python. When you call rect.area(), the rect instance is passed as the self parameter to the area method, so you can use self to access the rect instance within the method.

Frequently Asked Questions(FAQs) on TCS Python Interview Questions

Given Below are some frequently asked questions (FAQs) on TCS Python interview questions:

Q1 – What type of questions can be asked in a TCS Python interview?
Answer – Python interview questions can cover a range of topics, including basic syntax, data structures, algorithms, object-oriented programming, file handling, error handling, libraries, frameworks, and best practices. The questions may vary based on the role and level of experience, but the interviewer will typically aim to assess the candidate’s understanding of the language and their ability to apply it to real-world problems.

Q2 – What are some common coding questions in a TCS Python interview?
Answer – Common coding questions in a TCS Python interview may include writing programs to implement specific algorithms, solve mathematical problems, or perform certain operations on data. The interviewer may also ask the candidate to write code to solve a particular problem, explain how they would debug a program, or refactor existing code to make it more efficient.

Q3 – How can I prepare for a Python interview?
Answer – Preparation is key to success in a Python interview. You can start by reviewing the basic syntax and features of the language, as well as more advanced topics such as object-oriented programming and error handling. You should also practice writing code and solving problems, and get comfortable with common libraries and frameworks. It’s also helpful to read up on best practices, design patterns, and current trends in the Python community.

Q4 – What should I expect in a TCS Python coding challenge?
Answer – A Python coding challenge is a test of your programming skills and ability to write code to solve specific problems. The interviewer may ask you to write code on a whiteboard, on paper, or on a computer, and may provide a problem statement or a code snippet to build upon. The interviewer will typically aim to assess your problem-solving skills, coding style, and ability to communicate your thought process.

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