#python3

Python Quiz: What is the Output? x = 10 if x == 10: print("Hello")

You may have heard about the Model Context Protocol and wondered how it lets AI tools connect to other tools, APIs, and systems. Well, it's all thanks to MCP servers. In this guide, @manishmshiva explains how MCP servers work and helps you build your own with Python and the FastMCP library.

Python Quiz: What is the Output? A) 5 B) 7 C) 8 D) 4

Which language is the best for creating games ? 1. Python 2. C++ 3. Java 4. C# 5. Rust

The field of Cryptography is all about securing both data and communication between systems. And in this course, you'll learn the basics like hashing, symmetric and asymmetric encryption, and more. By the end, you'll have built a fully-functioning Python-based command line cryptography tool.

STOP WASTING HOURS TRYING TO FIGURE OUT WHAT TO LEARN IN AI. I put together one practical roadmap with videos, GitHub repos, guides, books, research papers, and courses. VIDEOS: 1. LLM Introduction — 2. LLMs from Scratch — 3. Agentic AI Overview (Stanford) — 4. Building & Evaluating Agents — 5. Building Effective Agents — 6. Building Agents with MCP — 7. Building an Agent from Scratch — 8. Philo Agents — GITHUB REPOS: 1. GenAI Agents — 2. Microsoft AI Agents for Beginners — 3. Prompt Engineering Guide — 4. Hands-On Large Language Models — 5. GenAI Agents — 6. Made with ML — 7. Hands-On AI Engineering — 8. Awesome Generative AI Guide — 9. Designing Machine Learning Systems — 10. Machine Learning for Beginners — 11. LLM Course — GUIDES: 1. Google's Agent Whitepaper — 2. Google's Agent Companion — 3. Building Effective Agents by Anthropic — 4. Claude Code Agentic Coding Practices — 5. OpenAI's Practical Guide to Building Agents — BOOKS: 1. Understanding Deep Learning — 2. Building an LLM from Scratch — 3. The LLM Engineering Handbook — 4. AI Agents: The Definitive Guide — 5. Building Applications with AI Agents — 6. AI Agents with MCP — 7. AI Engineering — RESEARCH PAPERS: 1. ReAct — 2. Generative Agents — 3. Toolformer — 4. Chain-of-Thought Prompting — COURSES: 1. Meta Data Analyst Professional Certificate: 2. Google Advanced Data Analytics Professional Certificate: 3. Microsoft Power BI Data Analyst Professional Certificate: 4. Google Data Analytics Professional Certificate: 5. Introduction to Data Analytics: 6. Machine Learning Specialization: 7. IBM Deep Learning with PyTorch, Keras and Tensorflow Professional Certificate: 8. Deep Learning Specialization: 9. Crash Course on Python: 10. Python for Data Science, AI & Development: 11. ChatGPT + Excel: AI-Enhanced Data Analysis & Insight Specialization: 12. Work Smarter with Microsoft Excel: 13. Microsoft Excel Professional Certificate: 14. Excel Basics for Data Analysis: 15. SQL Foundations: Repost so someone else can find this roadmap, and pls consider following @Mohiniuni for more content around AI, Beauty, and businesses.

Python Quiz: What is the Output?

🚨 CRITICAL SECURITY ALERT PHP, GitLab & Node.js were already facing serious security vulnerabilities. Now, Linux, Python & Java are also in the spotlight. The potential impact across the tech stack is huge.

Learn Coding by playing games 1. Kubernetes 2. DevOps 3. Linux 4. Git 5. Python 6. CSS & HTML 7. Cybersecurity 8. Mobile Coding (like Duolingo) 9. For Complete Beginners 10. 25+ Programming Languages

Learn Python. ⠀ Learn JavaScript. ⠀ Learn React. ⠀ Learn Docker. ⠀ Learn AWS. ⠀ Learn Kubernetes. ⠀ Finally, you start feeling confident. ⠀ Then someone says, “I built the whole app with a prompt.” ⠀ Welcome to being a developer. ⠀ After 16+ years in engineering, I understand why this feels exhausting. Every time you get comfortable, the industry gives you more homework. ⠀ But I’d redraw the last part of this curve. ⠀ Your engineering knowledge still matters when you have to explain why: ⠀ • The app works locally but fails in production. ⠀ • One database query takes down the API. ⠀ • A retry charges the customer twice. ⠀ • An AI-generated endpoint lets users access someone else’s data. ⠀ Knowing how to investigate those problems takes experience. Every layer you learned gives you somewhere to start. ⠀ That knowledge helps while you’re prompting, too. ⠀ You can spot a missing requirement, question a design choice, and catch a dangerous assumption before it spreads across twenty files. ⠀ I want AI to handle more of the repetitive work. I also want to understand what I’m putting into production. ⠀ If you’re feeling behind, try this: ⠀ Take one small feature you already know how to build. Ask an AI coding tool to implement it. Then review the result like a teammate’s pull request. ⠀ 1. Read the diff. ⠀ 2. Check the dependencies. ⠀ 3. Test the failure cases. ⠀ 4. Find something you would change and explain why. ⠀ You’ll learn the tool while exercising the judgment you’ve spent years developing. ⠀ And if you’re just starting, follow the generated code all the way through: from the button, to the API, to the database, and back. ⠀ You don’t have to restart your career every time the tools change. ⠀ You do have to keep learning. That part of the picture has always been accurate. ⠀ Which skill on this chart took you the longest to learn?

