Web Scraping With GPT: Translate Foreign News Headlines

 

In a world brimming with diverse information, the ability to navigate, extract, and understand global content has become indispensable. The Coursera course “AI Web Scraping with GPT: Translating Foreign News Headlines,”  introduces learners to a groundbreaking approach that combines web scraping and AI-powered translation. This blog delves into the unique features and potential applications of this course.

Why This Course Stands Out

Designed for tech enthusiasts, beginners, and professionals alike, this course merges essential technical skills with practical applications. Rudi Hinds’ offering is particularly noteworthy for:

Focusing on Real-World Relevance: The course centers on scraping and translating foreign news headlines, a practical use case with applications in journalism, market research, and global communication.

Utilizing Advanced AI Tools: Learners are introduced to OpenAI’s GPT technology, renowned for its powerful natural language processing and translation capabilities.

Step-by-Step Learning: The course ensures accessibility by breaking down complex tasks into manageable steps, making it ideal for learners with basic Python skills.

Course Overview

1. Foundations of Web Scraping

Participants are guided through the fundamentals of web scraping using Python libraries like BeautifulSoup. This foundational skill allows users to extract structured data, such as foreign news headlines, from various websites.

2. Integrating GPT for Translation

A standout feature of the course is its integration of GPT for translating foreign headlines into the learner’s preferred language. Learners gain hands-on experience working with OpenAI’s API to:

• Generate accurate translations.
• Maintain contextual integrity across different languages.
• Experiment with parameters to fine-tune the output.

3. Storing and Analyzing Data

The course also covers data organization and storage, providing learners with the skills to compile, sort, and analyze translated headlines. This opens doors to insights into global trends and narratives.

4. Practical Applications

By the end of the course, participants can:

• Automate multilingual data collection.
• Analyze media trends across languages and regions.
• Apply these techniques to personal, academic, or professional projects.

What You Will Gain

The course equips learners with a versatile skill set that combines programming, AI, and global communication. Key takeaways include:

Technical Expertise: Hands-on experience with Python, BeautifulSoup, and OpenAI’s GPT.

Global Awareness: An ability to explore and understand foreign media content in your native language.

Scalable Insights: Skills that can be adapted to various domains, from business intelligence to policy research.

Real-World Applications

1. Journalism and Media

Journalists can use these skills to monitor and analyze international news stories, ensuring diverse coverage and perspectives.

2. Business Intelligence

Marketers and business strategists can uncover global trends, identify opportunities, and assess risks by translating and analyzing international headlines.

3. Education and Research

Academics and students can explore multilingual data sets, enabling cross-cultural studies and fostering global insights.

Why Learn AI-Powered Web Scraping and Translation?

With the proliferation of information online, the ability to automate data extraction and translate it effectively is a game-changer. Rudi Hinds’ course provides an accessible pathway to harnessing these technologies, empowering learners to:

Break language barriers.

Analyze data at scale.

Gain a competitive edge in an increasingly data-driven world.

Join Free: Web Scraping With GPT: Translate Foreign News Headlines

Conclusion:

 “AI Web Scraping with GPT: Translating Foreign News Headlines,” is a must-try for anyone looking to explore the intersection of AI and data. Whether you’re a tech enthusiast, researcher, or professional aiming to stay ahead of the curve, this course provides a robust foundation in one of the most impactful applications of AI today.

Read More

Python Coding Challange - Question With Answer(01171224)

 

Explanation:

1. Tuple t Creation:

• t is a tuple with three elements:
  • 1 → an integer
  • [2, 3] → a mutable list
  • 4 → another integer
• So, t looks like this:
  
  
• t = (1, [2, 3], 4)

2. Tuple Immutability:

   • In Python, tuples are immutable. You cannot change the tuple itself (e.g., reassign or delete elements directly).
   • However, tuples can hold mutable objects like lists. If a tuple contains a list, you can modify the list.

3. Modifying the List:

   • t[1] refers to the list [2, 3] (the second element of the tuple).
   • t[1][0] = 100 changes the first element of the list [2, 3] to 100.
   • After this operation, the list becomes [100, 3].

4. Resulting Tuple:

   • The tuple t remains intact (as a container), but the list inside it has been modified.
   • The final tuple now looks like:

     t = (1, [100, 3], 4)

---

Output:

(1, [100, 3], 4)

---

Key Takeaways:

1. Tuples are immutable, but they can hold mutable objects like lists.
2. You can modify the contents of mutable objects inside a tuple.
3. Direct reassignment like t[1] = [100, 3] would raise an error because it tries to modify the tuple structure.

Read More

Python Coding Challange - Question With Answer (02161224)

 

What will the output of the following code be?

def puzzle():
    a, b, *c, d = (10, 20, 30, 40, 50)
    return a, b, c, d
print(puzzle())

A) (10, 20, [30], 40, 50)
B) (10, 20, [30, 40], 50)
C) (10, 20, [30, 40], 50)
D) (10, 20, [30, 40], 50)

Explanation:

The code involves tuple unpacking with the use of the * operator. Here's the step-by-step breakdown:

1. Unpacking the Tuple:
   The tuple (10, 20, 30, 40, 50) is unpacked using the variables a, b, *c, and d.

   • a gets the first value 10.
   • b gets the second value 20.
   • *c takes all the intermediate values as a list. In this case, *c will be [30, 40].
   • d gets the last value 50.

2. Return Statement:
   The function returns the unpacked values as a tuple: (a, b, c, d). This results in (10, 20, [30, 40], 50).

---

Correct Answer:

B) (10, 20, [30, 40], 50)

---

Key Concepts:

• Tuple Unpacking: The * operator collects multiple values into a list when unpacking.
• Order Matters: The first variable gets the first value, the last variable gets the last value, and * collects everything in between.

Read More

Python Coding challenge - Day 285| What is the output of the following Python Code?

Explanation:

1. Function Definition

def func(a, b, c): 

    print(a, b, c)

A function func is defined with three positional parameters: a, b, and c.

Inside the function, it simply prints the values of a, b, and c.

2. Creating a Tuple

args = (1, 2, 3)

A tuple named args is created with three elements: (1, 2, 3).

3. Calling the Function with Argument Unpacking

func(*args)

The *args syntax is called argument unpacking.

When *args is passed to a function, Python "unpacks" the elements of the tuple (or list) and passes them as separate arguments to the function.

In this case, func(*args) is equivalent to calling func(1, 2, 3).

