#Python programming for YouTube API

[trendingnow3-blog]

YouTube Most Watched Videos Finder: Python Code

YouTube Most Watched Videos Finder: Python Code

Description: This article contains a Python script that utilizes the YouTube Data API to find the most watched videos in the past 24 hours for a specific region. The script fetches data from the YouTube API, extracts relevant information such as video title, view count, like count, and creates a list of the most popular videos in the desired region. How it Works: The script is written in…

[pixiedust111]

It's been a real fun! I'm hoping to work on the front end next and make it available for everyone 😁!

[nadirelzouki]

Malware-Analysis-sites

[jbfly46]

Your All-in-One AI Web Agent: Save $200+ a Month, Unleash Limitless Possibilities!

Imagine having an AI agent that costs you nothing monthly, runs directly on your computer, and is unrestricted in its capabilities. OpenAI Operator charges up to $200/month for limited API calls and restricts access to many tasks like visiting thousands of websites. With DeepSeek-R1 and Browser-Use, you:

• Save money while keeping everything local and private.

• Automate visiting 100,000+ websites, gathering data, filling forms, and navigating like a human.

• Gain total freedom to explore, scrape, and interact with the web like never before.

You may have heard about Operator from Open AI that runs on their computer in some cloud with you passing on private information to their AI to so anything useful. AND you pay for the gift . It is not paranoid to not want you passwords and logins and personal details to be shared. OpenAI of course charges a substantial amount of money for something that will limit exactly what sites you can visit, like YouTube for example. With this method you will start telling an AI exactly what you want it to do, in plain language, and watching it navigate the web, gather information, and make decisions—all without writing a single line of code.

In this guide, we’ll show you how to build an AI agent that performs tasks like scraping news, analyzing social media mentions, and making predictions using DeepSeek-R1 and Browser-Use, but instead of writing a Python script, you’ll interact with the AI directly using prompts.

These instructions are in constant revisions as DeepSeek R1 is days old. Browser Use has been a standard for quite a while. This method can be for people who are new to AI and programming. It may seem technical at first, but by the end of this guide, you’ll feel confident using your AI agent to perform a variety of tasks, all by talking to it. how, if you look at these instructions and it seems to overwhelming, wait, we will have a single download app soon. It is in testing now.

This is version 3.0 of these instructions January 26th, 2025.

This guide will walk you through setting up DeepSeek-R1 8B (4-bit) and Browser-Use Web UI, ensuring even the most novice users succeed.

What You’ll Achieve

By following this guide, you’ll:

1. Set up DeepSeek-R1, a reasoning AI that works privately on your computer.

2. Configure Browser-Use Web UI, a tool to automate web scraping, form-filling, and real-time interaction.

3. Create an AI agent capable of finding stock news, gathering Reddit mentions, and predicting stock trends—all while operating without cloud restrictions.

A Deep Dive At ReadMultiplex.com Soon

We will have a deep dive into how you can use this platform for very advanced AI use cases that few have thought of let alone seen before. Join us at ReadMultiplex.com and become a member that not only sees the future earlier but also with particle and pragmatic ways to profit from the future.

System Requirements

Hardware

• RAM: 8 GB minimum (16 GB recommended).

• Processor: Quad-core (Intel i5/AMD Ryzen 5 or higher).

• Storage: 5 GB free space.

• Graphics: GPU optional for faster processing.

Software

• Operating System: macOS, Windows 10+, or Linux.

• Python: Version 3.8 or higher.

• Git: Installed.

Step 1: Get Your Tools Ready

We’ll need Python, Git, and a terminal/command prompt to proceed. Follow these instructions carefully.

Install Python

1. Check Python Installation:

• Open your terminal/command prompt and type:

python3 --version

• If Python is installed, you’ll see a version like:

Python 3.9.7

2. If Python Is Not Installed:

• Download Python from python.org.

• During installation, ensure you check “Add Python to PATH” on Windows.

3. Verify Installation:

python3 --version

Install Git

1. Check Git Installation:

• Run:

git --version

• If installed, you’ll see:

git version 2.34.1

2. If Git Is Not Installed:

• Windows: Download Git from git-scm.com and follow the instructions.

• Mac/Linux: Install via terminal:

sudo apt install git -y # For Ubuntu/Debian

brew install git # For macOS

Step 2: Download and Build llama.cpp

We’ll use llama.cpp to run the DeepSeek-R1 model locally.

1. Open your terminal/command prompt.

2. Navigate to a clear location for your project files:

mkdir ~/AI_Project

cd ~/AI_Project

3. Clone the llama.cpp repository:

git clone https://github.com/ggerganov/llama.cpp.git

cd llama.cpp

4. Build the project:

• Mac/Linux:

make

• Windows:

• Install a C++ compiler (e.g., MSVC or MinGW).

• Run:

mkdir build

cd build

cmake ..

cmake --build . --config Release

Step 3: Download DeepSeek-R1 8B 4-bit Model

1. Visit the DeepSeek-R1 8B Model Page on Hugging Face.

2. Download the 4-bit quantized model file:

• Example: DeepSeek-R1-Distill-Qwen-8B-Q4_K_M.gguf.

3. Move the model to your llama.cpp folder:

mv ~/Downloads/DeepSeek-R1-Distill-Qwen-8B-Q4_K_M.gguf ~/AI_Project/llama.cpp

Step 4: Start DeepSeek-R1

1. Navigate to your llama.cpp folder:

cd ~/AI_Project/llama.cpp

2. Run the model with a sample prompt:

./main -m DeepSeek-R1-Distill-Qwen-8B-Q4_K_M.gguf -p "What is the capital of France?"

