PostgreSQL Password Security in Python Backend Development

If you’re working with MariaDB with Python for CRUD ops, this walkthrough is a solid place to start. #MariaDB #MySQL #Python #CRUD #Database #OpenSource #LAMP #DevOps #SysAdmin #Backend #MariaDBFoundation #PostgreSQL https://lnkd.in/gVqdKdDJ

The very beginnings of a pure python library for MPI. Other libraries already exist, but they are overcomplicated for someone who "just wants to run it". https://lnkd.in/epx2a-Rh

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.

📅 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

Solving these SQL questions on LeetCode is actually fun. In a couple of my recent projects, I actually stumbled upon cases where the ORM (fancy word for a database client) couldn't help, and I had to step in and write a row query. Only then did I realize that solving these LeetCode questions is not a total waste of time.

AWS stopped patching the Python 3.9 Lambda runtime on December 15, 2025. If you're still running python3.9 functions, they're exposed right now. Hard deadline: September 30, 2026. After that, you're locked out of function updates entirely. The real challenge isn't knowing you need to upgrade - it's finding every affected function scattered across dozens of accounts and regions. And Python 3.9 isn't the only one. Python 3.8, Node.js 18.x, and .NET 6 are all running unpatched too. We put together a walkthrough to help you assess your exposure, prioritize by actual risk, and plan your migration before the deadlines hit. https://lnkd.in/gp7ua8rK

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....

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

Those who are amazed by LLMs ability to code should ask it to generate SPARQL queries to query DBPedia. You can try the results in DBPedia SPARQL editor. Yes, there may be million times more Python codes than SPARQL queries available for LLMs to learn from, one must wonder: if these models are genuinely intelligent, shouldn't they have mastered SPARQL by now?

Have you tried using PyO3? It is a library that helps integrate Rust with Python. It allows you to either expose Rust code as a Python extension module or embed the Python interpreter directly into a Rust application. A common usecase is when you have built your application in Python and start running into bottlenecks. Because Python being a dynamically typed interpreted language running on the GIL, has inherent performance limitations. I am sure some of you out there have already ran into it. Rust can give you a significant uplift here. Rather than rewriting the entire program, you profile your Python application, rewrite the hot paths in Rust, compile it as a native extension, and let the Python interpreter consume it seamlessly. Libraries like Polars and Pydantic V2 are great real-world examples of this pattern. In HFT systems built in Rust, the usecase flips. You want the strategies and algorithms written in Python because they are easier to iterate on, backtest, and hand off to quants. But the execution layer needs to be fast and deterministic which is happening in microseconds. Here you embed the Python interpreter into the Rust binary, load your core algorithm logic at runtime, and let the Rust runtime drive execution while calling into Python only when needed. It's fun to do this! PyO3 paired with Maturin (for build tooling) makes both of these workflows surprisingly ergonomic. How effectively have you used PyO3 in your projects or organizations? . . . . #rust #python #pyo3 #HFT #programming