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News & links about Python programming.
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Building a Real-Time HackerNews Trending Topics Detector with CocoIndex

Automatically turn HackerNews into a real-time, AI-powered trending topics feed — always up to date.

https://cocoindex.io/blogs/hackernews-trending-topics
200 Lines of Python beats $50M supercomputer – Navier-Stokes at Re=10⁸ [pdf]

https://philpapers.org/archive/CAMIIA-3.pdf
Building Data Visualisations in Python in Minutes

The video demonstrates how to use Streamlit, a Python framework, to quickly build professional and interactive data visualizations with minimal code, showing live examples involving Pandas for data manipulation and visualization. It highlights Streamlit's simplicity, live reloading, interactivity, and caching features, making it ideal for rapid data exploration and sharing within small u...

https://www.youtube.com/watch?v=lQRq4-MiAGA
Gunicorn Internals

This blog is a technical case of the Gunicorn source code.

https://humbulani1234.github.io/blog/
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Setting up a Django project with Vite, React, and Tailwind CSS

The video demonstrates setting up a modern Django project with Vite for frontend builds: create Django app with UV, configure Vite for JS/CSS bundling to Django's staticfiles, integrate django-vite for HMR dev server.

https://www.youtube.com/watch?v=GztJ1h6ZXA0
AI infrastructure in the "Era of experience"

The article analyzes AI infrastructure needs in the "Era of Experience," where RL-trained models interact with proprietary environments, using GRPO for efficient policy optimization and LoRA adapters to enable low-cost training/inference via multi-tenancy and large-batch async RL. It predicts commoditized base models will spawn a reinforcement fine-tuning (RFT) industry for custom models...

https://www.tensoreconomics.com/p/ai-infrastructure-in-the-era-of-experience
Become an AI Researcher Course – LLM, Math, PyTorch, Neural Networks, Transformers

This comprehensive course on becoming an AI Researcher starts with the foundational mathematics (vectors, derivatives, gradients, matrices) and PyTorch fundamentals necessary for understanding modern AI. It then progresses through the building blocks of neural networks and culminates with an in-depth module on Transformers, the critical technology behind Large Language Models and generat...

https://www.youtube.com/watch?v=wu8npoU37cI
Improve Query Performance Using Python Django QuerySets

The post shows how efficient Django QuerySet usage can significantly improve database performance, reduce latency, and create faster applications. It explains that writing better queries leads to more stable, scalable, and cost-effective Django systems because the ORM can easily generate unnecessary load when used carelessly.

https://blog.appsignal.com/2025/12/03/improve-query-performance-using-django-python-querysets.html
A first look at Django's new background tasks

Django 6.0 introduces django.tasks, a lightweight framework for defining and enqueuing background tasks via a standard API, but lacks built-in workers—requiring external infrastructure like custom database-backed backends. The article builds a demo notification app with a DB backend, worker, retries, and result polling, showing how to implement queuing while noting limitations like no co...

https://roam.be/notes/2025/a-first-look-at-djangos-new-background-tasks/