The function receives:

a = 1

b = 2

c = 3

4. Execution of the Function

Inside the function, print(a, b, c) is executed, which prints the values of a, b, and c.

Output:

1 2 3

 

Read More

Web Scraping with Python

 

Exploring Python Web Scraping with Coursera’s Guided Project

In today’s digital era, data has become a crucial asset. From market trends to consumer preferences, accessing the right data can drive strategic decisions and innovative solutions. Python, with its simplicity and versatility, has emerged as one of the top tools for web scraping — the process of extracting information from websites. If you’re looking to dive into this domain, the Python Web Scraping guided project on Coursera offers an excellent starting point. Here, we’ll explore what this project entails, its benefits, and why it’s a great learning experience.

What is Python Web Scraping?

Web scraping is the technique of automatically extracting data from web pages. Using Python, developers can leverage powerful libraries such as Beautiful Soup, Requests, and Selenium to scrape, parse, and manipulate web content. Web scraping is widely used in applications like:

Gathering product prices from e-commerce sites.

Analyzing competitor data.

Extracting information for research purposes.

Automating tedious manual data collection tasks.

The Coursera project introduces you to these concepts in a structured, beginner-friendly manner.

Overview of the Coursera Guided Project

Coursera’s Python Web Scraping guided project is a hands-on, practical learning experience designed for beginners and intermediate learners. This project spans a few hours and teaches you the basics of web scraping with Python in a step-by-step format. Here are some key highlights:

Interactive Learning Environment

The project is hosted on Coursera’s interactive learning platform, which provides a virtual lab environment. This eliminates the need for complex setups, allowing you to focus on learning rather than installation hurdles.

Comprehensive Curriculum

You’ll explore fundamental tools and techniques, including:

Using the Requests library to fetch web page content.

Parsing HTML with Beautiful Soup.

Navigating and extracting specific elements like tables, images, and text from web pages.

Handling challenges like pagination and dynamic content.

Real-World Applications

The project emphasizes practical use cases, guiding you to scrape data from real websites. For instance, you might work on collecting data from job listing sites, news portals, or e-commerce platforms.

Guided Assistance

Every step of the project is accompanied by detailed explanations, ensuring that you understand the logic behind each line of code. Whether you’re a coding novice or a Python enthusiast, the instructions are clear and intuitive.

Flexible Pace

Coursera allows you to learn at your own pace. Pause, rewind, or revisit sections as needed to solidify your understanding.

Why Choose This Project?

Beginner-Friendly: The project assumes no prior web scraping experience, making it ideal for newcomers.

Practical Skills: By the end of the project, you’ll have a working web scraper and the confidence to build more complex tools.

Affordable Learning: Compared to traditional courses, guided projects are cost-effective, offering high value for a minimal investment.

Industry-Relevant Skills: Web scraping is a valuable skill in industries like data science, marketing, and finance. Learning it can boost your career prospects.

Prerequisites and Tools

Before starting the project, ensure you have a basic understanding of Python programming. Familiarity with concepts like loops, functions, and data structures will be helpful. The guided project uses the following tools:

Python: The primary programming language.

Requests Library: For fetching web page data.

Beautiful Soup: For parsing and navigating HTML.

Jupyter Notebook: For writing and testing your code interactively.

What you'll learn

• Parse complex HTML using Python 
• Apply powerful techniques for managing web scraping effectively 

Key Takeaways

• After completing this project, you’ll gain:
• A solid foundation in Python-based web scraping.
• Experience with essential libraries and their real-world applications.
• Insights into ethical scraping practices and handling website restrictions.
• Ethical Considerations

While web scraping is powerful, it’s essential to use it responsibly. Always respect website terms of service, avoid scraping private or sensitive data, and ensure your scripts do not overload servers. Ethical scraping builds trust and prevents legal complications.

How to Get Started

Visit the project page on Coursera: Python Web Scraping Guided Project.

Sign up and enroll in the project.

Follow the instructions to access the virtual lab environment.

Dive into the hands-on exercises and build your first web scraper.

Join Free: Web Scraping with Python

Conclusion:

The Python Web Scraping guided project on Coursera is an invaluable resource for anyone looking to harness the power of Python for data extraction. With its clear instructions, practical examples, and interactive platform, this project ensures a smooth learning curve. Whether you’re a student, researcher, or professional, mastering web scraping can open doors to countless opportunities. Start your journey today and unlock the potential of data-driven insights!

Read More

Python Coding challenge - Day 10| What is the output of the following Python Code?

 
Code Explanation:

Initialization of my_dict:

my_dict = {"a": 1, "b": 2, "c": 3}

Here, you're creating a dictionary called my_dict with three key-value pairs:

"a" is mapped to 1

"b" is mapped to 2

"c" is mapped to 3

So, initially, the dictionary looks like this:

{"a": 1, "b": 2, "c": 3}

Using the popitem() method:

result = my_dict.popitem()

The popitem() method removes and returns a randomly selected key-value pair from the dictionary.

It also removes that key-value pair from the dictionary.

After calling popitem(), my_dict is modified and loses one of its items.

For example, let's assume the last inserted item is ("c", 3) (which is usually the case in Python 3.7+). So after this call:

result will be the tuple ("c", 3)

The updated dictionary my_dict will look like this:

{"a": 1, "b": 2}

Printing result:

print(result)

This prints the key-value pair that was removed from my_dict by popitem(). In our example, it will 

print:

('c', 3)

Output:

('c', 3)

Read More

Python Coding challenge - Day 9| What is the output of the following Python Code?

 

Step-by-step Explanation:

Initialization of my_dict:

my_dict = {"a": 1, "b": 2, "c": 3}

Here, you're creating a dictionary named my_dict with three key-value pairs:

"a" is mapped to 1

"b" is mapped to 2

"c" is mapped to 3

The dictionary looks like this:

{"a": 1, "b": 2, "c": 3}

Using the clear() method:

my_dict.clear()

The clear() method is used to remove all items from the dictionary.

After calling clear(), my_dict becomes an empty dictionary because it deletes all the key-value pairs.

