GitHub Copilot: A Terminal Upgrade for Developers

🚀 AI is entering the terminal! GitHub has just taken Copilot to the next level with the new GitHub Copilot CLI — and it’s a total game-changer for developers. 💡 With Copilot CLI, you can now use AI assistance directly from your command line — no need to open VS Code or any editor. Just type natural language commands and let Copilot generate, explain, or debug your code instantly. ⚙️ Here are some of the cool things you can do with it 👇 ✅ Ask Copilot to generate scripts (e.g., “create a Python Fibonacci script”) ✅ Use gh copilot explain to understand complex code snippets ✅ Use gh copilot suggest to get code suggestions directly in your terminal ✅ Integrates smoothly with GitHub CLI ✅ Works across Command Prompt, PowerShell, and Windows Terminal 💻 In my latest YouTube video, I’ve covered the step-by-step installation and setup of GitHub Copilot CLI on Windows, including authentication, configuration, and a quick demo. 🎥 Watch here 👉 https://lnkd.in/gz76eG-b If you love exploring AI + Development tools, this one’s definitely worth trying! #GitHub #Copilot #GitHubCopilot #AI #DeveloperTools #CLI #Windows #Coding #Programming #Automation #GitHubCLI

Exploring GitHub Copilot in the CLI Today I explored GitHub Copilot for the command line (CLI) — and it’s quite interesting to see how AI is being integrated beyond the IDE! When I tried: gh copilot suggest "write a prime number program in Java below 10"   Copilot responded with a PowerShell/Bash script instead of Java code. That’s when I realized something important — the CLI version of Copilot is mainly built to assist with terminal and GitHub commands, not full programming code like the VS Code extension does. A few key takeaways: gh copilot suggest helps you write or refine shell and GitHub commands gh copilot explain clarifies what a command does Have you tried GitHub Copilot in the CLI yet? #GitHubCopilot #CLI #AI #Automation #Developers #VSCode #OpenAI #CodingProductivity

🚀 Pushing Code to GitHub – Made Simple! If you're just starting out with Git and GitHub, this visual guide is your new best friend. It breaks down the essential steps to move your code from your local machine to a remote repository — no fluff, just the commands that matter. 🔹 Local Git Setup git init – Start tracking your project git add – Stage your changes git commit -m "your message" – Save a snapshot 🔹 Connect to GitHub git remote add origin – Link your local repo to GitHub git push -u origin main – Push your code and set upstream Whether you're building your first Python script or deploying a full-stack app, mastering this flow is a must. #GitHub #Git #VersionControl #DevLife #CodingTips #100DaysOfCode #TechForBeginners #Python #OpenSource #SoftwareEngineering

I was curious about how Git works. I watched a bunch of videos about git, its working and how it stores, verifies and protects data. So I thought of making my own mini git named "LUMO". To start, I built its foundation — "Origin" — basically v1.0 of LUMO. What origin does so far : 1. Repository initialization (.origin). 2. SHA-1 hashing for files. 3. Git-style headers (blob <size>\0). 4. Data compression with zlib. 5.Hash-based object storage. 6.A custom .origin/index to track filenames and hashes. Right now, I’m testing it directly with sample files to ensure hashing, compression, and storage all behave exactly like Git before adding command support. Through this, I’ve learned how Git structures data internally, how zlib compression works at the binary level, and how file integrity is maintained using hashing and immutability. •Project: Origin. • Language: C++,C(SHA1 implementation). • Libraries: OpenSSL (SHA-1), zlib (Compression). •Github link : https://lnkd.in/d7NbKvkS #GitInternals #OpenSource #SoftwareEngineering #VersionControl #Programming #DeveloperJourney #LearningByBuilding #CodingProjects #DataIntegrity #Compression #Hashing #Zlib #OpenSSL #GitImplementation #TechLearning