3. Expected Output:

The capital of France is Paris.

Step 5: Set Up Browser-Use Web UI

1. Go back to your project folder:

cd ~/AI_Project

2. Clone the Browser-Use repository:

git clone https://github.com/browser-use/browser-use.git

cd browser-use

3. Create a virtual environment:

python3 -m venv env

4. Activate the virtual environment:

• Mac/Linux:

source env/bin/activate

• Windows:

env\Scripts\activate

5. Install dependencies:

pip install -r requirements.txt

6. Start the Web UI:

python examples/gradio_demo.py

7. Open the local URL in your browser:

http://127.0.0.1:7860

Step 6: Configure the Web UI for DeepSeek-R1

1. Go to the Settings panel in the Web UI.

2. Specify the DeepSeek model path:

~/AI_Project/llama.cpp/DeepSeek-R1-Distill-Qwen-8B-Q4_K_M.gguf

3. Adjust Timeout Settings:

• Increase the timeout to 120 seconds for larger models.

4. Enable Memory-Saving Mode if your system has less than 16 GB of RAM.

Step 7: Run an Example Task

Let’s create an agent that:

1. Searches for Tesla stock news.

2. Gathers Reddit mentions.

3. Predicts the stock trend.

Example Prompt:

Search for "Tesla stock news" on Google News and summarize the top 3 headlines. Then, check Reddit for the latest mentions of "Tesla stock" and predict whether the stock will rise based on the news and discussions.

--

Congratulations! You’ve built a powerful, private AI agent capable of automating the web and reasoning in real time. Unlike costly, restricted tools like OpenAI Operator, you’ve spent nothing beyond your time. Unleash your AI agent on tasks that were once impossible and imagine the possibilities for personal projects, research, and business. You’re not limited anymore. You own the web—your AI agent just unlocked it! 🚀

Stay tuned fora FREE simple to use single app that will do this all and more.

[eduvantec]

How to Learn Python from Scratch in 2025: A Beginner’s Guide

Python continues to be one of the most in-demand and beginner-friendly programming languages in 2025. Whether you're a student, aspiring developer, or working professional looking to upskill, learning Python from scratch is easier than ever — if you follow the right roadmap.

🎯 Step 1: Understand Why You’re Learning Python

Are you aiming for data science, web development, automation, or AI? Knowing your goal helps you stay focused and choose the right path. Python is versatile, so you can start simple and expand into your area of interest.

📚 Step 2: Start with the Basics

Begin with core Python concepts like:

Variables and Data Types

Loops and Conditionals

Functions and Modules

Lists, Tuples, and Dictionaries Use beginner platforms like W3Schools, Codecademy, or free YouTube tutorials. Practice as you go — don’t just read or watch.

💻 Step 3: Install Python and Use an IDE

Download the latest Python version from python.org. Use beginner-friendly IDEs like Thonny or VS Code. Try writing small scripts like a calculator, number guesser, or basic chatbot.

🧠 Step 4: Practice Every Day

Use platforms like HackerRank, LeetCode, or Replit to practice coding daily. Aim for 30–60 minutes of hands-on coding. Solving problems builds logic and confidence.

📊 Step 5: Learn by Building Projects

Apply what you learn by creating small projects like:

To-do app

Weather app using APIs

Simple games with Pygame Building helps reinforce concepts and improves your portfolio.

👨‍🏫 Step 6: Get Expert Help When Stuck

If you're struggling with assignments or need personalized guidance, reach out to experts at AllHomeworkAssignments.com. They offer reliable help for Python coding, debugging, and project development.

🧭 Final Thoughts

Python is easy to learn but requires consistency. With clear goals, daily practice, and the right resources, you’ll be writing powerful Python programs in no time. Start small, stay steady, and you’ll master Python from scratch in 2025.

[fromdevcom]