So after this line, my_dict is now:

{}

Printing my_dict:

print(my_dict)

This prints the current state of my_dict, which is now empty:

Output:

{}

Read More

Python Coding Challange - Question With Answer(01161224)

 

What will the following code output?

a = [1, 2, 3]
b = a[:]
a[1] = 5
print(a, b)

[1, 5, 3] [1, 5, 3]
[1, 2, 3] [1, 2, 3]
[1, 5, 3] [1, 2, 3]
Error

Step-by-Step Explanation:

1. a = [1, 2, 3]
   • A list a is created with elements [1, 2, 3].
2. b = a[:]
   • The slicing operation a[:] creates a shallow copy of the list a and assigns it to b.
   • At this point:
     • a and b are two separate objects in memory.
     • b contains the same elements as a, but any changes made to a will not affect b, and vice versa.
3. a[1] = 5
   • The element at index 1 of list a (which is 2) is replaced with 5.
   • After this modification:
     • a becomes [1, 5, 3].
     • b remains unchanged as [1, 2, 3].
print(a, b)
• The print() function outputs the current values of a and b:
• a is [1, 5, 3].
• b is [1, 2, 3].

Output: [1, 5, 3] [1, 2, 3]

---

Key Concept:

• Slicing ([:]) creates a shallow copy of the list.
  Changes made to the original list a do not affect the copied list b, because they are now stored in different memory locations.

Read More

Python Text Type Quiz

 

Read More

Day 39: Python Program to Convert Gray to binary Code

 

def gray_to_binary(gray_str):

    """

    Function to convert a Gray Code to its equivalent Binary Code.

    :param gray_str: The input Gray Code string.

    :return: The converted Binary Code string.

    """

    binary_code = gray_str[0]

    for i in range(1, len(gray_str)):

        binary_bit = str(int(binary_code[i - 1]) ^ int(gray_str[i]))

        binary_code += binary_bit  

    return binary_code

if __name__ == "__main__":

    gray_input = input("Enter a Gray Code to convert into Binary Code: ")

     if all(bit in '01' for bit in gray_input):

        result = gray_to_binary(gray_input)

        

        print(f"Gray Code: {gray_input}")

        print(f"Corresponding Binary Code: {result}")

    else:

        print("Invalid input. Please enter a valid Gray Code consisting only of 0's and 1's.")

        #source code --> clcoding.com 

Code Explanation:

1. Function: gray_to_binary

Purpose

This function takes a Gray Code string as input and converts it into the corresponding Binary Code.

Parameters

gray_str: A string representing the Gray Code (e.g., "1011").

Logic

First Bit:

In Binary Code, the first bit is always the same as the first bit of the Gray Code:

binary_code = gray_str[0]

Subsequent Bits:

For each subsequent bit, the binary bit is calculated using the XOR operation between:

The last calculated binary bit (binary_code[i - 1]).

The current bit in the Gray Code (gray_str[i]).

Formula:

binary_bit = str(int(binary_code[i - 1]) ^ int(gray_str[i]))

int() converts the binary characters into integers.

^ performs the XOR operation.

str() converts the result back to a string for concatenation.

Concatenate the Binary Bit:

Append the computed binary bit to binary_code:

binary_code += binary_bit

Return Result:

After processing all bits, return the final Binary Code string.

Example Walkthrough:

For gray_str = "1011":

binary_code[0] = gray_str[0] = 1

Iteration 1 (i = 1):

binary_bit = binary_code[0] XOR gray_str[1] = 1 XOR 0 = 1

binary_code = "11"

Iteration 2 (i = 2):

binary_bit = binary_code[1] XOR gray_str[2] = 1 XOR 1 = 0

binary_code = "110"

Iteration 3 (i = 3):

binary_bit = binary_code[2] XOR gray_str[3] = 0 XOR 1 = 1

binary_code = "1101"

Final Binary Code: "1101"

2. Input Handling

The program prompts the user for a Gray Code:

gray_input = input("Enter a Gray Code to convert into Binary Code: ")

Validation

The program ensures the input contains only 0 and 1:

if all(bit in '01' for bit in gray_input):

all(bit in '01' for bit in gray_input):

Checks if every character in gray_input is either '0' or '1'.

If valid:

Calls the gray_to_binary function to compute the Binary Code.

Prints the input Gray Code and the corresponding Binary Code.

If invalid:

Displays an error message:

print("Invalid input. Please enter a valid Gray Code consisting only of 0's and 1's.")

3. Output

Valid Input:

For example:

Enter a Gray Code to convert into Binary Code: 1011

Gray Code: 1011

Corresponding Binary Code: 1101

Invalid Input:

If the user enters invalid characters:

Enter a Gray Code to convert into Binary Code: 12A

Invalid input. Please enter a valid Gray Code consisting only of 0's and 1's.

Read More

Snake Game in Python

CODE:

import pygame

import time

import random

pygame.init()

WIDTH, HEIGHT = 1200, 700

WHITE = (255, 255, 255)

BLACK = (0, 0, 0)

RED = (255, 0, 0)

GREEN = (0, 255, 0)

BLUE = (0, 0, 255)

screen = pygame.display.set_mode((WIDTH, HEIGHT))

pygame.display.set_caption("Snake Game")

clock = pygame.time.Clock()

snake_block = 10

snake_speed = 15

font_style = pygame.font.SysFont("bahnschrift", 25)

score_font = pygame.font.SysFont("comicsansms", 20)

def display_score(score):

    value = score_font.render(f"Your Score: {score}", True, RED)

    screen.blit(value, [10, 10])

def draw_snake(snake_block, snake_list):

    for block in snake_list:

        pygame.draw.rect(screen, GREEN, [block[0], block[1], snake_block, snake_block])

def message(msg, color):

    msg_surface = font_style.render(msg, True, color)

    screen.blit(msg_surface, [WIDTH / 6, HEIGHT / 3])

def game_loop():

    game_over = False

    game_close = False

    x, y = WIDTH // 2, HEIGHT // 2

    x_change, y_change = 0, 0

    snake_list = []

    snake_length = 1

    food_x = round(random.randrange(0, WIDTH - snake_block) / 10.0) * 10.0

    food_y = round(random.randrange(0, HEIGHT - snake_block) / 10.0) * 10.0

    while not game_over:

        while game_close:

            screen.fill(BLACK)

            message("Game Over! Press Q-Quit or C-Play Again", RED)

            display_score(snake_length - 1)

            pygame.display.update()

            for event in pygame.event.get():

                if event.type == pygame.KEYDOWN:

                    if event.key == pygame.K_q:

                        game_over = True

                        game_close = False

                    if event.key == pygame.K_c:

                        game_loop()

        for event in pygame.event.get():

            if event.type == pygame.QUIT:

                game_over = True

            if event.type == pygame.KEYDOWN:

                if event.key == pygame.K_LEFT:

                    x_change, y_change = -snake_block, 0

                elif event.key == pygame.K_RIGHT:

                    x_change, y_change = snake_block, 0

                elif event.key == pygame.K_UP:

                    x_change, y_change = 0, -snake_block

                elif event.key == pygame.K_DOWN:

                    x_change, y_change = 0, snake_block

        if x >= WIDTH or x < 0 or y >= HEIGHT or y < 0:

            game_close = True

        x += x_change

        y += y_change

        screen.fill(BLACK)

        pygame.draw.rect(screen, BLUE, [food_x, food_y, snake_block, snake_block])

        snake_head = [x, y]

        snake_list.append(snake_head)

        if len(snake_list) > snake_length:

            del snake_list[0]

        for block in snake_list[:-1]:

            if block == snake_head:

                game_close = True

        draw_snake(snake_block, snake_list)

        display_score(snake_length - 1)

        pygame.display.update()

        if x == food_x and y == food_y:

            food_x = round(random.randrange(0, WIDTH - snake_block) / 10.0) * 10.0

            food_y = round(random.randrange(0, HEIGHT - snake_block) / 10.0) * 10.0

            snake_length += 1

        clock.tick(snake_speed)

    pygame.quit()

    quit()

game_loop()

#source code --> clcoding.com

Code Explanation:

1. Imports and Initialization

import pygame

import time

import random

pygame.init()

pygame: A library used to create games.

time and random: Standard Python libraries for time delays and random number generation.

pygame.init(): Initializes all imported pygame modules.

2. Screen Setup

WIDTH, HEIGHT = 1200, 700

screen = pygame.display.set_mode((WIDTH, HEIGHT))

pygame.display.set_caption("Snake Game")

Defines the screen dimensions as 1200x700.

Creates the game window using pygame.display.set_mode().

Sets the title of the game window to "Snake Game".

3. Colors

WHITE = (255, 255, 255)

BLACK = (0, 0, 0)

RED = (255, 0, 0)

GREEN = (0, 255, 0)

BLUE = (0, 0, 255)

RGB tuples are used to define colors.

4. Game Variables

snake_block = 10

snake_speed = 15

snake_block: The size of each block of the snake.

snake_speed: Determines the snake's speed (frames per second).

5. Fonts

font_style = pygame.font.SysFont("bahnschrift", 25)

score_font = pygame.font.SysFont("comicsansms", 20)

Two fonts are created for rendering messages and scores.

6. Helper Functions

Displaying Score

def display_score(score):

    value = score_font.render(f"Your Score: {score}", True, RED)

    screen.blit(value, [10, 10])

Displays the player's score in red at the top-left corner.

Drawing the Snake

def draw_snake(snake_block, snake_list):

    for block in snake_list:

        pygame.draw.rect(screen, GREEN, [block[0], block[1], snake_block, snake_block])

Draws the snake as a series of green blocks using the snake_list, which tracks the coordinates of each block.

Displaying Messages

def message(msg, color):

    msg_surface = font_style.render(msg, True, color)

    screen.blit(msg_surface, [WIDTH / 6, HEIGHT / 3])

Displays messages on the screen, such as "Game Over".

7. Main Game Loop

Variables

def game_loop():

    game_over = False

    game_close = False

    x, y = WIDTH // 2, HEIGHT // 2

    x_change, y_change = 0, 0

    snake_list = []

    snake_length = 1

    food_x = round(random.randrange(0, WIDTH - snake_block) / 10.0) * 10.0

    food_y = round(random.randrange(0, HEIGHT - snake_block) / 10.0) * 10.0

game_over and game_close: Flags for the game's state.

x and y: Initial coordinates of the snake's head.

x_change and y_change: Tracks the snake's movement direction.

snake_list and snake_length: Represents the snake and its current length.

food_x and food_y: Randomly generated coordinates for the food.

Game Over Logic

while game_close:

    screen.fill(BLACK)

    message("Game Over! Press Q-Quit or C-Play Again", RED)

    display_score(snake_length - 1)

    pygame.display.update()

Displays a "Game Over" screen, along with options to quit (Q) or restart (C).

Event Handling

for event in pygame.event.get():

    if event.type == pygame.QUIT:

        game_over = True

    if event.type == pygame.KEYDOWN:

        if event.key == pygame.K_LEFT:

            x_change, y_change = -snake_block, 0

        elif event.key == pygame.K_RIGHT:

            x_change, y_change = snake_block, 0

        elif event.key == pygame.K_UP:

            x_change, y_change = 0, -snake_block

        elif event.key == pygame.K_DOWN:

            x_change, y_change = 0, snake_block

Handles quitting the game and arrow key input to change the snake's direction.

Boundary Collision

if x >= WIDTH or x < 0 or y >= HEIGHT or y < 0:

    game_close = True

Checks if the snake has hit the boundaries of the screen.

Snake Movement

x += x_change

y += y_change

Updates the snake's position.

Snake Growth and Collision Detection

snake_head = [x, y]

snake_list.append(snake_head)

if len(snake_list) > snake_length:

    del snake_list[0]

for block in snake_list[:-1]:

    if block == snake_head:

        game_close = True

Adds the new position of the snake's head to the snake_list.

Removes the last block if the snake hasn’t eaten food.

Checks if the snake collides with itself.

Food Collision

if x == food_x and y == food_y:

    food_x = round(random.randrange(0, WIDTH - snake_block) / 10.0) * 10.0

    food_y = round(random.randrange(0, HEIGHT - snake_block) / 10.0) * 10.0

    snake_length += 1

If the snake's head overlaps with the food, it generates new food and increases the snake's length.

8. Rendering

screen.fill(BLACK)

pygame.draw.rect(screen, BLUE, [food_x, food_y, snake_block, snake_block])

draw_snake(snake_block, snake_list)

display_score(snake_length - 1)

pygame.display.update()

Clears the screen, redraws the food and snake, updates the score, and refreshes the display.

9. Frame Rate

clock.tick(snake_speed)

Controls the frame rate based on snake_speed.

10. Quit

pygame.quit()

quit()

Exits the game when the loop ends.

Read More

Python Numeric Types Quiz

 

Read More

The Fundamentals of RDMA Programming

The Fundamentals of RDMA Programming

The "Fundamentals of RDMA Programming" course offered by NVIDIA on Coursera focuses on teaching Remote Direct Memory Access (RDMA), a crucial technology for high-speed server-to-server communication. RDMA enables direct memory access between systems without involving the CPU, making it ideal for applications requiring high throughput and low latency, such as HPC (high-performance computing) and data centers.