✅ How to Learn Python Programming in 10 days ! .#pythonprogramming #python3 #pythoncode #pythonlearning #pythondeveloper #pythonprojects

this is f*cking brilliant... a 16-year-old CS student in China figured out how to run 300 Grok Bots for less than $0.02 per bot per week. the same swarm could cost $4,500 a week. he eliminated pointless status checks, stopped rereading entire chat histories, and killed endless retry loops. now most bots only wake up when there's actual work to do. Here 20 GitHub repos he used to make the setup cheaper: 01 Crawl4AI → turn web pages into clean Markdown before analysis, reducing the navigation menus and page clutter your bot has to read 02 Firecrawl → collect web content as Markdown or structured data so your workflow can select the fields it actually needs 03 Chonkie → split long documents into manageable chunks so retrieval can select relevant passages instead of attaching the whole document 04 FlagEmbedding → rerank retrieved passages before generation, keeping the strongest evidence and dropping irrelevant matches from the prompt 05 LLMLingua → compress lengthy inputs before the model reads them. preserve the facts, constraints, and qualifications your task depends on 06 RTK → compress common command outputs before they enter the conversation, keeping repetitive logs from swallowing the useful context 07 GPTCache → reuse suitable answers to similar requests instead of generating them again. define matching and freshness rules around the task 08 Portkey Gateway → cache matching API responses behind a shared gateway, letting connected workflows reuse answers across repeated requests 09 Prefect → cache successful task results and reuse them when the configured inputs match, avoiding unnecessary reruns of completed workflow steps 10 Mem0 → store and retrieve relevant facts across runs so each assignment can start with selected memory instead of the entire conversation 11 Graphiti → keep changing facts and relationships in a searchable graph, then retrieve the relevant context instead of replaying the event history 12 requests-cache → keep fetched responses with expiry rules, then let your scripts reuse valid data before asking the bot to investigate again 13 Hishel → add HTTP caching and revalidation to your fetching tools, keeping unchanged responses out of repeated download-and-analysis cycles 14 APScheduler → schedule lightweight checks in Python and batch nonurgent work before handing useful updates to the agent 15 Celery → put background jobs on a worker queue so code handles waiting and dispatch while model calls happen inside the tasks that need them 16 PyBreaker → pause calls to a repeatedly failing service after a configured threshold, stopping one broken dependency from generating endless attempts 17 LiteLLM → track spending and set budgets for connected API calls before one runaway workflow eats the whole allowance 18 RouteLLM → route simpler API requests to a cheaper model and reserve the stronger one for work that needs it 19 Semantic Router → match requests to predefined workflows using local embeddings instead of paying a large model to decide every next step 20 Phoenix → trace your instrumented AI workflow, inspect repeated calls, and compare changes against output quality before keeping an “optimization” connect the tools your workflow needs through the terminal, MCP, or your own code. route API calls through the gateway or router you choose so its controls actually apply start with the biggest leak: oversized inputs, repeated research, empty checks, or failed operations that keep restarting filter before reading → reuse before generating → check for changes → stop failed loops then measure completed work against total usage, including the tools running around your bot the full course below shows how to put the workflow together ↓

