Python 3.10 End-of-Life Approaching October 2026

Python’s most popular packages aren’t always the safest ones. 🪦 Some of them are still being downloaded millions of times — even after they’ve reached end-of-life. That means: • No more security patches • No more bug fixes • No maintainer support — ever From libraries that parse untrusted files to tools embedded deep in CI/CD pipelines, these EOL dependencies create a quiet but very real attack surface. Because the risk isn’t just “is there a CVE today?” It’s “what happens when the next one drops — and no one is there to fix it?” Outdated doesn’t always mean unused. And in open source, usage without support is where risk compounds. #Python #OpenSource #AppSec #EOL #SoftwareSecurity #DevSecOps #HeroDevs

🚀 Understanding the Proxy Pattern (Python) The Proxy pattern provides a surrogate or placeholder for another object to control access to it. A proxy acts as an intermediary, controlling access to the real object. This pattern is useful when you want to add security, lazy initialization, or remote access to an object. The proxy can perform additional operations before or after forwarding the request to the real object. This promotes loose coupling and provides a flexible way to control object access. #Python #PythonDev #DataScience #WebDev #professional #career #development

Every #Python developer has a well-worn toolkit. Pandas for data, requests for HTTP, logging when something needs to be logged, print() when you’re debugging, and nobody’s looking. These tools work, and they’re battle-tested for good reason. But the Python Package Index now hosts more than 800,000 projects, and Python Software Foundation keeps the ecosystem growing through grants, infrastructure, and community programs that fund the people building the next generation of libraries. Some of the most useful ones never quite break into the mainstream. Most developers use only a fraction of what’s available, so take a gander at what’s new once in a while. (And sign up for #PyConUS, it starts on May 13th! https://us.pycon.org/2026/) Read more about these libraries like #Rich, #Nuff, #Typer:\ https://lnkd.in/ejw3G5Pf

Python 3.12 Delivers Critical Syntax and Performance Upgrades for Production Systems 📌 Python 3.12 hits production with game-changing syntax, slashing boilerplate and boosting speed-thanks to PEP 695’s sleek type hints, f-string power-ups, and async TaskGroup for smoother concurrency. Whether you’re building scalable backends or refining type-safe code, this update delivers tangible performance gains and cleaner, more expressive Python. 🔗 Read more: https://lnkd.in/dU8h3pJr #Python312 #Pep695 #Fstringgrammar #Typesafety

Advanced Python 2026 (Part 7) is Live: Virtual Environments As your Python projects grow, managing dependencies becomes critical. In Part 7 of the Advanced Python 2026 series, we explore virtual environments—a must-have skill for every serious developer. Key highlights: • Isolating project dependencies • Avoiding version conflicts • Creating clean, reproducible setups • Managing libraries professionally This is how developers ensure their code runs consistently across different systems. If you want to build reliable, production-ready applications, this is a step you can’t skip. Read Part 7 here: https://lnkd.in/ewjUtv-7 #Python #Programming #JMSM #KNKA #SoftwareDevelopment #Developers #TechEducation #CleanCode #DevOps #Python2026

I’ve published my first technical article: a walkthrough of the SOLID principles—with Python examples. It started as “I’ve heard these letters everywhere—what do they actually mean in code?” Turning that into something concrete helped me more than skimming another diagram. In the post I break things down into bite-sized pieces, including: • Single Responsibility: One job per module—easier to reason about and change. • Open/Closed: Extend behavior without rewriting existing code. • Liskov Substitution: Subtypes that don’t break expectations. • Interface Segregation: Small, focused contracts instead of fat interfaces. • Dependency Inversion: Depend on abstractions, not concrete details. Beyond the theory, each section includes short Python snippets so the ideas map to something you can run and tweak—not just memorize. The full post is here: https://lnkd.in/gFXSE4d9 #SoftwareEngineering #SOLID #Python #CleanCode #OOP #DesignPatterns

⚠️ Medium Risk Vulnerability Alert! The Claude SDK for Python has a memory tool path validation race condition that allows sandbox escape. This issue is related to API security and can lead to unrestricted resource consumption. It's been patched in version 0.87.0. Stay safe and keep your systems updated! #ClaudeSDK #Python #APIsecurity #OWASP #CVE2026-34452 https://lnkd.in/g26q6ZAn

Published pytures on crates.io — a small library that lets Rust Futures and Python Coroutines await each other. Came out of a real need: we have an algorithmic trading system in Rust and wanted to script it with async Python. Both sides are poll-based state machines under the hood, so adapting one to the other turned out to be a clean problem. The tricky part was getting the wakeup semantics right so nothing busy-polls unless necessary. The entire public API is two types. BSD-3-Clause. Github: https://lnkd.in/dFT5HBec crates.io: https://lnkd.in/dzzNAgRW #rust #python #async #opensource

Python 3.15 is adding something developers have wanted for years: an immutable dictionary type. In the latest Dev with Serdar, Serdar Yegulalp explains frozendict, a hashable, immutable counterpart to Python's standard dict. Because it can't change after creation, it can be used in places a regular dict simply cannot, including as a key inside another dictionary or as part of a set. If you work with configuration data, cache keys, or any scenario that requires guaranteed immutability in a mapping structure, this is worth understanding before 3.15 ships. #DevwithSerdar #Python

Python 3.15 is adding something developers have wanted for years: an immutable dictionary type. In the latest Dev with Serdar, Serdar Yegulalp explains frozendict, a hashable, immutable counterpart to Python's standard dict. Because it can't change after creation, it can be used in places a regular dict simply cannot, including as a key inside another dictionary or as part of a set. If you work with configuration data, cache keys, or any scenario that requires guaranteed immutability in a mapping structure, this is worth understanding before 3.15 ships. #DevwithSerdar #Python