The course covers RDMA basics, core components, operations, code examples, and connection management. Learners will gain skills in writing RDMA applications over InfiniBand and Ethernet, understanding data-path flows, and managing memory efficiently. By the end, participants will be proficient in developing RDMA-based applications.

The Fundamentals of RDMA Programming course on Coursera provides comprehensive training in Remote Direct Memory Access (RDMA), a technology that allows servers to access each other's memory directly, bypassing the CPU. 

RDMA Basics: Understanding the core concepts, such as memory regions, queues, and buffers.

InfiniBand and Ethernet: Learning how RDMA operates over different networking fabrics.

Programming with RDMA: Hands-on exercises on building RDMA-based applications.

Data Path Flows: Understanding how data is transferred with minimal CPU involvement.

The Fundamentals of RDMA Programming course on Coursera offers the following key highlights:

Key Highlights of the course:

Introduction to RDMA: Learn the core concepts of Remote Direct Memory Access, including its benefits for high-performance applications.

Networking Protocols: Understand RDMA protocols such as InfiniBand and RoCE (RDMA over Ethernet).

Memory Management: Master memory region registration, allocation, and how they affect performance.

Efficient Data Communication: Explore how RDMA enables direct memory access between systems, bypassing the CPU for faster data transfer.

Hands-on Exercises: Gain practical experience writing RDMA-based applications, managing connections, and optimizing network performance.

This course is designed to equip learners with the skills to develop efficient, low-latency applications in high-performance computing environments.

What you'll learn

• RDMA Basics: Bypassing the OS, Memory zero copy and transport offload
• Core RDMA:  RDMA verbs and objects, data-path flow and memory management
• RDMA Operations:  Send and receive operations, RDMA write and RDMA read operations, atomic operations
• Become familiar with InfiniBand architecture layer, RDMA basic flow, create a completion queue (CQ) and a queue pair (QP), and execute RDMA operation
•  Establish connection using RDMA_CM API

Future enhancements in RDMA programming may include:

Support for New Protocols: Expanding support for upcoming RDMA protocols like PCIe-based RDMA and advanced Ethernet technologies.

Integration with AI/ML Workloads: Optimizing RDMA for AI and machine learning environments, which require low latency and high-throughput communication.

Scalability Improvements: Increasing the scalability of RDMA in large-scale distributed systems.

Security Enhancements: Implementing better security features, like encryption, in RDMA communication to prevent data breaches in critical environments.

These developments could expand RDMA’s applications, making it even more powerful for modern high-performance computing systems.

Join Free:

Conclusion:

The Fundamentals of RDMA Programming course provides essential knowledge and hands-on experience in building efficient, high-performance applications using RDMA. Through understanding RDMA protocols, memory management, and network communication, learners gain the skills to optimize data transfer processes. The course also equips professionals to work with technologies like InfiniBand and RoCE, making it a valuable resource for those seeking to enhance their expertise in high-performance computing and networking. As technology evolves, RDMA's role in low-latency, high-throughput systems will continue to grow.

Read More

Python Coding challenge - Day 296| What is the output of the following Python Code?

Code Explanation:

Function Definition (factorial(n)):

The function factorial(n) is designed to calculate the factorial of a number n. The factorial of a number is the product of all positive integers less than or equal to that number. For example, 5! = 5 * 4 * 3 * 2 * 1 = 120.

Base Case (if n == 1:):

The line if n == 1: checks whether the number n is equal to 1.

If n is 1, the function returns 1. This is because the factorial of 1 is defined as 1. This is called the base case in recursion, which prevents the recursion from continuing indefinitely.

Recursive Case (return n * factorial(n-1)):

If n is not 1, the function proceeds to the line return n * factorial(n-1).

This is the recursive step, where the function calls itself with the value n-1 and multiplies the result by n.

The idea is that the factorial of n can be calculated as n * factorial(n-1). For example, to calculate 5!, the function will first calculate 4!, then multiply it by 5, and so on until it reaches the base case (factorial(1)).

First Call (factorial(5)):

When factorial(5) is called, n is 5, which is not equal to 1, so it proceeds to the recursive case and calls factorial(4).

The call stack becomes:

factorial(5) -> 5 * factorial(4)

factorial(4) -> 4 * factorial(3)

factorial(3) -> 3 * factorial(2)

factorial(2) -> 2 * factorial(1)

factorial(1) -> 1

Unwinding the Recursion:

Once factorial(1) returns 1, the recursion "unwinds" and each function call returns its result:

factorial(2) returns 2 * 1 = 2

factorial(3) returns 3 * 2 = 6

factorial(4) returns 4 * 6 = 24

factorial(5) returns 5 * 24 = 120

Final Output:

The final result of factorial(5) is 120, which is printed by the print(factorial(5)) statement.

Visualizing the Process:

factorial(5) calls factorial(4)

factorial(4) calls factorial(3)

factorial(3) calls factorial(2)

factorial(2) calls factorial(1)

factorial(1) returns 1

factorial(2) returns 2 * 1 = 2

factorial(3) returns 3 * 2 = 6

factorial(4) returns 4 * 6 = 24

factorial(5) returns 5 * 24 = 120

Thus, the output is 120.

Read More

AI Infrastructure and Operations Fundamentals

 

AI Infrastructure and Operations Fundamentals

The "AI Infrastructure and Operations Fundamentals" course by NVIDIA on Coursera is designed for IT professionals and those new to AI. It covers AI technologies, machine learning, deep learning, and the essential role of GPUs in AI workloads. The course provides insights into deploying AI infrastructure across various environments such as on-premises, cloud, and hybrid setups. With modules on AI operations and infrastructure management, it equips learners with the tools to support and manage AI workflows effectively. Completing this course also prepares you for the NVIDIA Certified Associate certification.

The AI Infrastructure and Operations Fundamentals course by NVIDIA on Coursera is a comprehensive learning experience aimed at IT professionals, engineers, and anyone looking to understand the foundational aspects of AI infrastructure. This course dives deep into how AI workloads are managed, optimized, and deployed across different environments, including on-premises, cloud, and hybrid setups.

Key highlights include:

Understanding AI infrastructure: Learn how GPUs power AI applications, and explore the deployment of AI systems.

Machine Learning and Deep Learning: Discover the crucial roles these technologies play in AI.

Practical skills: Learn best practices for infrastructure management and how to build efficient AI pipelines.