   There’s no doubt that Python is a language on the rise in the world of programming. The multi-purpose, high-level, and object-oriented programming language can be used to develop just about anything, thanks to its numerous diverse features.Designed by a Dutch programmer, Guido Van Rossum in 1991, Python has consistently gained ground and now dominates top programming languages such as Java, C, and C++. Many programmers love its concise, modular and simplistic approach.Today, it’s popularly used in web development, system administration, artificial intelligence, data analysis, scientific computing, and game development industries.In this article, we explain seven reasons why python will continue to rule for the foreseeable future.Python is PopularPopularity is an understatement when it comes to the python programming language. Recent data shows that more than 30,000 people search for the language every month.Some of the reasons behind this growing popularity are because it is beginner-friendly, versatile, and boasts a pseudo-code nature.Python has a friendly, simple, and easy-to-learn syntax that even complete beginners will find easy to master. Just by looking at the code, you can comprehend what it is supposed to do, something most other programming languages can’t promise.It’s also versatile and multi-purpose in the sense that it has packages to do just about everything. Some of the popular ones include SciPy for tech, computations, engineering, and NumPy to crunch numbers, matrices, and vectors. For tasks related to AI, there is Scikit-Learn and Pandas to help with data analysis and manipulation.Strong and Supportive CommunityWith the growing popularity comes a huge community of Python coders with solutions for any imaginable problem. There are also plenty of Python for beginners��� tutorials, documentations, and guides to help programmers handle their projects and beginners to learn the ropes.The rich community with millions of software programmers and developers from all corners of the world means you never have to worry about lacking help and support. Python is surely evolving into a more agile, more refined, and efficient software capable of handling future problems.Open-SourcePython is free for all to use in the sense that it is open-source. What this means is that its source code is available publicly and anyone can use it directly or modify it to suit their programming needs.Besides, you are allowed to distribute copies of the software freely. This may seem insignificant but with open-source software, there are endless possibilities.Python is Used by Tech GiantsNumerous top tech companies are now turning to Python to test and develop their core applications. Some of the most notable players who’ve joined the league include Google, NASA, YouTube, PayPal, Facebook, Netflix, and Reddit.A good example is NASA whose open-source projects such as API, WAS, EVEREST, and APOD are founded on the Python programming language. YouTube also recently started implementing it to manage website templates, video streaming, and obtaining authoritative data.Another large organization that is heavily relying on Python is Walt Disney. The company now uses it as a scripting language for its production and animation-related tasks.Cross-Platform LanguagePython is widely considered to be a portable language because it runs smoothly in various operating systems such as Linux, Windows, Mac, and Ubuntu. But that’s not all; if you entered your code on the Linux platform, you can run it on a Windows or Mac platform. This means you don’t need to make any changes to your code for it to run on another platform. This alone is a timesaver for many coders as it makes application building easier and fuss-free.An Education’s LanguageThe education sector continues to evolve quickly and part of that is the integration of coding in classrooms aimed at equipping students with skills for the future.Python is naturally the language of choice for schools and institutions taking this route and it’s easy to see why.

The language is designed with simple syntax and descriptions that make it user-friendly and easy to use. It also prioritizes user experience which makes it ideal for teaching. Finally, it’s free to use, saving learning institutions millions of dollars that would have otherwise gone to acquire licenses.An Extensive LibraryPython programming language comes with a massive standard library that eliminates the need to write a code or function. This library contains pre-written codes and inbuilt functions that you can use for almost everything. Again this is another huge time-saver, especially for new programmers.Python is Here to Stay!Python is powerful, easy to learn and use, and comes with numerous high-level built-in packages and libraries that make building applications and scripts simple. More importantly, it costs little to use and support is in plenty. If these reasons won’t convince you that it’s one for the future, then we’re not sure what will!

[codingbrushup]

8 Advantages of Choosing Coding Brushup for Java Programming Success

In the world of software development, Java continues to reign as one of the most in-demand programming languages. It powers everything from enterprise-level applications to Android development, making it an essential skill for aspiring developers. But to truly master Java and make yourself industry-ready, you need more than just YouTube videos and outdated tutorials. That’s where Coding Brushup comes into play.

Whether you're just beginning your coding journey or looking to upgrade your current skill set, Coding Brushup for Java programming offers a comprehensive and career-focused learning experience. Let’s explore the 8 key advantages of choosing this platform for your Java training—and why it’s trusted by thousands of learners across India and beyond.

1. Expert-Led Instruction by Industry Professionals

The backbone of any great training program is its instructors. At Coding Brushup for Java, you’ll be learning from professionals who have hands-on experience in real-world software development. These mentors aren’t just academically sound—they work or have worked with top tech companies and bring a wealth of industry insights into the classroom.

2. Industry-Relevant Curriculum and Java Frameworks

Coding Brushup’s Java curriculum is built to match current tech industry demands. Rather than sticking to just theory, the course takes you from the basics of Java syntax to advanced topics such as:

Object-Oriented Programming (OOP)

Collections and Multithreading

JDBC, Servlets, and JSP

Spring, Spring Boot, and Hibernate

RESTful API development

Deployment on AWS or other cloud platforms

3. Real-World Projects and Portfolio Development

When recruiters look at candidates, they’re not just checking for certifications—they want to see what you’ve built. Coding Brushup for Java places a strong emphasis on hands-on learning through:

Mini-projects after each module

Capstone projects based on real-world scenarios

Live coding sessions and hackathons

4. Career-Oriented Java Bootcamp Format

If you're serious about accelerating your career, the Java Bootcamp at Coding Brushup is tailor-made for you. Designed as an intensive 12–16 week program, it includes:

Full-time or part-time schedules

Structured curriculum with weekly goals

Regular assessments and mentor feedback

Dedicated career coaching

This bootcamp approach is ideal for students, career switchers, or working professionals aiming to break into the software industry quickly.

5. Full Stack Developer Pathway with Java Backend

One of the best things about Coding Brushup for Java is how seamlessly it integrates into their Full Stack Developer program. If you're looking to become a versatile developer, this track teaches:

Frontend: HTML, CSS, JavaScript, React/Angular

Backend: Java with Spring Boot and MySQL

Tools: Git, Docker, Jenkins, CI/CD pipelines

This combination gives you end-to-end knowledge of building scalable web applications, making you a full-stack expert—a profile highly sought after by tech recruiters.

6. Python and Cross-Language Skill Development

Beyond Java, Coding Brushup for Python is another high-quality offering. Whether you're diving into data science, backend development, or automation, Python is an essential tool—and Coding Brushup ensures you're well-equipped.

The Python course includes:

Python basics and OOP

Data structures and algorithms

Django and Flask frameworks

Intro to data analysis and machine learning basics

7. Placement Assistance and Career Support

A key reason why Coding Brushup is considered the best institute for Java programming is their 100% placement assistance. Here’s what you can expect:

Resume building and LinkedIn optimization

1-on-1 interview prep and mock technical interviews

Access to a network of hiring partners and startups

Internship opportunities and job referrals

With a dedicated placement team, Coding Brushup helps bridge the gap between learning and employment, making your transition into the IT industry smoother.

