Building a small Django app with help from AI
This tutorial demonstrates how to build a basic Django idea-voting application using AI as an interactive assistant rather than an autonomous developer. It emphasizes using targeted prompts to generate boilerplate, explain error messages, write tests, and catch edge cases like database race conditions while keeping architectural decisions in the developer’s hands.
https://codewithstein.com/building-a-small-django-app-with-help-from-ai/
This tutorial demonstrates how to build a basic Django idea-voting application using AI as an interactive assistant rather than an autonomous developer. It emphasizes using targeted prompts to generate boilerplate, explain error messages, write tests, and catch edge cases like database race conditions while keeping architectural decisions in the developer’s hands.
https://codewithstein.com/building-a-small-django-app-with-help-from-ai/
Codewithstein
Building a small Django app with help from AI | Code With Stein
I've been using AI more and more when I'm programming.
Speculative Decoding: The Art of Guessing Well
Speculative decoding lets smaller models guess several tokens ahead while the larger model verifies them in parallel, reducing LLM inference latency without changing the final sampling distribution. From the acceptance math to Gumbel coupling, EAGLE-3, and multi-token prediction, the piece shows how increasingly sophisticated drafters make those guesses accurate enough to deliver real sp...
https://astralord.github.io/posts/speculative-decoding-the-art-of-guessing-well/
Speculative decoding lets smaller models guess several tokens ahead while the larger model verifies them in parallel, reducing LLM inference latency without changing the final sampling distribution. From the acceptance math to Gumbel coupling, EAGLE-3, and multi-token prediction, the piece shows how increasingly sophisticated drafters make those guesses accurate enough to deliver real sp...
https://astralord.github.io/posts/speculative-decoding-the-art-of-guessing-well/
AstraBlog
Speculative Decoding: The Art of Guessing Well
Large Language Models spend most of their decoding time not computing, but waiting: every new token requires reading all of the model weights from memory, only to multiply them by a single vector. What if the model could check several tokens for the price…
loopinfo: let your for loop know if it is on the first or last item
Python loops do not know where they are. loopinfo adds loop.first, loop.last, loop.index, loop.count, previous, next and more.
https://pypi.org/project/loopinfo/
Python loops do not know where they are. loopinfo adds loop.first, loop.last, loop.index, loop.count, previous, next and more.
https://pypi.org/project/loopinfo/
PyPI
loopinfo
Know where you are in a for-loop: first, last, index, count, previous and next, like Jinja's loop object.
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Quicksand
Quicksand is an async Python API for launching, controlling, snapshotting, and rolling back QEMU virtual machines to provide isolated sandboxes for AI agents without requiring Docker or root privileges.
https://github.com/microsoft/quicksand
Quicksand is an async Python API for launching, controlling, snapshotting, and rolling back QEMU virtual machines to provide isolated sandboxes for AI agents without requiring Docker or root privileges.
https://github.com/microsoft/quicksand
GitHub
GitHub - microsoft/quicksand: Quickly sandbox your AI agent.
Quickly sandbox your AI agent. Contribute to microsoft/quicksand development by creating an account on GitHub.
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Python vs Go: A Practical Comparison for Developers
Python offers a huge ecosystem, especially for AI, data, and scripting, while Go trades some flexibility for faster execution, simpler deployment, and built-in concurrency. This post compares where each language fits best today, including performance, typing, tooling, developer adoption, and why many teams end up using both rather than choosing one outright.
https://blog.jetbrains.com/go/2026/10/13/python-vs-go/
Python offers a huge ecosystem, especially for AI, data, and scripting, while Go trades some flexibility for faster execution, simpler deployment, and built-in concurrency. This post compares where each language fits best today, including performance, typing, tooling, developer adoption, and why many teams end up using both rather than choosing one outright.
https://blog.jetbrains.com/go/2026/10/13/python-vs-go/
The JetBrains Blog
Python vs Go: A Practical Comparison for Developers - The JetBrains Blog
We look at how Python and Go differ, what surveys tell us about the devs who use them, and what interviews say about the trade-offs between them.
BOOTH
A lightweight, zero-dependency Python checkpoint layer for structured LLM output reliability.
https://github.com/Vedantgitbot/booth
A lightweight, zero-dependency Python checkpoint layer for structured LLM output reliability.
https://github.com/Vedantgitbot/booth
GitHub
GitHub - Vedantgitbot/booth: A lightweight, zero-dependency Python checkpoint layer for structured LLM output reliability.
A lightweight, zero-dependency Python checkpoint layer for structured LLM output reliability. - Vedantgitbot/booth
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Python 3.15's best new features
Trey Hunner's opinion on which Python 3.15 features will be most exciting for the average Python user.
https://www.pythonmorsels.com/python315/
Trey Hunner's opinion on which Python 3.15 features will be most exciting for the average Python user.
https://www.pythonmorsels.com/python315/
Pythonmorsels
Python 3.15's best new features
Python 3.15 includes a UTF-8 default encoding, explicit lazy imports, * unpacking in comprehensions, a new sampling profiler, sentinel, frozendict, and more!