Certification: Completing this course can lead to the NVIDIA Certified Associate certification, enhancing your professional credibility in the AI space.

Ideal for those starting in AI or those working in operations and looking to expand their skill set, the course is designed to equip learners with the skills necessary to support AI workflows, optimize performance, and ensure smooth operations across AI infrastructures. Whether you're a beginner or already have some experience with AI, this course offers valuable insights into managing AI infrastructure efficiently.

What you'll learn

• Explore diverse applications of AI across various industries.
• Understand concepts like Machine Learning, Deep Leaning, training and inference.
• Trace the evolution of AI Technologies. From its inception to the revolutionary advances brought by Generative AI, and the role of GPUs.
• You will become familiar with deep learning frameworks and AI software stack.
• Learn about considerations when deploying AI workloads on a data center on prem, in the cloud, on a hybrid model, or on a multi-cloud environment.

The AI Infrastructure and Operations Fundamentals course by NVIDIA on Coursera is a valuable resource for those seeking to understand AI infrastructure management. It covers:

GPU-Powered AI: Learn about GPUs and their significance in accelerating AI and ML workloads.

Deployment Environments: Explore on-premise, cloud, and hybrid deployment strategies for AI systems.

AI Workflow Optimization: Gain practical skills in managing and optimizing AI pipelines for improved performance.

Scalability: Learn how to scale AI systems and ensure long-term efficiency.

Join Free:

Conclusion:

 This course is ideal for anyone looking to build or manage AI systems, with the added benefit of preparing learners for the NVIDIA Certified Associate certification, making it a great step forward in a tech career. The AI Infrastructure and Operations Fundamentals course by NVIDIA provides learners with essential skills to manage and deploy AI systems across various environments. By focusing on GPUs, AI workflows, and infrastructure optimization, it prepares professionals for AI infrastructure management and supports certification for the NVIDIA Certified Associate role. This course is perfect for those wanting to gain practical insights into AI operations and scale AI systems effectively, making it a strong foundation for a career in AI infrastructure

Read More

Python Coding challenge - Day 8| What is the output of the following Python Code?

 

Code Explanation:

my_list = [1, 2, 3, 4, 5]

This line creates a list called my_list with the values [1, 2, 3, 4, 5].

result = my_list[1:4:2]

This line uses list slicing with a start, stop, and step.

Start index (1): This tells Python where to start slicing. It starts from index 1, which is the second element in the list (2).

Stop index (4): This tells Python where to stop slicing. It stops just before index 4. So, it will slice up to index 3 (which is the value 4), but does not include index 4 (the element 5).

Step size (2): This tells Python to take every second element between the start and stop indices. In this case, starting at index 1, it will skip every other element. So, it will take:

The element at index 1 (which is 2),

Then skip index 2 (which is 3), and

Take the element at index 3 (which is 4).

Therefore, the sliced list will contain [2, 4].

print(result)

This line prints the resulting sublist, which is [2, 4].

Summary:

You started with the list [1, 2, 3, 4, 5].

Using slicing with a start index of 1, stop index of 4, and a step size of 2, you selected every second element between index 1 and index 3 (inclusive).

The result is the list [2, 4].

Output:

[2, 4]

Read More

Python Coding challenge - Day 7| What is the output of the following Python Code?

 

Code Explanation:

my_list = [1, 2, 3, 4, 5]

This line creates a list called my_list, which contains the numbers [1, 2, 3, 4, 5].

In Python, a list is an ordered collection of items, and each item in the list has an index that represents its position.

result = my_list[-3:-1]

This line uses list slicing to create a sublist from my_list.

Negative indices are used here:

-3: Refers to the third element from the end of the list. Since the list is [1, 2, 3, 4, 5], the third-to-last element is 3.

-1: Refers to the last element of the list. So, my_list[-1] is 5, but in slicing, the stop index (-1 here) is excluded. That means the slice will stop right before 5.

The slice starts at the element at index -3 (which is 3), and it goes up to but does not include the element at index -1 (which is 5). So, it includes the elements at indices -3 (3) and -2 (4), which results in the sublist [3, 4].

print(result)

This line prints the sublist result, which contains [3, 4].

Summary:

You started with the list [1, 2, 3, 4, 5].

Using negative indices, you sliced the list starting from the third-to-last element (3) and stopping just before the last element (5), giving you [3, 4].

The output is:

[3, 4]

Read More

Day 40: Python Program to Convert Celsius to Fahrenheit

def celsius_to_fahrenheit(celsius):

    fahrenheit = (celsius * 9/5) + 32

    return fahrenheit

celsius = float(input("Enter temperature in Celsius: "))

fahrenheit = celsius_to_fahrenheit(celsius)

print(f"{celsius}°C is equal to {fahrenheit}°F")

 #source code --> clcoding.com 

Code Explanation:

1. Function: celsius_to_fahrenheit

def celsius_to_fahrenheit(celsius):

    fahrenheit = (celsius * 9/5) + 32

    return fahrenheit

Purpose:

Converts a given temperature in Celsius to Fahrenheit.

Parameter:

celsius: A float or integer representing the temperature in Celsius.

Formula:

The conversion formula from Celsius to Fahrenheit is:

F=(C×9/5​)+32

Where:

𝐹

F is the temperature in Fahrenheit.

𝐶

C is the temperature in Celsius.

Steps:

Multiply the Celsius temperature by 9/5.

Add 32 to the result.

Return the calculated Fahrenheit temperature.

2. User Input

celsius = float(input("Enter temperature in Celsius: "))

input():

Prompts the user to enter a temperature value in Celsius.

float():

Converts the input string to a floating-point number, allowing decimal values.

celsius:

Stores the user-provided temperature.

3. Function Call

fahrenheit = celsius_to_fahrenheit(celsius)

The program calls the celsius_to_fahrenheit function, passing the celsius value entered by the user as an argument.

The function returns the equivalent temperature in Fahrenheit, which is stored in the variable fahrenheit.

4. Output

print(f"{celsius}°C is equal to {fahrenheit}°F")

Formatted String (f-string):

Embeds the values of celsius and fahrenheit into the output string.

Displays the conversion result in a user-friendly format.

 

Read More

Day 38: Python Program to Print Inverted Star Pattern

 

rows = int(input("Enter the number of rows: "))

for i in range(rows, 0, -1):

    print("*" * i)

#source code --> clcoding.com

Code Explanation:

1. Input: Number of Rows

rows = int(input("Enter the number of rows: "))

input(): Prompts the user to enter a value.

int(): Converts the input (string) into an integer.

rows: Represents the total number of rows in the reverse triangle.

