How to Ace Your Python Job Interview: Essential Questions to Prepare For

In this article, I have included the questions that have been asked in the Python Developer Interviews in 2022.

Q1. What is the difference between a tuple and a list?

In Python, a tuple is an immutable sequence of objects, whereas a list is a mutable sequence of objects. This means that once a tuple is created, it cannot be modified, whereas a list can be changed by adding, removing, or modifying elements. Tuples are more memory-efficient than lists because they use less memory for storage.

Here’s an example of how to create a tuple and a list in Python:

# Creating a tuple
my_tuple = (1, 2, 3, 4, 5)

# Creating a list
my_list = [1, 2, 3, 4, 5]

To modify a list, you can use methods like append(), insert(), remove(), and pop(). However, since tuples are immutable, you cannot modify them once they are created.

Q2. What are generators in Python?

Generators in Python are a type of iterator, which allows you to iterate over a sequence of values without actually storing the entire sequence in memory. Instead, a generator yields one value at a time and then pauses until the next value is requested. This makes generators memory-efficient and faster than other types of iterators.

Generators are defined using a special type of function called a generator function. Generator functions use the yield keyword instead of return to yield values one at a time. Here's an example:

def countdown(n):
    while n > 0:
        yield n
        n -= 1

# Using the generator
for num in countdown(5):
    print(num)

In this example, the countdown() function is a generator that yields a sequence of integers from n down to 1. The yield the statement returns a value and pauses the function's execution, allowing the for loop to request the next value. When the function is called again, it resumes execution from where it left off until it reaches the next yield statement.

Generators are useful when you need to iterate over a large sequence of values, but don’t want to load the entire sequence into memory at once. They can also be used to generate infinite sequences, such as random numbers or prime numbers, that would be impossible to store in memory as a list or tuple.

Q3. What are Lambda functions? How can they be used with filter(), map(), and reduce()?

Lambda functions, also known as anonymous functions, are a type of function in Python that can be defined without a name. Unlike regular functions, which are defined using the “def” keyword, lambda functions are defined using the “lambda” keyword. They are often used for small, one-time operations and are frequently passed as arguments to other functions.

Here’s an example of how to create a lambda function in Python:

# A lambda function to add two numbers
add = lambda x, y: x + y

# Call the lambda function
result = add(5, 3)

# Output the result
print(result) # Output: 8

Lambda functions will be useful whenever a function object is required. For example, built-in functions like filter(), map(), and reduce() make use of the Lambda function as they require a function object as an argument.

Here are some examples of using lambda functions with filter(), map(), and reduce():

1. Using lambda function with map():

a = [1, 2, 3, 4, 5]
cube = lambda x: x ** 3
print(list(map(cube, a)))

Output:

[1, 8, 27, 64, 125]

In the above example, we created a lambda function “cube” that takes one argument “x” and returns “x” raised to the power of 3. We then used this lambda function with the map() function to apply the “cube” function to each element of the list “a” and return the results in a new list.

2. Using lambda function with filter():

a = [1, 2, 3, 4, 5]
even = lambda x: True if x % 2 == 0 else False
print(list(filter(even, a)))

Output:

[2, 4]

In the above example, we created a lambda function “even” that takes one argument “x” and returns True if x is even and False if x is odd. We then used this lambda function with the filter() function to filter out the even numbers from the list “a” and return the results in a new list.

3. Using lambda function with reduce():

from functools import reduce
a = [1, 2, 3, 4, 5]
sum = lambda x, y: x + y
reduce(sum, a)

from functools import reduce
a = [1, 2, 3, 4, 5]
sum = lambda x, y: x + y
reduce(sum, a)

Output:

15

In the above example, we created a lambda function “sum” that takes two arguments “x” and “y” and returns their sum. We then used this lambda function with the reduce() function to apply the “sum” function to the first two elements of the list “a”, then to the result of the previous operation and the next element of the list, and so on until all the elements have been processed and a single result is obtained.

Q4. What are list comprehensions? Create one.

List comprehensions provide a concise way to create lists in Python. They consist of an expression followed by a for clause and zero or more if or for clauses.

Syntax:

newlist = [expression for item in iterable if condition == True]

Here’s an example of a list comprehension:

# Example 1
squares = [x**2 for x in range(10)]
print(squares)

# Output: [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

In this example, we create a list of squares of numbers from 0 to 9. The expression x**2 is followed by the for clause for x in range(10), which specifies that we want to iterate over the numbers from 0 to 9.

We can also add an if clause to filter the list:

# Example 2
even_squares = [x**2 for x in range(10) if x % 2 == 0]
print(even_squares)

# Output: [0, 4, 16, 36, 64]

In this example, we create a list of squares of even numbers from 0 to 9. The if clause if x % 2 == 0 filters out odd numbers.

List comprehensions are a concise and readable way to create lists in Python, and they can often replace longer for loops and conditional statements.

Q5. What is Dictionary Comprehension in Python?

Dictionary Comprehension is a concise and readable way to create a dictionary in Python. It provides a simple way to create a dictionary by iterating over an iterable and defining the key-value pairs.

The syntax of dictionary comprehension is similar to list comprehension but instead of square brackets [], curly braces {} are used to define the key-value pairs.

