Capgemini Python Interview Questions

Ans. A decorator in Python is a function that takes another function as an argument and extends its behavior without explicitly modifying it. Here is a simple example:

def my_decorator(func):
def wrapper():
print(“Something is happening before the function is called.”)
func()
print(“Something is happening after the function is called.”)
return wrapper

@my_decorator
def say_hello():
print(“Hello!”)

2. What is the difference between a list and a tuple?

Ans. The primary difference between a list and a tuple is that lists are mutable, meaning they can be changed after their creation, whereas tuples are immutable and cannot be changed once created.

3. Explain the concatenation property in tuples.

Ans. Although tuples are immutable, you can concatenate two tuples using the + operator to create a new tuple.

4. When should you prefer tuples over lists?

Ans. Tuples should be used when the data is fixed and does not need to be changed, whereas lists should be used when the data is likely to be modified.

5. Which is better, Django or Flask?

Ans. Both frameworks have their own advantages. Django is a high-level, monolithic framework that requires a thorough understanding of its components, making it suitable for larger projects. Flask is a micro-framework that is lightweight and better for smaller applications or scripts. My personal preference is Django due to my extensive experience with it.

6. Which libraries do you use in Python?

Ans. I use several libraries, including requests, os, json, numpy, and pandas.

7. How do you combine two data frames in pandas?

Ans. You can combine two data frames using the append or concat methods. Here’s an example:

df1 = pd.DataFrame({‘A’: [1, 2], ‘B’: [3, 4]})
df2 = pd.DataFrame({‘A’: [5, 6], ‘B’: [7, 8]})
combined = pd.concat([df1, df2])

8. How do you read files in Python?

Ans. You can read files using the with open keyword:

with open(‘file.txt’, ‘r’) as file:
data = file.read()

Using with open ensures the file is properly closed after reading.

9. What is the purpose of the with keyword in file handling?

Ans.The with keyword ensures that resources are properly managed and automatically closed after their usage, which eliminates the need to manually close the file.

10. How do you check if a string is a palindrome?

Ans. You can check if a string is a palindrome using slicing:

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

11. What are the most commonly used Git commands?

Ans. Some commonly used Git commands are:

• git init: Initializes a new Git repository.
• git pull: Pulls updates from a remote repository.
• git checkout: Switches branches.
• git add: Stages changes.
• git commit: Commits staged changes.
• git push: Pushes commits to a remote repository.

12. Which databases have you worked with?

Ans. I am more comfortable with RDBMS like MySQL and PostgreSQL.

13. How do you set up PostgreSQL in Python?

Ans. You can set up PostgreSQL using the psycopg2 library:

import psycopg2
conn = psycopg2.connect(“dbname=test user=postgres password=secret”)

14. How do you configure PostgreSQL in Django?

Ans. You configure PostgreSQL in Django by updating the DATABASES setting in settings.py:

DATABASES = {
‘default’: {
‘ENGINE’: ‘django.db.backends.postgresql’,
‘NAME’: ‘your_db_name’,
‘USER’: ‘your_db_user’,
‘PASSWORD’: ‘your_db_password’,
‘HOST’: ‘your_db_host’,
‘PORT’: ‘your_db_port’,
}
}

15. Do you have experience with Docker, Jenkins, or AWS?

Ans. I have basic knowledge and understanding of Docker, Jenkins, and AWS, and have used these tools for various tasks in my projects.

16. What are Python’s key features?

Ans. Python’s key features include:

• Simple and easy to learn: Python’s syntax is clear and intuitive.
• Interpreted language: Python code is executed line by line, making debugging easier.
• Object-oriented: Python supports object-oriented programming, promoting code reuse.
• High-level language: Python abstracts low-level details, allowing developers to focus on problem-solving.
• Extensive libraries: Python has a rich set of libraries and frameworks for various tasks, including web development, data analysis, machine learning, and more.

17. What is the difference between deepcopy and copy in Python?

Ans.

• copy.copy() creates a shallow copy of an object. It copies the object itself, but not the objects it refers to.
• copy.deepcopy() creates a deep copy of an object. It copies the object as well as all the objects it refers to, recursively.

18. How does Python manage memory?

Ans. Python manages memory using a private heap space. The Python memory manager handles the allocation of heap space for Python objects. The built-in garbage collector is used to recycle unused memory to make it available for heap space.

19. What is a lambda function in Python?

Ans. A lambda function is a small anonymous function defined with the lambda keyword. It can have any number of arguments but only one expression. The expression is evaluated and returned. Syntax:

lambda arguments: expression

add = lambda x, y: x + y
print(add(2, 3)) # Output: 5

20. How do you handle exceptions in Python?

Ans. Exceptions in Python are handled using the try, except, else, and finally blocks. Example:

try:
# Code that may raise an exception
result = 10 / 0
except ZeroDivisionError:
# Code to handle the exception
print(“Cannot divide by zero.”)
else:
# Code to execute if no exceptions occur
print(“Division successful.”)
finally:
# Code to execute regardless of whether an exception occurs
print(“Execution complete.”)

21. What are Python iterators and generators?

Ans.

• Iterators: An iterator is an object that contains a countable number of values and can be iterated upon, meaning it returns one value at a time.
• Generators: Generators are a simple way of creating iterators using a function and the yield statement. Each call to yield produces a value and suspends the function’s state, which is resumed when the next value is requested.

22. How do you create a virtual environment in Python?

Ans. A virtual environment in Python can be created using the venv module:

python -m venv myenv

To activate the virtual environment:

• Windows: myenv\Scripts\activate
• Mac/Linux: source myenv/bin/activate

23. What is list comprehension in Python?

Ans. List comprehension provides a concise way to create lists. It consists of brackets containing an expression followed by a for clause. Example:

squares = [x**2 for x in range(10)] print(squares) # Output: [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

24. Explain the difference between ‘==’ and ‘is’ operators.

Ans.

• == checks for value equality. It compares the values of both operands.
• is checks for reference equality. It compares the memory locations of both operands.

a = [1, 2, 3] b = a
c = a[:]

print(a == b) # Output: True
print(a is b) # Output: True
print(a == c) # Output: True
print(a is c) # Output: False

25. How do you create a dictionary in Python?

Ans. A dictionary in Python can be created using curly braces { } with key-value pairs, or by using the dict()  function:

# Using curly braces
my_dict = {‘name’: ‘John’, ‘age’: 30}

# Using dict() function
my_dict = dict(name=’John’, age=30)

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Capgemini Python Interview: Conclusion

Capgemini python interview consists of 4 rounds. The technical, analytical and behavioral aspects of the candidate is thoroughly checked during the process. Candidate can use this article to understand the process and also practice for their interview with sample questions given here.