8. Flexible Learning Options and Affordable Pricing

Coding Brushup for Java is accessible to everyone—thanks to its flexible learning models and budget-friendly pricing. Choose the format that fits your lifestyle:

Live online classes with mentor interaction

In-person classroom training in selected cities

Self-paced video courses for convenience

Tuition is competitively priced, with EMI options, scholarships, and free trial classes available. It’s a smart investment in your future with a high ROI, especially when compared to more expensive coding bootcamps.

Conclusion:-

Whether you’re aiming to become a backend developer, a full-stack engineer, or even expand into Python and automation, Coding Brushup is your trusted learning partner. With expert mentorship, real-world projects, flexible learning options, and strong career support, it’s easy to see why so many learners choose Coding Brushup for Java programming.

Plus, if you're exploring broader paths, the Coding Brushup for Full Stack Developer and Python bootcamp programs provide everything you need to become a well-rounded developer in today’s competitive tech market.

[optimisticdelusiontheorist]

Python for YouTube: Backend, Scripting & Deployment

YouTube, the world’s largest video-sharing platform, relies on powerful programming languages to ensure smooth functionality, scalability, and efficiency. Python plays a critical role in YouTube’s backend development, scripting, and deployment. Given its simplicity, readability, and extensive libraries, Python helps YouTube manage vast amounts of data, optimize video processing, and enhance user experience.

Python's widespread adoption by tech giants like YouTube proves its importance in modern web applications. If you are looking to understand how Python is used by YouTube, this blog will provide in-depth insights into its role in��backend development, automation, and scaling operations efficiently.

Why YouTube Uses Python

Python is a preferred language at YouTube due to its ease of use, robust libraries, and scalability. Here are some key reasons why YouTube incorporates Python in its ecosystem:

1. Code Readability and Simplicity – Python’s clean and structured syntax makes it easy to maintain and scale.

2. Extensive Libraries and Frameworks – Python provides powerful frameworks like Django and Flask for web development.

3. High Scalability – YouTube’s infrastructure demands scalability, which Python efficiently provides.

4. Fast Development and Deployment – Python speeds up development cycles, making it ideal for scripting and automation.

5. Data Handling and Processing – Python supports large-scale data processing required for recommendations and video analytics.

Role of Python in YouTube’s Backend Development

YouTube’s backend is designed to manage billions of users and videos while maintaining fast load times and minimal downtime. Python contributes significantly to this process by handling:

1. Server-Side Scripting

Python scripts play a crucial role in YouTube’s backend by automating various tasks such as:

Managing video uploads

Processing metadata

Handling user authentication

Generating video recommendations

2. Data Processing and Analytics

Python is used for analyzing massive amounts of user data to enhance YouTube’s recommendation algorithm. Libraries like Pandas, NumPy, and Scikit-learn help process this data efficiently, ensuring personalized video suggestions.

3. Content Delivery Optimization

Python helps optimize YouTube’s content delivery network (CDN) by automating caching strategies and load balancing to deliver videos quickly and efficiently to users worldwide.

4. Handling API Requests

YouTube’s API, which allows third-party applications to interact with the platform, relies on Python to manage requests, retrieve video data, and facilitate integrations seamlessly.

5. Security and User Authentication

Python contributes to YouTube’s robust security framework by managing OAuth authentication, data encryption, and access controls to prevent unauthorized access.

Python’s Role in YouTube’s Automation & Scripting

Automation is a key component of YouTube’s workflow. Python scripts are used extensively for:

Video Processing Automation – Python automates video transcoding and compression, ensuring compatibility across devices.

Spam Detection and Filtering – AI-powered Python scripts detect spam comments and fake user interactions.

Content Moderation – Machine learning models powered by Python assist in identifying inappropriate content.

Automated Testing and Debugging – Python is used to automate unit testing and debugging processes, improving system efficiency.

Python's automation capabilities significantly reduce manual intervention, enhancing operational efficiency at YouTube.

Python for YouTube’s Deployment and Scaling

YouTube must handle an enormous amount of data and traffic efficiently. Python contributes to its deployment strategy through:

1. Cloud Integration – YouTube leverages Python’s cloud-based libraries to manage video storage and streaming services seamlessly.

2. Microservices Architecture – Python enables YouTube to scale operations using microservices, improving efficiency.

3. Continuous Deployment – Python-based DevOps tools help in CI/CD (Continuous Integration/Continuous Deployment), ensuring regular updates without service disruptions.

4. Machine Learning & AI – Python powers YouTube’s AI-driven features, including speech recognition, video recommendations, and auto-captioning.

Softcrayons: Best Python Training Institute

If you want to master Python and build a successful career in backend development, automation, or cloud deployment, Softcrayons is the best institute to learn from.

Why Choose Softcrayons for Python Training?

Expert-Led Training – Learn from industry professionals with real-world experience.

Comprehensive Course Curriculum – Covers basic to advanced concepts, including web development, data analytics, and AI.

Hands-On Projects – Get practical experience with real-time projects.

100% Placement Assistance – Helps students secure top jobs in IT companies. 

Flexible Learning Modes – Offers both online and offline courses.

