Bridging between Scala & Python with GraalVM

This talk explores using GraalVM to enable seamless interoperability between Scala 3 and Python 3 code, focusing on generating idiomatic Scala facades for Python libraries. It details strategies for handling dynamic Python concepts, such as type hints, structural typing, and decorators, within the static and nominal type system of Scala.

https://www.youtube.com/watch?v=EnEVtmbr-uM

retro-kit

Headless-Ghidra toolkit for reverse engineering 32-bit DOS and Win32 games (1993-2010): own LE/LX loader, Watcom calling conventions, library signatures, MCP server

https://github.com/nemo22/retrokit

How to Build a Decision Model Like Jev

Learn how to build AI decision models that return calibrated probabilities for classification, scoring, and routing tasks without generating text, using Hugging Face Transformers and the /v1/systemone API. The guide covers custom option tokens, model fine-tuning, probability calibration, and tree batching to improve accuracy, reduce latency, and lower inference costs.

https://www.fratepietro.com/2026/how-to-build-a-decision-model-like-jev/

DeepInfer

DeepInfer is the high-performance inference framework that powers DeepSeek's large-scale production services.

https://github.com/deepseek-ai/DeepInfer

How to improve technical SEO on a Django website

Learn how to improve technical SEO in Django applications by implementing canonical URLs, XML sitemaps, robots.txt, structured data, and proper redirects. The guide includes practical Django code examples for controlling search engine indexing, preventing duplicate content, optimizing page performance, and monitoring results with Google Search Console.

https://codewithstein.com/improve-technical-seo-django/

vlmhub

A lightweight, config-driven framework for unified vision-language model inference across local and cloud backends, built on LiteLLM and Transformers.

https://github.com/dbiswas55/vlmhub

Popular Python Features You Probably Shouldn’t Use

Explore seven powerful Python features, including properties, dataclasses, caching, decorators, async, pattern matching, and slots, that can make code harder to understand and maintain when misused. Learn the trade-offs of each feature and when using it improves code clarity, design, and maintainability.

https://www.youtube.com/watch?v=RHCyTWaRZSk

Django: check version support with norwegianblue

Adam Johnson demonstrates how to use norwegianblue, a command-line tool powered by endoflife.date, to check release cycles and support deadlines for Django, Python, PostgreSQL, and other software. The tool displays version compatibility, end-of-life dates, and upcoming support deadlines in a color-coded table, helping developers identify unsupported versions and plan upgrades.

https://adamj.eu/tech/2026/10/16/django-norwegianblue/

Python's binary wheels and supply chain attacks

Artem Golubin highlights a supply chain security risk in Python's packaging ecosystem: binary wheels uploaded to PyPI can contain malicious code that differs from their accompanying source distributions. Since most security scanners focus on source code rather than compiled binaries, attackers could hide malware in prebuilt wheels that pip installs by default.

https://rushter.com/blog/python-binary-wheels/

Write Python, Run native, All in Python.

PCC compiles Python and C source into native programs. This compiler and runtime aims to preserve Python's syntax and behavior without libpython, with self-hosting。

https://github.com/allstoalls/pcc

apache iceberg beneath the surface

A video tutorial on how Apache Iceberg's manifests, snapshots, and catalog turn a folder of Parquet files into a table with ACID transactions, hidden partitioning, time travel, and schema evolution. Tutorial uses the data on NYC taxi trips along with PyIceberg, Polars, and DuckDB.

https://www.youtube.com/watch?v=9Fz5noobWcE

Build an AI That Turns Your Voice Into Images, Video and Audio (Python)

This video demonstrates how to build a Python AI agent that automates the entire video creation pipeline, including speech-to-text, scriptwriting, image generation, voice synthesis, and video rendering. By using OpenRouter as a unified API, the project shows how to integrate multiple AI models efficiently while tracking individual operation costs.

https://www.youtube.com/watch?v=aypkvuGFq5Y

Bringing uv and ty together

Astral introduces experimental integration between uv and ty, enabling dependency-aware type checking for Python scripts with PEP 723 inline metadata and a new uv check command that automatically prepares project environments and runs ty. The integration also supports workspace-wide type checking and consistent ty versions through uv's lockfile, bringing Python development tools closer t...

https://astral.sh/blog/uv-ty-integration

llm-d

State of the art inference performance with modern accelerators on Kubernetes

https://github.com/llm-d/llm-d

TutorLoom

TutorLoom is an open-source, self-hosted learning management system built with Django, React, and Flutter, featuring course management, quizzes, grading, progress tracking, and multi-tenant support.

https://github.com/pacewisdomhq/TutorLoom

How to Run Turing-Complete Malware in PyTorch's Backward Pass

Elon Litman demonstrates how a malicious PyTorch loss function can report a value of zero while secretly manipulating model weights through the backward pass. By exploiting differences between floating-point arithmetic and automatic differentiation, he shows how gradient descent can execute arbitrary computations inside a neural network, creating a potential attack vector for AI training...

https://elonlit.com/scrivings/how-to-run-turing-complete-malware-in-pytorchs-backward-pass/

lightseekorg / tokenspeed

TokenSpeed is a speed-of-light LLM inference engine.

https://github.com/lightseekorg/tokenspeed