Python in Real Systems: Scalable and Observable

Stop shipping massive, bloated Python containers. 🐳🐍 As a DevOps engineer, one of the easiest wins for performance and security is optimizing your FastAPI Dockerfiles. Moving from a single-stage "heavy" build to a multi-stage workflow isn't just about saving disk space—it’s about: ✅ Security: Removing compilers, pip, and OS packages in the final image. ✅ Speed: Faster CI/CD pipelines and quicker scaling during deployments. ✅ Efficiency: Using non-root users and slim base images to reduce the attack surface. Check out this breakdown: 1.2 GB (Bad) ➡️ 150 MB (Good) How are you optimizing your Python builds? Let's discuss in the comments! 👇 #DevOps #Docker #Python #FastAPI #CloudNative #ProgrammingTips

Python Reimplementation of Claude Code Agent Now Available for Local Models 📌 Claw Code Agent lets devs run Claude-style coding agents locally-no cloud subscription needed. Built in pure Python, it strips away enterprise bloat for lean, open-source control over tool calls, file edits, and shell commands. Perfect for Python engineers wanting to experiment with agentic workflows using local models like Qwen3-Coder. 🔗 Read more: https://lnkd.in/d7SNVJ4f #Python #Claudecodeagent #Clawcodeagent #Localmodels #Opensource

Architecture for Python applications with FastAPI Building scalable Python applications? Here’s a modern architecture using FastAPI that every developer should know 💡 From frontend to deployment, this architecture ensures: ✅ High performance APIs ✅ Clean separation of concerns ✅ Scalable microservices design ✅ Secure authentication with JWT ✅ Async background processing ⚙️ Tech Stack Highlights: API Layer: FastAPI Backend: Python (Service-based architecture) Database: PostgreSQL / MongoDB Background Jobs: Celery + Redis Deployment: Docker & Kubernetes 💭 Whether you're building startups, SaaS products, or AI systems — this architecture can handle it all. #FastAPI #PythonDeveloper #BackendDevelopment #SoftwareArchitecture #SystemDesign #APIDevelopment #Microservices #Docker #Kubernetes #FullStackDeveloper #AIEngineering #TechArchitecture #CodingLife #DevelopersIndia #StartupTech #Programming #WebDevelopment #ScalableSystems #LearnToCode #TechInnovation

Built a live stock analysis dashboard from scratch using Python, Streamlit & Plotly. Features: Candlestick charts with SMA/EMA/RSI Portfolio tracker with P&L & allocation Live news feed per ticker Deployed on Streamlit Cloud → https://lnkd.in/ddR-gVps #Python #DataScience #Streamlit #FinTech

Built a small real-time notification system this week using Python, IMAP, and Discord webhooks. The goal was simple — stop manually checking for updates and instead have clean, structured alerts delivered instantly. It pulls in incoming data, processes it, and pushes formatted notifications in real time. Deployed it to the cloud so it runs continuously without any manual effort. Tech stack was straightforward: • Python for processing and logic • IMAP for ingestion • BeautifulSoup for parsing • Discord webhooks for output • Cloud deployment for 24/7 uptime Nothing overly complex, but it’s a good example of how a lightweight system can plug directly into a workflow and improve visibility immediately. Sometimes the most valuable builds aren’t the biggest ones — they’re the ones that remove friction. Keep Building. #Python #Automation #APIs #Engineering #BuildInPublic

## **6. Python** Python has emerged as one of the most versatile programming languages in the tech industry. Its simplicity, readability, and vast ecosystem make it a favorite among developers. From web development to data science, automation, and DevOps, Python is everywhere. Frameworks like Django and Flask power web applications, while libraries like Pandas and NumPy drive data analysis. One of Python’s biggest strengths is its ease of learning. Developers can quickly write clean and maintainable code, making it ideal for both beginners and experienced engineers. In DevOps, Python is widely used for automation. Tasks like infrastructure provisioning, log analysis, and monitoring integrations become much easier with Python scripts. Python also plays a crucial role in AI and machine learning. Libraries like TensorFlow and PyTorch have made it the go-to language for building intelligent systems. Another advantage is its strong community support. With thousands of libraries and frameworks available, developers can solve problems efficiently without reinventing the wheel. Python continues to evolve, adapting to modern development needs. Its versatility and efficiency ensure it remains a key skill for any tech professional. #Python #Programming #Automation #DataScience #AI #MachineLearning #DevOps #Coding

Stop fighting with Docker and timeout limits just to run a simple Python script in your n8n or Zapier workflows. Visual automation tools are incredible, but the moment you need a heavy Python package like pandas or BeautifulSoup, you usually hit a wall. Suddenly, you are spending hours configuring environments instead of building workflows. That is exactly why V-RUN was created. It is a serverless Python engine built specifically to remove DevOps friction from automations. We’ve designed a workflow that feels like magic: 1️⃣ Write your Python code in V-RUN (or let our AI agent - V-Dev write it for you). 2️⃣ Click "Copy to n8n". 3️⃣ Hit Ctrl+V in your n8n canvas. It instantly drops a fully configured HTTP Request Node into your workspace. All the heavy lifting and pip install dependency management happens in the cloud, and your workflow simply receives the clean JSON data. Zero infrastructure setup. Just copy, paste, and run. Try the platform directly here: https://lnkd.in/gS_jB6Qb Demo: https://lnkd.in/gqxi28na Let me know what workflows you are automating! 👇 #n8n #Automation #Python #DevOps #Productivity #NoCode #WebScraping

You don't need an API key to run AI from Python. Two tools - uv for dependency management - ollama for model management One file - a simple Python script No extras - no Docker - no venv - no cloud bill Here is a quick setup I use for local LLM projects. Swipe to see it. Link in comments. #Python #LocalAI #Ollama #DeveloperTools #AI

🐍📈 DevOps With Python — With this learning path you'll sample a variety of skills and technologies that any DevOps engineer working with Python should know #python #learnpython

🚀 Starting My Python Journey for Cloud Support Why Python? ✔ Automate repetitive tasks ✔ Handle logs & files ✔ Work with APIs Goal: Use Python to solve real cloud problems. #Python #CloudSupport #Learning