Python Career Opportunities After Training

Python is in high demand across various industries. With Python training from Softcrayons, you can explore career opportunities in roles such as:

Python Developer

Backend Engineer

Data Analyst

Machine Learning Engineer

DevOps Engineer

Conclusion

Python plays a crucial role in YouTube’s backend development, automation, and deployment strategies. It enables efficient video processing, data analytics, and content delivery, ensuring seamless user experience for billions of users. With its scalability, ease of use, and extensive libraries, Python remains a top choice for tech giants like YouTube.

If you are looking to build a career in Python development, enrolling in a professional Python training course at Softcrayons will give you the necessary skills to excel in the industry. Master Python today and begin your journey of endless career opportunities in web development, automation, data analytics, and AI.

[dcpwebdesigners-blog]

How to Make Money with Programming: 9 Proven Ways to Earn from Your Coding Skills – Infographic

Programming isn’t just a skill, it’s a passport to countless income opportunities. Whether you’re a beginner or a seasoned developer, there are many ways to turn your coding knowledge into a reliable stream of income. 

In this blog post infographic, we’ll explore nine effective ways to make money with programming, from starting a blog to developing games and selling online courses.

Download Infographic

1. Blogging

If you enjoy writing and have a passion for coding, blogging can be a fantastic way to earn money. Starting a programming blog allows you to share tutorials, code snippets, solutions to technical problems, or industry news. Over time, as your blog gains traffic, you can monetise it through:

Google AdSense

Affiliate Marketing (promote tools like GitHub Copilot, hosting providers, or IDEs)

Sponsored Posts

Email List Marketing

Choose a specific niche like Python automation, web development, or data science to attract a targeted audience. The more value you provide, the more loyal readers and passive income you can build.

2. Sell Books

Programmers who can write clearly and teach effectively often find success in self-publishing. Writing an eBook or paperback on a specific programming language, framework, or topic can generate steady income. You could publish:

Beginner guides (e.g. “Learn Python in 30 Days”)

Advanced problem-solving books

Interview preparation guides

You can sell books on platforms like Amazon Kindle Direct Publishing, Gumroad, or your own website. Add bonus material like source code or video content to increase value.

3. Web/App Development

One of the most straightforward and lucrative ways to make money with programming is by developing websites or mobile apps. Businesses everywhere need online presence and custom solutions. You can:

Build websites using WordPress, React, or Laravel

Develop mobile apps using Flutter or React Native

Offer eCommerce development (e.g. Shopify or WooCommerce)

You can sell your services to local businesses, startup founders, or online clients. Alternatively, create your own app or SaaS (Software as a service) and monetise it through subscriptions or ads.

4. YouTube Tutorials

YouTube is a powerful platform for programmers looking to build an audience and generate income. If you’re good at explaining concepts, start a programming channel with:

Coding tutorials (e.g. “Build a Todo App in JavaScript”)

Explainer videos (e.g. “What is an API?”)

Career advice and learning paths

You can earn money through YouTube ad revenue, channel memberships, sponsored videos, and affiliate links. Once your audience grows, you can also use your channel to promote your own products, like courses or software.

5. Freelancing

Freelancing offers flexibility and the ability to earn while working on a wide variety of projects. Platforms like:

Upwork

Freelancer

Fiverr

Toptal

…connect you with clients looking for developers. Whether it’s bug fixes, full-stack development, automation scripts, or WordPress setup, there’s always demand. To succeed, create a strong portfolio, offer competitive pricing, and deliver great results to gain repeat clients and referrals.

6. Games Development

If you’re passionate about gaming and have strong programming skills, consider game development. Platforms like Unity (C#) or Unreal Engine (C++) make it accessible to solo developers. You can:

Create indie games and publish them on Steam or itch.io

Build mobile games and monetise via ads or in-app purchases

Sell game assets, templates, or source code

Some developers also earn by creating tutorials, documentation, or toolkits that help other game developers.

7. Competitions

Coding competitions and hackathons are not just fun, they can be profitable too. Websites like:

HackerRank

Codeforces

TopCoder

Kaggle (for data science)

…often have prize money or sponsorship opportunities. Many companies also host hackathons and innovation challenges where winners receive cash, job offers, or equity. Even if you don’t win, competitions sharpen your skills and can improve your resume or portfolio.

8. Sell Software

Have a great idea for a tool that solves a problem? Package it as software and sell it! This could include:

SaaS tools (e.g. CRM for freelancers)

Developer tools (e.g. code snippet managers)

Desktop apps (e.g. productivity tools)

Browser extensions

You can monetise through one-time purchases, monthly subscriptions, or freemium models with paid upgrades. Promote your product through your blog, social media, or YouTube channel to build traction.

9. Sell Courses

Online learning is booming, and if you’re an expert in a topic, you can create and sell your own programming course. Platforms like:

Udemy

Teachable

Gumroad

Skillshare

…allow you to host and sell your courses to a global audience. Courses could focus on specific programming languages, frameworks, or skills like API development, data analysis, or building real-world apps.

High-quality video content, practical projects, and community support (e.g. Discord or Facebook group) will help you stand out and keep your students engaged.

Conclusion

Programming is one of the most versatile and valuable skills you can have in today’s economy. Whether you would like to work for yourself or build a side hustle, there are many ways to make money with coding, from sharing your knowledge through blogs or courses to building products and solutions for clients or the marketplace.

The key is to start with one path, stay consistent, and keep learning. As you grow in experience and confidence, you can diversify your income by combining multiple strategies. For example, many successful developers run blogs, YouTube channels, and sell software or courses all at once.

