Upgrade AWS Lambda Runtimes by September 30, 2026

Perhaps you've seen that uvx command in your MCP server configs and wondered what it does. It's shorthand for uv tool run. uv is a single Rust binary that replaces your entire Python toolchain — pyenv, virtualenv, pip-tools, Poetry, all of it. uvx runs any package in its own throwaway environment, which is exactly why MCP configs use it. Since I switched, versioning issues are gone and my Python setup is simpler than it's ever been. Here's the full story: 👉 https://lnkd.in/epFEYRBC

🚀 Python 3.14 — Back to the Interpreter. Back to the Basics. Today I went back to where everything starts: An Informal Introduction to Python. https://lnkd.in/d4NN7cmG # Launch Python 3.14 explicitly (Windows launcher) C:\Users\John> py -3.14 # This is a comment → ignored by Python # Remember. This is a comment. # This is NOT a comment because it's inside quotes text = "# This is not a comment." # Addition 7 + 4 # Subtraction 50 - 37 # Order of operations (multiplication first) (100 - 5 * 7) # True division → float 17 / 3 # Floor division → integer 17 // 3 # Modulo → remainder 17 % 3 # Exponentiation 2 ** 10 # Store resolution values width = 1920 height = 1080 # Calculate total pixels (Full HD) width * height 💥 Fail Fast # Access undefined variable size → NameError 🔁 REPL Superpower: _ # `_` holds the last result in interactive mode width - _ 🎯 My Take Deep systems aren’t built on complexity. They’re built on mastery of fundamentals. Whether you’re building: A Django backend A distributed system An AI-powered application It all starts here — with clean thinking. “If you want to fly high, take a deep dive.” #Python #Django #Backend #SoftwareDevelopment #DeepDive

🤔 Flask vs FastAPI: Which Python framework should you choose in 2024? After building APIs with both frameworks, here's my honest breakdown: 🐍 Flask - The Veteran: • Mature ecosystem with tons of resources • Complete flexibility and control • Perfect for complex, custom architectures • Steeper learning curve for beginners ⚡ FastAPI - The Speed Demon: • Built-in async support for high performance • Automatic API documentation with Swagger • Type hints make code more maintainable • Modern Python features out of the box My take: FastAPI wins for new projects requiring speed and modern features. Flask remains king for legacy systems and when you need maximum customization. The real winner? Learning both! Each has its place in different scenarios. What's your experience? Are you team Flask or FastAPI? Share your thoughts below! 👇 #Python #WebDevelopment #API #Flask #FastAPI #Programming #TechTips #SoftwareDevelopment #Coding

📅 Day 12/30 – Requests Module in Python Today I learned how to use the Requests module to send HTTP requests and interact with APIs. What I covered: • Installing the requests library • Sending GET and POST requests • Handling response objects • Working with JSON data • Checking status codes • Basic API integration Understanding how Python communicates with web services is powerful 💪 📚 Learning resource: HackerBytez – https://lnkd.in/gzKTANVt Step by step, moving closer to real-world application development 🚀 #Day12 #PythonChallenge #30DaysOfPython #RequestsModule #Python #APIs #LearningInPublic #CodingJourney

I almost rewrote my entire Python backend in Rust this weekend. The problem: generating 300 API calls through Claude was taking 5 hours. One at a time, 60 seconds each. Sequential. Painful. I started researching multithreading. Connection pools. Async Python. Rate limit management. Retry queues. Then I found Anthropic's Batch API. You submit all your requests in one call — up to 10,000 at once. Anthropic handles the parallelism, the rate limits, the infrastructure. You get results back within an hour. And it costs 50% less than standard API pricing. My entire pipeline went from this: 1. Manage threads 2. Handle rate limits 3. Retry failures 4. Monitor progress 5. Pray nothing crashes To this: 1. Submit batch 2. Save the batch ID 3. Go make coffee or take a nap 4. Come back and download results If my script dies mid-wait? Doesn't matter. The batch lives on Anthropic's servers. Grab the ID, check back later. Results stay available for 29 days. Stack prompt caching on top and costs drop even further. No Rust. No async. No infrastructure. Just one API call I didn't know about. The lesson: before you optimize your code, read the docs. The answer might already be built.

« The lesson: before you optimize your code, read the docs. The answer might already be built » Worth a read! (🙋🏻♂️ btw PgCache has docs! If you’re running postgres in the cloud it’ll 3-8x your qps: https://lnkd.in/ejM6g6_w)

FastAPI with SQLAlchemy: A Comprehensive Guide for Beginners Building robust and scalable APIs often involves interacting with databases. SQLAlchemy is a powerful and flexible Python SQL toolkit and Object-Relational Mapper (ORM) that allows you to interact with various databases using Python code. FastAPI, known for its speed and ease of use, pairs perfectly with SQLAlchemy, providing a streamlined experience for building data-driven applications. This tutorial will guide you through the process of integrating SQLAlchemy with FastAPI, equipping you with the knowledge to create and manage database-backed APIs....

TinyDB: A Lightweight JSON Database for Small Projects From https://lnkd.in/e_7bMpvu If you're looking for a JSON document-oriented database that requires no configuration for your Python project, TinyDB could be exactly what you need.

For anyone that migrated from #TwosApp to #Obsidian or just wants to include their TwosApp notes in Obsidian, I created this #Python utility to export a TwosApp markdown export into individual markdown files that follow the standard YYYY-MM-DD date format filename convention. You can find the repo for this at... https://lnkd.in/ep9E8xCF You don't have to download the entire repo, just the Python file. I strongly recommend exporting the files into their own subfolder, not your Daily Notes folder. But that's up to you. #OpenSource #GitHub