In this tutorial, we implement a practical use case with Loguru, a powerful, flexible, and production-ready logging library for Python. We start by building a clean, idempotent logging setup that can ...

OpenCV-video-multiprocessing is a small educational project that demonstrates how to process video frames faster and more cleanly using OpenCV, Python worker pools, and a frame queue. The repository ...

In this tutorial, we demonstrate how to use the UAgents framework to build a lightweight, event-driven AI agent architecture on top of Google’s Gemini API. We’ll start by applying nest_asyncio to ...

But in many cases, it doesn’t have to be an either/or proposition. Properly optimized, Python applications can run with surprising speed—perhaps not as fast as Java or C, but fast enough for web ...

Hello! I'm a dreamer focusing on high-load distributed systems and low-level engineering. I mainly code in Rust and Python This article focuses on pitfalls, solutions, and my findings with regard to ...

Optimized apps and websites start with well-built code. The truth, however, is that you don't need to worry about performance in 90% of your code, and probably 100% for many scripts. It doesn't matter ...

Learn how to use Python’s async functions, threads, and multiprocessing capabilities to juggle tasks and improve the responsiveness of your applications. If you program in Python, you have most likely ...

Climate forecasts, both experimental and operational, are often made by calibrating Global Climate Model (GCM) outputs with observed climate variables using statistical and machine learning models.