So pick your starting point, and begin turning your coding skills into real-world income!

[kodspirit]

How to Master Python Full Stack Like a Pro?

Python Full Stack development is among the most sought-after skills in the IT sector at present. From back-end logic and databases to front-end interfaces, knowing Python Full Stack lets you design, deploy, and maintain entire web applications. To learn how to become an expert in Python Full Stack, this guide will assist you in progressing effectively.

Understand the Fundamentals of Web Development

Before diving deep into Python Full Stack, ensure you have a solid foundation in web development concepts. Learn about: ✔️ HTML, CSS, and JavaScript – The building blocks of web pages. ✔️ Responsive Design – Using frameworks like Bootstrap to make mobile-friendly designs. ✔️ Version Control – Git and GitHub to manage your code efficiently.

Master Front-End Technologies

Even as a full-stack developer, front-end knowledge is crucial. Some key areas to focus on: ✔️ JavaScript (ES6+): Learn the latest JavaScript features to enhance interactivity. ✔️ Frameworks like React.js or Vue.js: Popular choices for modern UI development. ✔️ APIs & AJAX: Fetching and handling data from back-end services.

Dive Deep into Python and Backend Development

Python is the backbone of many full-stack applications. To master it: ✔️ Core Python & OOPs: Understand Python syntax, data structures, and object-oriented programming. ✔ ️ Django or Flask: Master one of these popular Python web frameworks for backend development. ✔️ RESTful APIs: Learn how to build APIs for communication between front-end and back-end. ✔️ Authentication & Security: Implement user authentication with JWT, OAuth, or Django’s built-in authentication system.

Work with Databases Like a Pro

A full-stack developer must know how to manage data efficiently. ✔️ SQL Databases: Learn PostgreSQL or MySQL for structured data management. ✔️ NoSQL Databases: Understand MongoDB for handling unstructured data. ✔️ ORMs (Object Relational Mappers): Use Django ORM or SQLAlchemy to interact with databases easily.

Learn DevOps and Deployment

A pro full-stack developer knows how to deploy and maintain applications. ✔️ Docker & Kubernetes: Containerization for scalable applications. ✔️ Cloud Services: AWS, Google Cloud, or Heroku for deploying web applications. ✔️ CI/CD Pipelines: Automate deployment using GitHub Actions, Jenkins, or Travis CI.

Work on Real-World Projects

Nothing beats hands-on experience! Build projects such as: ✔️ To-Do List App – CRUD operations using Python and a database. ✔️ E-commerce Website – Integrating payment gateways and user authentication. ✔️ Blogging Platform – User registration, content management, and commenting system.

Stay Updated and Keep Practicing

Technology evolves rapidly, so continuous learning is key! ✔️ Follow Python Full Stack blogs, YouTube channels, and communities. ✔️ Contribute to open-source projects on GitHub. ✔️ Take part in coding challenges on platforms like LeetCode, HackerRank, or CodeWars.

Mastering Python Full Stack development takes time and dedication, but with structured learning and practical application, you can become a pro. Start with the basics, build projects, explore new tools, and stay updated with the latest trends. We provide industry-driven master’s programs designed to help you excel in high-demand fields.Your journey to Python Full Stack mastery starts today! Ready to take your Python Full Stack skills to the next level? Start coding now!

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Yeah, I've finally made it! Though, with limited functionality, 'cause I use free accounts everywhere 😬! (I've been so stupid, I accidentally added my name to the domain 🙁)

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Python Roadmap

Embark on Your Python Learning Journey: Master Python Step by Step! 🌟

Hello aspiring developers, tech enthusiasts, and future Python pros! 🐍💻

Are you eager to dive into the world of programming? Whether you're a complete beginner or looking to enhance your coding skills, I’ve got exciting news for you!

I’m launching a comprehensive Python learning series on YouTube, aimed at taking you from zero to Python hero! Whether you’re learning for web development, data science, automation, or just to broaden your programming knowledge, Python is a powerful, versatile language you must master. 🎉

Python is the go-to programming language for various applications, from web development and data analysis to machine learning and AI. But let's be honest—it can be overwhelming to know where to start. That’s why I’ve put together this roadmap to guide you through the learning process in a structured, easy-to-understand way. 💡

🛤️ The Ultimate Python Learning Roadmap

Here’s the detailed structure of this series, designed to make your Python journey enjoyable, practical, and hands-on. We’ll break down each topic step by step, so you can understand and master Python, one lesson at a time.

1️⃣ Starting with the Basics: Laying the Foundation

Introduction to Python: Learn why Python is one of the most popular and easy-to-learn programming languages today.

Setting Up Your Python Environment: Step-by-step guide to installing Python and setting up your IDE.

Your First Python Program: Get started by writing and running your very first Python script.

Variables and Data Types: Understand different data types (int, float, string) and how to use them in your programs.

2️⃣ Core Python Concepts: Dive Deeper into Python

Operators: Master arithmetic, comparison, and logical operators.

Control Flow: Learn about if statements, loops, and how to control the flow of your program.

Functions: Discover how to define and call functions for cleaner, reusable code.

Lists, Tuples, and Dictionaries: Work with Python’s built-in data structures for storing and managing data.

3️⃣ Intermediate Python Skills: Making Progress

Error Handling: Learn how to catch and handle errors to make your programs robust.

Modules and Libraries: Explore Python’s vast ecosystem of libraries, such as math, datetime, and os, to extend your program’s functionality.

File Handling: Learn how to read and write files in Python for real-world applications.