Install Github Copilot on your computer terminal using this line of code: npm install -g @github/copilot. 🔧 Why it matters: - Terminal-native development: Work with Copilot coding agent directly in your command line — no context switching required. - GitHub integration out of the box: Access your repositories, issues, and pull requests using natural language, all authenticated with your existing GitHub account. - Agentic capabilities: Build, edit, debug, and refactor code with an AI collaborator that can plan and execute complex tasks. - MCP-powered extensibility: Take advantage of the fact that the coding agent ships with GitHub's MCP server by default and supports custom MCP servers to extend capabilities. - Full control: Preview every action before execution — nothing happens without your explicit approval. Resources: https://lnkd.in/djKeTtvH Tutorial link on how to use the cli: https://lnkd.in/dR96S2je #GitHubCopilot #CopilotCLI #AIForDevelopers #DevTools #SoftwareDevelopment #OpenSource #Terminal #Productivity #MCPServer #DeveloperCommunity #JavaScript #Python #FullStackDevelopment #logixseven

🐳 5 Practical Tips for Writing a Clean and Optimized Dockerfile Working with Docker every day taught me one thing — the smaller and cleaner your image, the happier your deployment pipeline will be. Here are a few practical lessons I’ve learned: 🔹 Use official base images. Start with something like python:3.11-slim instead of ubuntu:latest. Smaller, faster, and easier to maintain. 🔹 Combine RUN commands. Every RUN creates a new layer. Combine them: RUN apt-get update && apt-get install -y curl && rm -rf /var/lib/apt/lists/* 🔹 Use .dockerignore. Don’t copy unnecessary files (logs, .git, configs) into your image. It keeps the build fast and secure. 🔹 Set a working directory. WORKDIR /app Keeps things organized and avoids path confusion. 🔹 Use multi-stage builds. Compile in one stage, run in another — smaller and cleaner final image. ✅ A Dockerfile isn’t just a build script — it’s part of your production. Treat it like code. #Docker #DevOps #Optimization #CICD

I’ve created and uploaded a Python repository on GitHub — perfect for beginners who want to practice Python, review core concepts, or simply understand the syntax in an easy and organized way. This repository includes well-structured examples and simple scripts that can help anyone starting their Python journey or refreshing their knowledge. 📂 GitHub Repository: https://lnkd.in/ecHVT7F2 Whether you’re learning, revising, or exploring Python, this repo can be a great starting point! Feel free to fork, explore, and contribute. 💻 #Python #Programming #GitHub #Coding #Developers #PythonForBeginners #LearnToCode

🚀 Dockerizing My Project — Step-by-Step Guide from Code to Container! 🐋 After exploring Docker in depth, I finally containerized my own FastAPI project — turning a normal app into a fully functional Docker image ready to run anywhere! 🌍 From writing the Dockerfile and defining base images, working directories, and environment variables — to building, running, exposing ports, and finally pushing the image to Docker Hub, this journey helped me deeply understand how real-world deployment pipelines work. 💻⚙️ Here’s what this guide covers: ✅ Creating and understanding Dockerfile commands (FROM, WORKDIR, COPY, RUN, CMD, EXPOSE, ENV) ✅ Building custom Docker images (docker build -t appname:version .) ✅ Running containers with port binding (docker run -p 8000:8000 --name myapp appname:1.0) ✅ Hosting your image on Docker Hub 🌐 ✅ Complete example: House Price Prediction App with FastAPI & Docker 📂 Full Step-by-Step Setup + Example Code available on GitHub 👇 🔗 Material Link:- https://lnkd.in/edkr-uFv 🔗 Sample Project:- https://lnkd.in/eHwa7VKD 🔗 Docker Image Link:- https://lnkd.in/ea26qdPG This hands-on experience made me realize how Docker makes deployment, scalability, and portability so effortless across environments! 💙 #Docker #DevOps #FastAPI #Python #Containerization #CloudComputing #SoftwareEngineering #Dockerfile #OpenSource #LearningJourney #DockerHub #GitHub #ProjectShowcase #TechCommunity #DeveloperJourney

🚀 Unleashing Your Coding Potential: IDEs vs Desktop Agent MCP Ever wonder how to truly supercharge your professional abilities? The answer might surprise you. IDEs (Integrated Development Environments) offer distinct advantages over Desktop Agent MCP setups. Here's why: • Versatility: Effortlessly craft Python and PowerShell scripts • All-in-One Functionality: Collect, interact, analyze, decide, and create • Limitless Possibilities: Push boundaries and expand your capabilities By embracing an IDE, you become your own AI-powered copilot. Your coding prowess reaches new heights, empowered by robust development tools. Question: Which IDE has been your game-changer? How has it amplified your productivity? Share your coding revelations below! 👇 #DeveloperProductivity #CodingTools #TechInnovation