How I Found a $90,000 Remote Code Execution Vulnerability in Google
A leaked Flask session signing secret let an attacker forge session cookies containing malicious pickled data, turning OAuth state handling into unauthenticated remote code execution on several Google developer sites. The writeup shows how combiningpicklewith client-controlled session data can turn a secret leak into code execution, and why untrusted data should never cross a pickle dese...
https://simonkoeck.com/writeups/google-devsite-flask-session-pickle-rce
A leaked Flask session signing secret let an attacker forge session cookies containing malicious pickled data, turning OAuth state handling into unauthenticated remote code execution on several Google developer sites. The writeup shows how combiningpicklewith client-controlled session data can turn a secret leak into code execution, and why untrusted data should never cross a pickle dese...
https://simonkoeck.com/writeups/google-devsite-flask-session-pickle-rce
Simon Koeck
How I Found a $90,000 Remote Code Execution Vulnerability in Google | Simon Koeck
A Flask cookie on developers.google.com was signed with a secret it carried inside itself. Pulling that secret out turned a forged session into code execution across Google's developer sites.
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
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
YouTube
Hamza Remmal – Bridging between Scala & Python with GraalVM #ScalaDays
More: https://scaladays.org/sessions/Bridging-between-Scala-Python-with-GraalVM
Speaker: Hamza Remmal
We will present our ongoing work to bridge between Scala 3 (& Kotlin) and Python 3 using GraalVM. We will explain how the interoperability was designed;…
Speaker: Hamza Remmal
We will present our ongoing work to bridge between Scala 3 (& Kotlin) and Python 3 using GraalVM. We will explain how the interoperability was designed;…
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
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
GitHub
GitHub - nautilusbits/retrokit: Headless-Ghidra toolkit for reverse engineering 32-bit DOS and Win32 games (1993-2010): own LE/LX…
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 - nautilusbits/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/
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/
Antonello Fratepietro
How to Build a Decision Model Like Jev
Autoregressive decoding is the wrong tool when software needs a fast, calibrated probability over a fixed set of outcomes. Here is how System-One decision models work from the inside: Hugging Face’s new /v1/systemone endpoint for turning 250+ LLMs and VLMs…
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DeepInfer
DeepInfer is the high-performance inference framework that powers DeepSeek's large-scale production services.
https://github.com/deepseek-ai/DeepInfer
DeepInfer is the high-performance inference framework that powers DeepSeek's large-scale production services.
https://github.com/deepseek-ai/DeepInfer
GitHub
GitHub - deepseek-ai/DeepInfer: DeepInfer: High-performance, large-scale inference framework for DeepSeek models
DeepInfer: High-performance, large-scale inference framework for DeepSeek models - 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/
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/
Codewithstein
How to improve technical SEO on a Django website | Code With Stein
Django gives you a good starting point for SEO because most pages are rendered on the server, but it doesn't automatically handle things like canonical URLs, sitemaps, structured data or duplicate URLs. In this article, I'll go through the technical SEO setup…
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
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
GitHub
GitHub - dbiswas55/vlmhub: A lightweight, config-driven framework for unified vision-language model inference across local and…
A lightweight, config-driven framework for unified vision-language model inference across local and cloud backends, built on LiteLLM and Transformers. - dbiswas55/vlmhub
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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
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
YouTube
7 Python Features That Make Your Code Worse
🧱 Build software that lasts. Join the Software Design Mastery program → https://arjan.codes/mastery.
Python has a lot of powerful features, but just because you can use them doesn’t mean you always should.
In this video, I look at 7 Python features that…
Python has a lot of powerful features, but just because you can use them doesn’t mean you always should.
In this video, I look at 7 Python features that…
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/
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/
adamj.eu
Django: check version support with norwegianblue - Adam Johnson
Django projects end up slotting into a bunch of software release cycles: Django itself, Python, database servers, cache servers, and more. It can be hard for us developers to keep track of all of them, with their different support policies and end-of-life…
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/
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/
Artem Golubin
Python's binary wheels and supply chain attacks
Why precompiled Python wheels are a weak spot in the supply chain security.
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
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
GitHub
GitHub - allstoalls/pcc: compile and eval c & python use python
compile and eval c & python use python. Contribute to allstoalls/pcc development by creating an account on GitHub.
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
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
YouTube
apache iceberg beneath the surface
In Chapter 2 of Data Engineering for ML and AI, we look at how Apache Iceberg turns a folder of Parquet files into a table with ACID transactions, time travel, and schema evolution. We also compare it with Hive tables and Delta Lake.
00:00 Data Warehouses…
00:00 Data Warehouses…