4️⃣ Advanced Python Techniques: Leveling Up

Object-Oriented Programming (OOP): Understand the core concepts of OOP—classes, objects, inheritance, and more.

Regular Expressions: Master text manipulation and pattern matching using regular expressions.

Python for Web Development: Introduction to web frameworks like Flask and Django.

Data Science with Python: Get a brief introduction to popular libraries like pandas, matplotlib, and seaborn for data analysis and visualization.

5️⃣ Real-World Projects: Build as You Learn

Project 1 - To-Do List Application: Start with a simple Python project to practice your skills by building a to-do list application.

Project 2 - Weather App: Develop a Python weather app by integrating APIs to fetch weather data.

🎯 Why You Should Follow This Python Series

Beginner-Friendly: Whether you're completely new to coding or just starting with Python, this series breaks down the concepts step by step.

Hands-On Learning: Each video will guide you through practical examples and coding exercises to help you learn by doing.

Real-World Applications: You won’t just learn syntax—you’ll build useful projects that you can showcase in your portfolio.

Comprehensive Coverage: From Python basics to advanced topics like web development and data science, this series has it all.

Simple & Engaging: I’ll explain even the most complex topics in simple, relatable language to ensure you’re never lost.

📅 What’s Next?

I’ll be releasing two videos every week, so you can learn at your own pace. Each video will cover a specific topic, and by the end of the series, you’ll have a solid grasp of Python and be able to tackle real-world problems with confidence.

👉 Subscribe to my YouTube channel now to get notified about new video releases: Subscribe to my YouTube channel

👉 Have any questions or suggestions? Drop them in the comments—I’m here to help and engage with you!

🚀 Ready to Dive In?

So, whether you’re starting your Python journey or sharpening your existing skills, this series has something for everyone. Grab your laptop, unleash your curiosity, and let’s master Python together, step by step. The adventure is just beginning!

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Top Full Stack Development Interview Questions Every Candidate Should Know

Preparing for a full stack development interview can be a daunting task. The field requires comprehensive knowledge of both front-end and back-end technologies, and interviewers often ask questions that test a candidate’s in-depth understanding of various programming concepts, frameworks, and best practices. To set you up for success, this guide covers some of the top full stack development interview questions you should be prepared for. Additionally, be sure to check out this YouTube video guide on essential full stack interview questions for further insights.

1. What is Full Stack Development?

Full stack development involves creating complete web applications, encompassing both the front-end (client-side) and back-end (server-side) development. Full stack developers are proficient in HTML, CSS, JavaScript, and at least one back-end language, such as Node.js, Python, Ruby, or Java.

2. Explain the Differences Between Front-End and Back-End Development.

Front-End Development focuses on the user interface and user experience. Technologies include HTML, CSS, JavaScript, and frameworks like React, Angular, and Vue.js.

Back-End Development deals with server-side logic, databases, and APIs. Popular technologies include Node.js, Express.js, Python (Django, Flask), Ruby on Rails, and Java (Spring).

3. What Are RESTful Services and APIs?

REST (Representational State Transfer) is an architectural style that uses HTTP requests for communication. RESTful APIs allow communication between client and server through GET, POST, PUT, and DELETE operations. It ensures stateless operations and a standardized way of building APIs, making them scalable and easily maintainable.

4. Can You Explain the Concept of MVC Architecture?

MVC (Model-View-Controller) is a design pattern used to develop web applications. It separates an application into three interconnected components:

Model: Represents the data and business logic.

View: Displays data to the user.

Controller: Handles input and updates the model or view accordingly. This architecture promotes modularization and makes code maintenance more manageable.

5. What Are the Advantages of Using Node.js for Back-End Development?

Node.js is widely used for its asynchronous, event-driven nature, making it suitable for building scalable network applications. Key advantages include:

Single Language: JavaScript can be used both on the client-side and server-side.

High Performance: Thanks to its non-blocking I/O operations.

Vast Ecosystem: Access to thousands of libraries through npm (Node Package Manager).

6. What Is the Role of a Package Manager in Full Stack Development?

A package manager, such as npm or Yarn, helps developers install, update, and manage dependencies for a project. It simplifies the process of adding libraries and frameworks, ensuring version control and smooth project development.

7. Explain the Concept of Asynchronous Programming in JavaScript.

Asynchronous programming allows the execution of non-blocking code, enabling functions to run in the background without stopping the main thread. Techniques like callbacks, promises, and async/await are used to handle asynchronous operations.

8. What Are Promises and How Do They Work?

A promise in JavaScript represents a value that may be available now, or in the future, or never. It has three states:

Pending: Initial state, neither fulfilled nor rejected.

Fulfilled: Operation completed successfully.

Rejected: Operation failed. Promises make it easier to manage asynchronous operations compared to traditional callbacks.

9. What Is the Importance of Version Control Systems in Development?

Version control systems like Git help track changes in code over time, allowing multiple developers to collaborate seamlessly. They provide features like branching, merging, and the ability to revert to previous code versions, essential for maintaining project integrity.

10. What Are the Benefits of Using Frameworks like React or Angular for Front-End Development?

React: Offers a component-based architecture, virtual DOM for enhanced performance, and easy integration with other libraries.

Angular: Provides a complete solution with two-way data binding, dependency injection, and a powerful CLI for streamlined development. Frameworks accelerate development, enhance code readability, and promote reusability.

11. How Would You Optimize a Website’s Performance?

Performance optimization strategies include:

Minimizing HTTP Requests: Using image sprites, combining CSS/JS files.

