How PyKitOps simplifies ML workflows with ModelKits

PyKitOps 1.4 is out for my #python lovers. It adds the ability to interact with remote registries to: * Get the kitfile without pulling the whole ModelKit - a great way to check the contents, especially if you want to grab only the model, or just the dataset * Inspect the ModelKit's manifest to check artifact sizes or signing * Delete a remote ModelKit Grab it with pip. You can learn more about PyKitOps from our docs: https://lnkd.in/eF6CdJhj

Day 12 – Organizing Python Code Like a Pro 🧩 Today, I explored how to make Python code more structured and reusable by creating modules and packages. It’s all about keeping things clean, breaking big code into smaller, focused parts that can be imported anywhere. What’s cool is that I practiced this directly in Google Colab, writing real .py files using `%%writefile` and organizing them into folders like a real project structure. I got the task and learning flow from AI (my coding partner 😎), and every day feels like building something bigger step-by-step. #PythonLearning #Day12 #100DaysOfCode #LearningJourney #AIChallenge #Colab

This TPT Release Talk presents the latest highlights Python API, TASMO coverage with Silver and review workflows in detail. Watch the whole presentation here: https://lnkd.in/eC4mTytz 

Understanding ASGI Through FastAPI While learning FastAPI, I came across ASGI and realized it's the key to understanding how modern Python web apps handle asynchronous requests. In this post, I will share what I learned. https://lnkd.in/gzMEezGd

#embedanything 🦀 now supports AWS-S3 bucket 🚀 . That means you can directly use files from an S3 bucket in embedanything. Thanks for your contribution Taradepan R 🤖 Check out the Python example below. 👇

🐍⚡ Stop manually writing requirements.txt — let Python do it for you. I just cleaned up and released AutoRequirements — a tiny, no-dependency Python tool that scans your codebase, finds all imports (including tricky from x import * and aliases), and automatically generates a clean requirements.txt. 💡 Why this matters: No more pip freeze dumping unnecessary packages No more forgetting which dependencies your scripts actually use Works across multiple files, handles aliases, and de-duplicates everything 📦 How it works: python autoreq.py file1.py file2.py # -> generates requirements.txt Your dependencies, clean and ready. 🎯 Perfect for solo devs, hackathon projects, or anyone who loves automation done right. Check it out here 👇 🔗 https://lnkd.in/ev8CfmEK ⭐ Stars = motivation 🍴 Forks = evolution 💬 Feedback = pure gold #Python #OpenSource #DevTools #Automation #Coding #SoloProject #Productivity #100DaysOfCode

FastAPI vs. Flask for a new microservice? For my recent API, I chose FastAPI for the automatic documentation (Swagger/OpenAPI) and inherent async support. Flask is great for simplicity, but FastAPI scales better for I/O bound tasks. Which do you reach for most often and why? #Python #FastAPI #Flask #BackendDevelopment

🚀 When your Python script finally runs perfectly...Yea... That is it!!! You built something cool: maybe a game, a new method, or an automation script. It works flawlessly with your current package versions and Python setup. Now you're ready to push it to GitHub so others can use it exactly like you did. But wait 👀 How can people know which packages (and versions) you used? 👉 You need a requirements.txt file. Just run this in your terminal: pip freeze > requirements.txt 💡 This command lists every installed package and its version and writes them all to a text file. That's the file you'll share in your repo. ✅ Simple. ✅ Reproducible. ✅ Professional. #HowtoPython #AutomationTips #LearnCoding #LifeOfADeveloper #AIProjects

Idempotency Challenge: Helm Charts in CI. We're optimizing our GitOps pipelines, and the non-deterministic nature of helm package is causing issues (new SHA every time!). What are the community's go-to strategies for ensuring that a chart package (.tgz file) is byte-for-byte identical if the source files haven't changed? Are there any clever Python/Go scripts you use to normalize file metadata before packaging? Let's share tips on making Helm builds truly repeatable. #GitOps #CloudNative #Engineering #HelmBestPractices

Day 53 – Why Error Handling Matters in Python Bugs happen. Programs crash. But clean code doesn’t let users see that. That’s why we use error handling to prevent unexpected breakdowns 🧯 try: result = 10 / 0 print(result) except ZeroDivisionError: print("Oops! Can't divide by zero.") 🧠 Output: Oops! Can't divide by zero. 🔹 try → The risky part 🔹 except → What to do if something goes wrong Robust apps = happy users. Handle your errors before they handle you 😄 👉 Ever had a small error break a big project? #Python #ErrorHandling #Debugging #100DaysOfCode