Example:

If the user inputs 5, then:

rows = 5

2. Reverse Triangle Logic

for i in range(rows, 0, -1):

range(rows, 0, -1):

Starts at rows (e.g., 5).

Stops at 0 (not inclusive).

Decrements by -1 in each iteration, creating a countdown.

i: Represents the current row number. The value of i starts from rows and decreases to 1.

Example:

For rows = 5, the range(rows, 0, -1) produces:

5, 4, 3, 2, 1

3. Print Asterisk Pattern

print("*" * i)

"*" * i:

Repeats the asterisk (*) i times for the current row.

For example, if i = 5, "*" is repeated 5 times (*****).

print():

Outputs the repeated asterisks on a new line, creating one row of the triangle.

Read More

Day 37: Python Program to Find Area of Triangle

 

base = float(input("Enter the base of the triangle: "))

height = float(input("Enter the height of the triangle: "))

area = 0.5 * base * height

print(f"The area of the triangle is: {area:.2f}")

#source code --> clcoding.com 

Code Explanation:

1. Inputs

The program prompts the user to enter the base and height of the triangle:

base = float(input("Enter the base of the triangle: "))

height = float(input("Enter the height of the triangle: "))

input(): Captures user input as a string.

float(): Converts the input string to a floating-point number, allowing for decimal values.

Example:

User enters 5 for the base and 10 for the height.

Both are converted to 5.0 and 10.0 (float type) for mathematical operations.

2. Area Calculation

The area of the triangle is calculated using the formula:

area = 0.5 * base * height

base and height: The values entered by the user.

The multiplication produces the area.

3. Output

The program prints the area with two decimal places:

print(f"The area of the triangle is: {area:.2f}")

f-strings: Format strings used to embed variables directly into the output.

{area:.2f}:

.2f: Formats the number to two decimal places.

Example Output:

For a triangle with a base of 5 and height of 10, the output will be:

The area of the triangle is: 25.00

Read More

Day 36 : Python Program to Convert Binary to Gray Code

def binary_to_gray(binary_str):

    """

    Function to convert a binary number to its corresponding Gray Code.

    :param binary_str: The input binary string.

    :return: The converted Gray Code string.

    """

    gray_code = binary_str[0]  

    for i in range(1, len(binary_str)):

        gray_bit = str(int(binary_str[i - 1]) ^ int(binary_str[i]))

        gray_code += gray_bit  

    return gray_code

binary_input = input("Enter a binary number to convert into Gray Code: ")

if all(bit in '01' for bit in binary_input):  

     result = binary_to_gray(binary_input)

    print(f"Binary number: {binary_input}")

    print(f"Corresponding Gray Code: {result}")

else:

    print("Invalid input. Please enter a valid binary number consisting only of 0's and 1's.")

#source code --> clcoding.com 

Code Explanation:

1. What is Gray Code?

Gray Code is a binary numeral system where two successive values differ by only one bit. It is often used in digital logic to minimize errors when transitioning between states.

2. Function: binary_to_gray

This function takes a binary string as input and converts it into Gray Code using the following steps:

Parameters:

binary_str: The input binary number as a string.

Process:

The first bit of the Gray Code is always the same as the first bit of the binary number:

gray_code = binary_str[0]

For each subsequent bit, compute the XOR of the previous bit (binary_str[i-1]) and the current bit 

(binary_str[i]):

gray_bit = str(int(binary_str[i - 1]) ^ int(binary_str[i]))

int(binary_str[i - 1]) and int(binary_str[i]): Convert the binary characters to integers for the XOR operation.

^: The XOR operator in Python.

str(): Converts the resulting integer back to a string for concatenation.

Append this new bit (gray_bit) to the Gray Code:

gray_code += gray_bit

Continue until all bits are processed.

Return:

The function returns the Gray Code string.

3. Input Handling

The program asks the user to enter a binary number:

binary_input = input("Enter a binary number to convert into Gray Code: ")

Validation:

It ensures the input consists only of 0 and 1:

if all(bit in '01' for bit in binary_input):

all(bit in '01' for bit in binary_input): Checks if every character in binary_input is either '0' or '1'.

If valid:

Calls the binary_to_gray function to compute the Gray Code.

Prints both the original binary number and the computed Gray Code.

If invalid:

Prints an error message.

4. Output

When the input is valid:

Displays the binary number and its Gray Code:

Binary number: <binary_input>

Corresponding Gray Code: <result>

If the input is invalid:

Outputs:

Invalid input. Please enter a valid binary number consisting only of 0's and 1's.

 

Read More

Day 35 : Python Program to Print Binary Equivalent of an Integer using Recursion

def binary_equivalent(number):

    if number == 0:

        return ""

    return binary_equivalent(number // 2) + str(number % 2)

number = int(input("Enter an integer: "))

if number == 0:

    print("The binary equivalent of 0 is 0.")

elif number > 0:

    print(f"The binary equivalent of {number} is {binary_equivalent(number)}.")

else:

    print(f"The binary equivalent of {number} is -{binary_equivalent(abs(number))}.")

#source code --> clcoding.com

Code Explanation:

1. Recursive Function: binary_equivalent(number)

This function computes the binary representation of a number using recursion.

def binary_equivalent(number):

    if number == 0:

        return ""

    return binary_equivalent(number // 2) + str(number % 2)

Base Case:

if number == 0:

    return ""

If the input number is 0, the function returns an empty string (""). This is the stopping condition for recursion. The binary representation is built as the recursion unwinds.

Recursive Case:

return binary_equivalent(number // 2) + str(number % 2)

For numbers greater than 0:

Integer Division (number // 2): Divides the number by 2, reducing it in each recursive call.

Modulo (number % 2): Finds the remainder when divided by 2, which represents the current binary digit (0 or 1).

The result is the binary representation of number // 2 concatenated with the binary digit of the current step.

2. Taking Input

number = int(input("Enter an integer: "))

Prompts the user to enter an integer.

Converts the input string into an integer using int().

3. Handling Special Cases

if number == 0:

    print("The binary equivalent of 0 is 0.")

4. Positive Numbers

elif number > 0:

    print(f"The binary equivalent of {number} is {binary_equivalent(number)}.")

If the input is positive, the program calls binary_equivalent(number) and prints the result.

5. Negative Numbers

else:

    print(f"The binary equivalent of {number} is -{binary_equivalent(abs(number))}.")