Top 4 Python patterns ✍️

‼️ Alert - Critical Brotli flaw behind #Node2Shell RCE goes far beyond Node.js. Bun, Python Brotli packages, Envoy, Istio and other widely used software are also affected by the same CVE-2026-111497 memory-corruption vulnerability. Read full details ↓

holy f*ck, Anthropic put an entire Claude degree on GitHub for free... 7 repos, ~465K stars, and in the right order they take you from your first prompt to an agent that reviews your PRs while you sleep. each repo is the next layer of the one before. prompt-eng-interactive-tutorial -> how to talk to Claude 9 chapters, from basic prompt structure to cutting hallucinations ↳ claude-cookbooks -> copy-paste recipes notebooks for RAG, tool use, vision, sub-agents and prompt caching ↳ claude-quickstarts -> full apps you can deploy 17 starter projects, from a support agent to Claude controlling a desktop ↳ skills -> teach Claude your workflows one folder with a SKILL.md and Claude does the task the same way every time ↳ claude-agent-sdk-python -> your own agent the Claude Code agent loop in Python, with your own tools and hooks ↳ claude-code -> the agent in your terminal reads your codebase, edits files, runs commands and handles git ↳ claude-code-action -> the agent in your repo tag @claude on a PR or issue and it reviews the code or pushes a fix ↳ build one agent with these and you become the person your team brings every AI project to, and that’s usually where the raise starts the Opus 5.5 prompting guide that goes on top of all 7 is below ↓

Stop wasting time running scripts manually on Kali Linux 🛑 I built an interactive Python tool that detects, cleans, and deploys .sh, .py and .exe files

If you started using Claude this year, install these before anything else. Here are 32 free skills that skip the months of trial. They come from 9 GitHub repos with 252K stars. NOTES & RESEARCH obsidian-markdown → Notes Obsidian can read. obsidian-bases → Notes into tables. json-canvas → Mind maps on a canvas. defuddle → Clean text from any page. notebooklm → Query your notebooks. huggingface-papers → Find AI papers. WRITING humanizer → Strip the AI tells. copywriting → Landing pages and ads. copy-editing → Edit line by line. social → Posts for LinkedIn and X. emails → Write email sequences. content-strategy → Plan what’s next. writing-guidelines → Make docs clear. MARKETING seo-audit → Find why you don’t rank. ai-seo → Get cited by AI. launch → Plan a product launch. pricing → Set your prices. lead-magnets → Freebies that grow lists. marketing-psychology → Why people buy. AUTOMATE n8n-workflow-patterns → Proven n8n flows. n8n-node-configuration → Set up nodes. n8n-expression-syntax → Fix expressions. n8n-validation-expert → Read n8n errors. n8n-code-javascript → Code in n8n nodes. BUILD & SHIP react-best-practices → Fast React code. web-design-guidelines → Catch UI mistakes. deploy-to-vercel → Go live with a link. modern-python → Python with uv and ruff. huggingface-gradio → Quick Python demos. huggingface-spaces → Host your AI app. huggingface-local-models → Run models locally. context-fundamentals → How context works. Don’t install all 32 tonight. Pick the folder closest to your daily work and add one skill from it. Give it a week of real tasks. If it saves you time, keep it and add the next. Honestly, 3 skills you use daily beat 30 sitting in a folder. For more cheat sheets like this, subscribe → Repost ♻️ to help a Claude beginner in your network.

Skills are the most underrated AI feature right now... You teach your AI once, and it remembers every time Build it right, and it runs in Claude and ChatGPT

⚠️🚨 THIS IS NOT A DRILL 🚨⚠️ Google has officially declared a bug in Brotli, its tool that shrinks web traffic, CRITICAL: 9.2 out of 10. Last night "Node2Shell" evolved into HTTP2SHELL. A formal CVE record has been issued citing CVE-2026-111497 -- a hole in versions 1.0.3 to 1.2.0 that can hit any app unpacking data from strangers, and could let them take it over. What this means: ▪️ This is not a Node.js problem anymore. This is an HTTP PROBLEM. ▪️ Every unpatched app across Node.js, Python, Bun, and Envoy that unpacks Brotli now has a hole attackers need no login to use ▪️ Istio. curl. Python's requests and httpx. All at risk under one CVE. ▪️ EVERY project that bundles Brotli must ship its own fix, and not all are out yet This changes everything. A normal bug can be fixed in one place. A 9.2 bug inside a shared tool cannot. We just entered the most dangerous phase of this crisis. If you're not paying attention - start now. Save this. Share this. This is the moment it escalated beyond return.

Which Programming Language Is the Easiest to Learn? If you're a beginner, choosing your first programming language can feel confusing. Here’s a quick comparison of 11 popular programming languages using the classic “Hello, World!” program: My recommendation: Start with Python if you're new to programming. Its readable syntax lets you focus on problem-solving before dealing with too many language-specific details. Remember, the easiest language depends on your goals and background! Which programming language did you learn first? Save this guide and share it with a beginner! Follow @CLCODING for more coding tips and programming tutorials.

Best YouTube Playlists to learn Programming: C C++ Python Java C# SQL Go PHP Swift Kotlin Dart Ruby Rust TypeScript R React Next.js Node.js HTML/CSS Machine Learning Deep Learning DSA Follow @Arina_sharmi for more