Here is an example of creating a dictionary using Dictionary Comprehension:

# Creating a dictionary using Dictionary Comprehension
numbers = [1, 2, 3, 4, 5]
squares = {num: num ** 2 for num in numbers}
print(squares)

Output:

{1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

In the above example, we have created a dictionary named ‘squares’ using dictionary comprehension. The dictionary contains the squares of the numbers from the list ‘numbers’.

Q. Program to add two list elements using lambda function.

list1 = [1, 2, 3]
list2 = [4, 5, 6]

sumxy=lambda x,y: x+y

print(list(map(sumxy,list1,list2)))

Q5. Classes in Python.

Classes are user-defined data types that are used to encapsulate data and its associated functions/methods. Classes are defined with keyword class. No memory is allocated to the class until its object is created. The objector instance contains real data or information. Only a description or blueprint is created.

Classes and Objects I Tutorials & Notes | Python | HackerEarth

Q. What is the difference between private and protected in python?

Protected members of a class are accessible from within the class and are also available to its sub-classes. No other environment is permitted access to it. This enables specific resources of the parent class to be inherited by the child class. Python’s convention to make an instance variable protected is to add a prefix _ (single underscore) to it. This effectively prevents it from being accessed unless it is from within a sub-class.

Python doesn’t have any mechanism that effectively restricts access to any instance variable or method. Python prescribes a convention of prefixing the name of the variable/method with a single or double underscore to emulate the behavior of protected and private access specifiers. The double underscore __ prefixed to a variable makes it private. It gives a strong suggestion not to touch it from outside the class.

Q6. How to get the number of rows and columns in a NumPy array?

import numpy as np
a=np.array([[1,2,3],[10,2,2]])
num_rows, num_cols = a.shape
print(num_rows, num_cols)

Q7. How to create an Empty DataFrame in Python using pandas?

import pandas as pd

new_df=pd.DataFrame([])
print(new_df)

Q8. How to create a file in Python?

Q9. How to read contents from a file in Python?

Q10. What is a super() keyword in python?

Q11. How is memory managed in Python?

Memory management in Python involves a private heap containing all Python objects and data structures. … At the lowest level, a raw memory allocator ensures that there is enough room in the private heap for storing all Python-related data by interacting with the memory manager of the operating system.

Q12. What is the use of __main__ in Python?

Python's main function is a starting point of any program. When the program is run, the python interpreter runs the code sequentially. The main function is executed only when it is run as a Python program. It will not run the main function if imported as a module.

It is not necessary to define the main function every time you write a program. This is because the Python interpreter executes from the top of the file unless a specific function is defined. Hence, having a defined starting point for the execution of your Python program is useful to understand better how your program works.

https://www.guru99.com/learn-python-main-function-with-examples-understand-main.html

Q13. What are static methods in Python?

A static method can be called without an object for that class. This also means that static methods cannot modify the state of an object as they are not bound to it.

Use @staticmethod decorators to define static methods. Inside this method, we don’t use instance or class variables because this static method doesn’t take any parameters like self and cls.

https://pynative.com/python-static-method/

Q14. What are dictionaries?

Q15. Is it compulsory to have distinct keys and values in a dictionary?

Q16. How to call the Parent Class constructor in Python?

Q17. Difference between Continue, Break, and Pass?

pass simply does nothing, passis used when we want to create an empty function or class. hile continue goes on with the next loop iteration. In the case of continue the current iteration that is running will be stopped.break statement is used to break out a loop.break will terminate the loop and exit. If used inside nested loops, it will break out from the current loop.

Python break, continue, pass statements with Examples

Q18. Try catch, finally, and else in python?

Q19. what are decorators in python?

Q20. Create a program to check if a string is a Palindrome.

def palindrome(s):
    str = ""
    for i in s:
        str = i + str
    return str

s = "ababa"

if s==palindrome(s):
    print('Palindrome')
else:
    print('Not Palindrome')

Q. Program to sort the list as per the digits in the string.

import re

#Find all digit characters:
def numsort(temp_str):
    return list(map(int,re.findall(r'\d+',temp_str)))[0]

txt_list = ['10-a','2-s','622-a','621-sd']

txt_list.sort(key=numsort)

print(txt_list)

Q21. What are enumerators?

Q22. How to create your dictionary in python?

I will keep updating the questions as per my experience. Please do share in the comments section any new questions you have encountered during the Interview it can help others to ace the interview.

Q23. Which data structure among list, tuple, and dictionary is faster?

Q 24. What is recursion? Create Fibonacci series using recursion.

Q25. What is the difference between a Python script and a program?

What are the requests in APIs?

Stateless and stateful APIs

How to save data API data irrespective of the device

what type of headers can be sent in the Rest APIs

What are microservices in Rest APIs?

How to set environment variables in Linux

What is the use of NumPy and Pandas?

Q 23. What is Idempotent APIs ?

In the context of REST APIs, when making multiple identical requests has the same effect as making a single request — then that REST API is called idempotent. … Idempotency essentially means that the result of a successfully performed request is independent of the number of times it is executed.

How to ensure the scalability of REST APIs

Why do we use REST APIs

Difference between HTTP and HTTPS.

Q . HOW TO FIND THE EMPLOYEE DETAILS WHO ARE GETTING THE SAME SALARY IN EMP TABLE?

select distinct A.id,A.salary from employee A,employee B
where A.salary = B.salary and A.id <> b.id;

Q. What is the difference between range() and xrange()?