If the input is negative:

The absolute value (abs(number)) is passed to the binary_equivalent function to compute the binary representation of the positive counterpart.

The program prepends a negative sign (-) to indicate the negative value.

 

Read More

Day 34 : Python Program to Find the Factorial of a Number Without Recursion

 

num = int(input("Enter a number to find its factorial: "))

factorial = 1

for i in range(1, num + 1):

    factorial *= i  

print(f"The factorial of {num} is: {factorial}")

 #source code --> clcoding.com

Code Explanation:

1. Taking Input from the User

num = int(input("Enter a number to find its factorial: "))

input(): Prompts the user to enter a number as a string.

int(): Converts the input string into an integer so it can be used in calculations.

The integer is stored in the variable num.

2. Initializing the Factorial Variable

factorial = 1

The factorial variable is initialized to 1 because multiplying by 1 does not affect the result.

This variable will be used to store the cumulative product of numbers from 1 to num.

3. Calculating the Factorial Using a Loop

for i in range(1, num + 1):

    factorial *= i

range(1, num + 1): Generates a sequence of numbers from 1 to num (inclusive).

For example, if num = 5, the range will generate: [1, 2, 3, 4, 5].

Iterative Multiplication:

The loop runs once for each number in the range.

In each iteration, the value of factorial is updated by multiplying it with the current value of i.

4. Printing the Result

print(f"The factorial of {num} is: {factorial}")

The calculated factorial is displayed using an f-string, which allows embedding variables directly within the string.

Read More

Day 33 : Python Program to Find the Factorial of a Number using Recursion

 

def factorial(n):

    if n == 0 or n == 1:

        return 1

    else:

    return n * factorial(n - 1)

num = int(input("Enter a number: "))

if num < 0:

    print("Factorial is not defined for negative numbers.")

else:

    print(f"The factorial of {num} is {factorial(num)}.")

#source code --> clcoding.com 

Code Explanation:

1. Function Definition: factorial(n)

This function computes the factorial of a given number 

𝑛

n using recursion.

def factorial(n):

    if n == 0 or n == 1:

        return 1

    else:

        return n * factorial(n - 1)

Base Case:

if n == 0 or n == 1:

    return 1

If 

𝑛

n is 0 or 1, the factorial is defined as 1. This serves as the stopping condition for the recursion.

Recursive Case:

return n * factorial(n - 1)

n by the result. This continues until the base case is reached.

How Recursion Works: 

factorial(5) = 5 * factorial(4)

factorial(4) = 4 * factorial(3)

factorial(3) = 3 * factorial(2)

factorial(2) = 2 * factorial(1)

factorial(1) = 1  (Base Case)

Substituting back:

factorial(5) = 5 * 4 * 3 * 2 * 1 = 120

Taking Input from the User

num = int(input("Enter a number: "))

Prompts the user to enter a number.

Converts the user input (a string) into an integer using int().

Handling Negative Input

if num < 0:

    print("Factorial is not defined for negative numbers.")

Factorial is defined only for non-negative integers.

If the input number is negative, the program prints an error message and does not proceed further.

Computing and Printing the Factorial

else:

    print(f"The factorial of {num} is {factorial(num)}.")

If the input is valid (a non-negative number):

The program calls the factorial function with the input num.

The result is printed in a formatted string: f"The factorial of {num} is {factorial(num)}.".

Read More

Day 32 : Python Program to Find Fibonacci Numbers using Recursion

 

def fibonacci_series(n):

    a, b = 0, 1

    series = []

    for _ in range(n):

        series.append(a)

        a, b = b, a + b

        return series

num_terms = int(input("Enter the number of terms: "))

if num_terms <= 0:

    print("Please enter a positive integer.")

else:

    print("Fibonacci series:")

    print(fibonacci_series(num_terms))

#source code --> clcoding.com 

Code Explanation:

1. Function Definition: fibonacci_series(n)

The function takes a single parameter, n, which represents the number of terms in the Fibonacci sequence to generate.

Inside the function:

a, b = 0, 1: Initializes the first two numbers of the Fibonacci sequence, where a starts at 0 and b at 1.

series = []: Creates an empty list to store the Fibonacci sequence.

2. Generating Fibonacci Terms

for _ in range(n)::

Iterates n times to generate the sequence.

The loop variable _ is used when the variable itself is not needed.

series.append(a):

Adds the current value of a (the current Fibonacci number) to the series list.

a, b = b, a + b:

Updates a to the value of b (the next Fibonacci number).

Updates b to the sum of a and b (the next-next Fibonacci number).

This update effectively shifts the series forward.

3. Returning the Result

After the loop ends, the complete Fibonacci sequence is stored in series.

The function returns the series list.

Main Program

4. Input from User

num_terms = int(input("Enter the number of terms: ")):

Prompts the user to input the number of terms they want in the Fibonacci sequence.

Converts the input to an integer and stores it in num_terms.

5. Input Validation

if num_terms <= 0::

Checks if the input is less than or equal to 0 (invalid input).

If invalid, prints a message: "Please enter a positive integer.".

else::

If the input is valid (a positive integer), proceeds to generate the Fibonacci sequence.

6. Generating and Printing the Sequence

print("Fibonacci series:"):

Outputs a message indicating that the Fibonacci sequence will follow.

print(fibonacci_series(num_terms)):

Calls the fibonacci_series function with the user-specified number of terms and prints the returned list.

Read More

Python Numpy Quiz

 

Read More

Python Coding challenge - Day 290| What is the output of the following Python Code?

 

Explanation:

Function Definition with a Default Argument:

def func(x=[]):

The function func is defined with a default parameter x, which is initialized to an empty list [] if no argument is passed during the function call.

Important behavior: Default arguments are evaluated once when the function is defined, not each time the function is called. This means if you use a mutable default argument (like a list), it will persist across multiple function calls.

Appending to the List:

x.append(1)

Inside the function, the code x.append(1) adds the value 1 to the list x.

Since x is initialized to an empty list [], 1 will be appended to it on the first call.

Return the List:

return x

After appending 1, the list x is returned.

First Function Call:

print(func())

When func() is called the first time, the default list x is an empty list [].

1 is appended to this list, making it [1], and this list is returned and printed.

Second Function Call:

print(func())

When func() is called the second time, the same list is used (because of the default argument behavior).

The list from the previous call already contains [1].

1 is appended again, so the list becomes [1, 1], and this list is returned and printed.

Final Output:

[1]

[1, 1]

Read More