Rust vs Python Performance: Rust Agents Outperform

Python 3.14t Launches with No-GIL Support as TypeScript Remains Top on GitHub Octoverse 📌 Python 3.14t launches with No-GIL support, enabling true multi-core performance for AI and scientific computing-marking a major leap for Python’s speed and scalability. Meanwhile, TypeScript remains the top language on GitHub, driving demand for stricter typing and WebAssembly solutions to bring Python to the web. 🔗 Read more: https://lnkd.in/dhdnV42J #Python314t #Nogil #Cpython #Pep703 #Githuboctoverse

😵 Thread-local storage works great... until you move to async. Then the weird stuff starts. Request IDs bleeding between coroutines. Background tasks sharing state. “Random” bugs that disappear under logging. Sound familiar? Async doesn’t care about threads. It cares about execution context. In my latest article I explain: 🔍 Why threading.local() fails under asyncio 🧠 How ContextVars isolate state per coroutine ⚙️ Real examples with async tasks and request-scoped data 👉 https://lnkd.in/d_aVTDtW #python #softwaredevelopment #backend #engineering #asyncio

Just published on QuantLabsNet: Death of Proprietary Platforms — How to Build an AI Trading Bot in Python for IBKR. This post explains why proprietary scripting languages are fading and shows how to design broker-agnostic systems with Python, practical examples, and deployment guidance. Read more: https://wix.to/3tcb7aY #AlgoTrading #Fintech #Python #IBKR #QuantFinance #TradingEngineering

New alpha of Python 3.15 just dropped, and there's a measurable speedup (especially with the JIT on, and ESPECIALLY in the free-threaded build) over previous point releases and even alphas of 3.15. Biased as I might be for saying this, I'm convinced Python's existing presence and continued improvement -- not just in speed but also in tooling, both first- and third-party -- will let it prevail over those positioned as challengers to its throne: Julia, Mojo, etc. As for Rust, it's fast becoming a companion to Python as much as any potential replacement. Yes, you're still going to pick Rust where it makes technological sense, but plenty of scenarios still exist where Rust runs hand-in-hand with Python rather than eclipsing it.

I've just ported Andrej Karpathy's minimalist Micro-GPT python implementation https://lnkd.in/dSVB3Chy to Rust. It’s definitely not the most efficient way to train a model, but it’s the best way to see how the "math" actually becomes "intelligence." It's essentially the "Long Way Round" to building a Language Model, and it was a fantastic exercise in Rust. Repo: https://lnkd.in/drDYibe9 #AI #Rust #DeepLearning

SpiderRock was recently referenced in an article published in AI Advances, Build a Real-Time Options Dashboard in an Afternoon with Python. In the piece, author Nikhil Adithyan walks through how to build a streamlined options dashboard using Python and modern developer frameworks. As part of the tutorial, SpiderRock’s MLink API is used to source live options data, showing how real-time chains, implied metrics, and Greeks can be integrated into a simple, responsive interface. It’s a practical example of how clean, structured derivatives data can accelerate analytics builds without heavy infrastructure. Learn more and read the full article below. https://lnkd.in/gM_FPSkN #OptionsData #MarketData #Derivatives #QuantitativeFinance #SpiderRock

Excited to share my latest project: Rule-Based Expert System! This is a Python-based rule system that recommends project ideas based on user interest and skill level. It demonstrates basic conditional logic and beginner-friendly decision-making in Python. Features: - Takes user input (domain & skill level) - Suggests relevant project ideas - Simple and interactive Check it out on my GitHub: https://lnkd.in/gvPRKg7M #Python #AI #MachineLearning #RuleBasedSystem #Project #Coding

 Why Python remembers things after a function is done (code screenshot below) db_connector has finished execution. Its stack frame is gone. Yet connect still remembers host and port. That preserved state is a closure — created automatically when an inner function captures outer scope. You don’t “use closures” explicitly. You design around them. Why this matters: • avoids globals   • keeps config scoped   • cleaner APIs   • safer state Closures aren’t a trick. They’re how Python naturally models state + behavior. Once you notice this, patterns such as DB clients, API wrappers, and rate limiters become obvious. #Python   #SoftwareEngineering   #BackendDevelopment  

Python Tip: With Statement The 'with Statement' Is More Than Syntax Most developers see 'with' as a shortcut for opening files. It’s not. It’s Python’s way of guaranteeing clean resource management, automatically and safely. No forgotten .close() No hidden leaks No fragile cleanup logic That’s the real shift from old to modern Python: Old mindset -> “Remember to clean up.” Modern mindset -> “Design so cleanup is automatic.” 'with' isn’t just cleaner code. It’s safer architecture. FOLLOW FOR MORE PYHON TIPS & INSIGHTS #Python #CleanCode #SoftwareEngineering #ProgrammingTips