Building and Shipping Python Software with CI/CD Pipeline

If you’ve ever wondered what really happens behind: pip install I broke it down here: https://lnkd.in/gtCmxDg6 What looks like a simple command is actually a pipeline: • Your project is built into distribution artifacts • Those artifacts are published to sources like PyPI • The installer resolves dependencies and selects versions • It prefers wheels for faster installs • Falls back to building from source when needed • Finally installs everything into site-packages The key shift: - You are not installing source code. - You are installing a built artifact. This is why you’ll notice: • Some installs are instant • Some take significantly longer • Some fail due to build or environment issues #Python #PythonPackaging #PyPI #SoftwareEngineering #DeveloperTools #Programming #BuildSystems #DevTools #OpenSource

🚀 Just wrapped up my latest Python project: A smart Command-Line Task Tracker! I wanted to move beyond basic scripts and tackle real-world data management. Here are the top 3 concepts I leveled up while building this: 💾 File Persistence: Built a permanent "filing cabinet" using Python's with open() to safely serialize, save, and reload user data. ⏳ Dynamic Data vs. Static Data: Used the datetime module to recalculate "days remaining" every time the app boots, rather than hard-coding static dates into the save file. 🌿 Clean Git Workflow: Managed isolated feature testing using git checkout -b and used .gitignore to keep system files out of my remote repo. This project really solidified my understanding of how data flows in and out of a program seamlessly. On to the next build! 💻 #Python #SoftwareDevelopment #CodingJourney #Git

𝗨𝗡𝗟𝗘𝗔𝗦𝗛𝗜𝗡𝗚 𝗧𝗛𝗘 𝗨𝗟𝗧𝗜𝗠𝗔𝗧𝗘 𝗣𝗬𝗧𝗛𝗢𝗡 𝗣𝗢𝗪𝗘𝗥𝗛𝗢𝗨𝗦𝗘: 𝗧𝗛𝗘 𝗦𝗘𝗖𝗥𝗘𝗧 𝗧𝗢 𝗕𝗨𝗜𝗟𝗗𝗜𝗡𝗚 𝗟𝗜𝗚𝗛𝗧𝗡𝗜𝗡𝗚 𝗙𝗔𝗦𝗧 𝗔𝗣𝗜𝗦 𝗥𝗘𝗩𝗘𝗔𝗟𝗘𝗗 As we head into 2026, building scalable microservices requires a rock-solid understanding of how your code is organized from the first line. This guide demystifies the structural foundations of FastAPI to ensure your backend remains maintainable as your codebase grows. THE FASTAPI INSTANCE The core of every application begins with initializing the FastAPI class. This instance acts as the central router and configuration hub, serving as the bridge between your incoming HTTP requests and your internal application logic. Understanding how to instantiate this object correctly is the first step toward managing middleware, dependencies, and route decorators effectively. ROUTING AND PATH OPERATIONS Path operations are the fundamental building blocks of your API. By using decorators linked to your FastAPI instance, you define how the server responds to specific HTTP methods like GET or POST. This video breaks down how these functions map directly to URL paths, allowing for clean, readable code that handles client communication without unnecessary complexity. PARAMETER HANDLING AND TYPE HINTS FastAPI leverages Python type hints to perform automatic data validation and documentation. By defining expected types for path parameters, query parameters, and request bodies, you enable the framework to enforce data integrity before your logic even executes. This approach significantly reduces the surface area for bugs while providing built-in Swagger UI documentation for your endpoints. As a Senior Engineer, I cannot overstate that the structure of your application in 2026 is just as important as the logic inside it. FastAPI enforces good habits early by requiring explicit type definitions and clear route mapping, which saves hundreds of hours in debugging and refactoring down the line. Treat your project structure as your primary documentation. Tags: #FastAPI #Python #API #BackendDevelopment 📺 Watch the full breakdown here: https://lnkd.in/d7YeSp75

I wrote a 6-part series on DevSecOps pipeline tooling — a deliberately vulnerable Python app scanned by open-source tools wired into GitHub Actions. This is not exhaustive but covers the essentials to get started. Part 1 – Secret Scanning with Gitleaks: https://lnkd.in/gN6GjP5M Part 2 – SAST with Bandit: https://lnkd.in/g7atYGRC Part 3 – SCA with pip-audit: https://lnkd.in/gBTaYqXk Part 4 - IaC Scanning with Checkov: https://lnkd.in/gmsCQZdj Part 5 – Container Scanning with Trivy: https://lnkd.in/gSUseHZV Part 6 – Putting it all together in one pipeline: https://lnkd.in/g8cvgH2E #devsecops #cicd #github

MentisDB now has a Python client and also integration with LangChain. (Not my idea, but my agent's) Used my PyPi account, created the Github CI workflow and published to PyPi all by itself. But sure, AGI isn't here yet. Here's the blog post it wrote about this new feature https://lnkd.in/gaYB2PjG

Laziness: the underrated superpower of every programmer. Built a small CLI tool that kills the most boring part of starting a new project. The problem: Every new project means the same manual steps — configuring ESLint, Prettier, Husky, commitlint, wiring scripts, setting up git hooks. Easy to misconfigure. Always time-consuming. The fix: One command, a few prompts, and your project is ready — → Asks a few interactive questions → Scaffolds your entire project structure → Sets up only the tools you actually want → Wires everything together automatically TypeScript supported now. Python on the way. Code: https://lnkd.in/dJvFfHVm The only thing I repeat is "I should automate this." #BuildInPublic #CLI #TypeScript #DevTools #OpenSource #DeveloperExperience

💻 Build cross-language integrations with ease! Watch the demo of a .NET producer and Python consumer using RabbitMQ transport with NServiceBus. ➡️ https://lnkd.in/dMiCy74u #RabbitMQ #Integration #NServiceBus #Microservices

Here's the thing most developers miss: Claude Code has full terminal access. That's the entire point. It can shell out to wc for accurate token counts (LLMs are terrible at counting). It can use grep, sed, awk for text processing. It can hit APIs, execute Python scripts, deploy to production. It can also rm -rf your entire system if you're not careful with permissions. So the setup isn't optional. It's the foundation. We talked about Claude Code setup and barely opened Claude Code itself yesterday. Because that's how software development works. You build the infrastructure first. #ClaudeCode #DeveloperProductivity #AITools #SoftwareDevelopment

Day 3 of #TDD_Series_Django Most testing frameworks need hours of configuration. Django? Zero setup. Everything is built in. Ready from day one. With Django you get: ✅ Run tests with one command ✅ Separate test database ✅ Auto reset between tests ✅ Test client (no server needed) ✅ Auth simulation out of the box Sounds simple… but it's powerful. Because it enforces one thing: test isolation No shared state. No random failures. No surprises. That’s what makes tests reliable. Tomorrow: the folder structure mistake that makes your tests silently disappear 👀 Do you use Django testing or pytest? 👇 #Python #Django #TDD #WebDevelopment #TDDWithDjango #Day3