Lazy Loading: Loading images or components only when needed.

Caching: Leveraging browser caching for static resources.

Content Delivery Network (CDN): Distributing content through servers located close to users.

Compression: Using Gzip or Brotli to compress files.

12. What Are the Security Concerns in Web Development, and How Do You Address Them?

Common security concerns include:

Cross-Site Scripting (XSS): Prevented by sanitizing user input.

SQL Injection: Avoided using parameterized queries or ORM libraries.

Cross-Site Request Forgery (CSRF): Mitigated with anti-CSRF tokens.

Secure Authentication: Implementing HTTPS and password hashing.

13. Describe a Few Commonly Used Database Solutions and When to Use Them.

SQL Databases (e.g., MySQL, PostgreSQL): Structured data, relational.

NoSQL Databases (e.g., MongoDB, Cassandra): Unstructured data, flexible schema, ideal for large-scale applications with rapidly changing requirements.

14. How Do You Ensure Code Quality and Maintainability?

Ensuring code quality involves:

Writing Clean, Readable Code: Following industry standards.

Unit Testing: Using tools like Jest or Mocha for JavaScript.

Code Reviews: Regular peer reviews for feedback.

Linting Tools: ESLint or Prettier for code consistency.

Conclusion

Preparing for full stack development interviews requires a solid understanding of both fundamental concepts and advanced topics. Familiarize yourself with these questions, practice your coding skills, and stay updated on the latest industry trends. Don’t forget to enhance your preparation by watching this comprehensive video on top interview questions to gain more tips and insights.

By thoroughly preparing for these questions and understanding the core principles behind them, you’ll be well on your way to acing your full stack development interview and landing your dream job.

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Prompt Engineering Overview

YouTube Lecture Summary: 00:41  Prompt engineering involves using instructions and context to leverage language models effectively for various applications beyond just language tasks. 02:18  Prompt engineering is crucial for understanding language model capabilities, applicable in research and industry, as highlighted by job postings emphasizing this skill. 03:37  Components of a prompt include instructions, context, input data, and output indicators, affecting the model's response, with elements like temperature and top P influencing model output diversity. 05:45  Prompt engineering applies to various tasks like text summarization, question answering, text classification, role playing, code generation, and reasoning, showcasing diverse applications. 09:57  Language models, like OpenAI's, exhibit impressive code generation abilities, handling queries from natural language prompts for tasks such as SQL query generation. 10:51  While language models can reason to an extent, specific prompts and techniques like Chain of Thought prompting aid in improving their reasoning capabilities, although it's an evolving field. 11:19  The lecture delves into code examples and tools, showcasing how prompt engineering techniques are applied practically, using OpenAI's Python client and other tools. 19:34  Advanced techniques like Few Shot Prompts, Chain of Thought prompting, and Zero Shot Chain of Thought prompting boost performance on complex tasks by providing demonstrations and step-by-step reasoning instructions to the language model. 23:13  Prompt engineering is an exciting space where crafting clever prompts empowers language models, allowing for powerful capabilities and advancements in various applications. 23:27  Prompt engineering aims to improve language models for complex reasoning tasks, as these models aren't naturally adept at such tasks. 24:22  Self-consistency in prompting involves generating multiple diverse reasoning paths and selecting the most consistent answers, boosting performance on tasks like arithmetic and Common Sense reasoning. 25:16  Demonstrating steps to solve problems within prompts guides models to produce correct answers consistently. 26:37  Using language models to generate knowledge for specific tasks has emerged as a promising technique, even without external sources or APIs. 30:15  Program-aided language models use interpreters like Python to generate intermediate reasoning steps, enhancing complex problem-solving. 32:35  React frameworks utilize language models and external sources interchangeably for reasoning traces, action plans, and task handling. 35:20  Tools and platforms for prompt engineering offer capabilities for development, evaluation, versioning, and deployment of prompts. 40:08  Various tools allow combining language models with external sources or APIs for sophisticated applications, augmenting the generation process. 44:45  Leveraging tools like Long-Chain allows building on language models by chaining and augmenting data for generating responses. 46:22  Prompt engineering involves combining react-based actions with language models, showcasing the observation, thought, and action sequence for varied tasks. 47:53  Updated and accurate information from external sources is crucial for prompt engineering applications, highlighting the importance of up-to-date data stores. 48:34  Data augmentation in prompt engineering involves reliance on external sources and tools to generate varied content, requiring data preparation and formatting. 50:34  Prompt engineering explores clever problem-solving techniques to engage language models effectively, like converting questions into different languages while maintaining context and sources. 52:40  Model safety is a critical aspect of prompt engineering, focusing on understanding and mitigating language model limitations, biases, and vulnerabilities, including initiatives like prompt injections to identify system vulnerabilities. 55:12  Potential vulnerabilities like prompt injection, prompt leaking, and jailbreaking highlight risks of manipulating language model outputs, emphasizing the importance of reinforcing system safety measures. 58:30  Reinforcement Learning from Human Feedback (RLHF) aims to train language models to meet human preferences, emphasizing the relevance of high-quality prompt datasets in this training process. 01:00:06  Prompt engineering facilitates the integration of external sources into language models, enabling diverse reasoning capabilities and applications, particularly useful for scientific tasks requiring factual references. 01:01:27  Understanding emerging language model capabilities, such as thought prompting, multi-modality, and graph data handling, is a crucial area for future exploration and development in AI research.