Scikit-learn 1.9
Scikit-learn 1.9 release is out, and it comes with solid improvements to many existing estimators, making them faster, more stable, handling missing values, adding GPU support… The release also enhances the estimator displays in notebooks, and introduces a callback mechanism that opens the door to progress bars or advanced monitoring of convergence.
https://blog.scikit-learn.org/updates/release-1-9/
Scikit-learn 1.9 release is out, and it comes with solid improvements to many existing estimators, making them faster, more stable, handling missing values, adding GPU support… The release also enhances the estimator displays in notebooks, and introduces a callback mechanism that opens the door to progress bars or advanced monitoring of convergence.
https://blog.scikit-learn.org/updates/release-1-9/
scikit-learn Blog
scikit-learn release 1.9: better numerics, new core functionality
Author: Gael Varoquaux
Plugins case study: Pluggy
The post explains how Pluggy works as a reusable Python library for building plugin systems, centered on hooks that hosts define and plugins implement. It also highlights the design tradeoffs Pluggy handles well, including registration, signature validation, ordering, and hook wrappers, while leaving plugin discovery largely up to the application.
https://eli.thegreenplace.net/2026/plugins-case-study-pluggy/
The post explains how Pluggy works as a reusable Python library for building plugin systems, centered on hooks that hosts define and plugins implement. It also highlights the design tradeoffs Pluggy handles well, including registration, signature validation, ordering, and hook wrappers, while leaving plugin discovery largely up to the application.
https://eli.thegreenplace.net/2026/plugins-case-study-pluggy/
PyData London 26
The videos from PyData London 2026 are now available.
https://www.youtube.com/playlist?list=PLGVZCDnMOq0rFQykYJg7t441AEpN4SszE
The videos from PyData London 2026 are now available.
https://www.youtube.com/playlist?list=PLGVZCDnMOq0rFQykYJg7t441AEpN4SszE
Choosing a Python task queue library in 2026: Celery vs Dramatiq vs FastStream vs Taskiq vs Repid
https://www.reddit.com/r/Python/comments/1u775lo/choosing_a_python_task_queue_library_in_2026/
https://www.reddit.com/r/Python/comments/1u775lo/choosing_a_python_task_queue_library_in_2026/
Reddit
From the Python community on Reddit: Choosing a Python task queue library in 2026: Celery vs Dramatiq vs FastStream vs Taskiq vs…
Explore this post and more from the Python community
defending-code-reference-harness
Skills for threat modeling, scanning, triage, patching, plus an autonomous scanning harness you can customize.
https://github.com/anthropics/defending-code-reference-harness
Skills for threat modeling, scanning, triage, patching, plus an autonomous scanning harness you can customize.
https://github.com/anthropics/defending-code-reference-harness
GitHub
GitHub - anthropics/defending-code-reference-harness: Skills for threat modeling, scanning, triage, patching, plus an autonomous…
Skills for threat modeling, scanning, triage, patching, plus an autonomous scanning harness you can /customize - anthropics/defending-code-reference-harness
tracesage
tracesage adds local, zero-infra tracing to LangChain/LangGraph agents in two lines, it captures every chain, tool, and LLM call to SQLite and shows the run as a live graph and timeline in your browser. Open source, pip install, MIT licensed.
https://github.com/kjgpta/tracesage
tracesage adds local, zero-infra tracing to LangChain/LangGraph agents in two lines, it captures every chain, tool, and LLM call to SQLite and shows the run as a live graph and timeline in your browser. Open source, pip install, MIT licensed.
https://github.com/kjgpta/tracesage
GitHub
GitHub - kjgpta/tracesage
Contribute to kjgpta/tracesage development by creating an account on GitHub.
BugHunter
AI-powered bug bounty hunting from your terminal - recon, 20 vuln classes, autonomous hunting, and report generation. All inside Claude Code.
https://github.com/shuvonsec/claude-bug-bounty
AI-powered bug bounty hunting from your terminal - recon, 20 vuln classes, autonomous hunting, and report generation. All inside Claude Code.
https://github.com/shuvonsec/claude-bug-bounty
GitHub
GitHub - shuvonsec/claude-bug-bounty: AI-powered bug bounty hunting from your terminal - recon, 20 vuln classes, autonomous hunting…
AI-powered bug bounty hunting from your terminal - recon, 20 vuln classes, autonomous hunting, and report generation. All inside Claude Code. - shuvonsec/claude-bug-bounty
Showcasing allauth IdP: build an MCP server
This article demonstrates how to build a Model Context Protocol (MCP) server using Django and django-allauth, with OpenID Connect (OIDC) authentication handled by the allauth.idp package. It shows how MCP hosts such as Claude can dynamically register and authenticate clients without relying on separate third-party identity providers.
https://allauth.org/news/2026/05/idp-demo-mcp-server/
This article demonstrates how to build a Model Context Protocol (MCP) server using Django and django-allauth, with OpenID Connect (OIDC) authentication handled by the allauth.idp package. It shows how MCP hosts such as Claude can dynamically register and authenticate clients without relying on separate third-party identity providers.
https://allauth.org/news/2026/05/idp-demo-mcp-server/
Libraries for your Python Polars workflows
The post highlights a set of Python libraries that work natively with Polars, letting you stay in the Polars ecosystem for validation, tables, visualization, and LLM-assisted analysis.
https://opensource.posit.co/blog/2026-06-04_libraries-for-python-polars/
The post highlights a set of Python libraries that work natively with Polars, letting you stay in the Polars ecosystem for validation, tables, visualization, and LLM-assisted analysis.
https://opensource.posit.co/blog/2026-06-04_libraries-for-python-polars/
Posit Open Source
Libraries for your Python Polars workflows
Posit's Python libraries provide excellent support for Polars DataFrames across your data science workflow.
How I made dependency injection in Python 130× faster: from reflection to compiling the graph
The post shows how a Python dependency injection container was optimized from ~53 µs to 0.40 µs per resolve by caching plans, eliminating unnecessary checks, and compiling dependency graphs into generated code. Along the way, it demonstrates practical performance engineering techniques, including code generation, common-subexpression elimination, fuzz testing, and reproducible benchmarking
https://vshulcz.hashnode.dev/python-dependency-injection-130x-faster
The post shows how a Python dependency injection container was optimized from ~53 µs to 0.40 µs per resolve by caching plans, eliminating unnecessary checks, and compiling dependency graphs into generated code. Along the way, it demonstrates practical performance engineering techniques, including code generation, common-subexpression elimination, fuzz testing, and reproducible benchmarking
https://vshulcz.hashnode.dev/python-dependency-injection-130x-faster
Vlad Shulcz Notes
How I made Python dependency injection 130× faster
How a Python DI container's resolve dropped from ~53 to 0.40 µs/op: plan caching, removing a dead check, and compiling the graph with exec.
How to build your first Scrapy extension
This tutorial uses a simple audio notification plugin to explain how Scrapy extensions work, covering signals, lifecycle hooks, settings, testing, and packaging. It provides a practical introduction to extending Scrapy with custom functionality while showcasing common patterns used across the ecosystem.
https://www.zyte.com/blog/how-to-build-your-first-scrapy-extension/
This tutorial uses a simple audio notification plugin to explain how Scrapy extensions work, covering signals, lifecycle hooks, settings, testing, and packaging. It provides a practical introduction to extending Scrapy with custom functionality while showcasing common patterns used across the ecosystem.
https://www.zyte.com/blog/how-to-build-your-first-scrapy-extension/
Zyte
How to build your first Scrapy extension
My Scrapy project now plays a triumphant fanfare when a crawl finishes clean and a sad trombone when it doesn't, which is also how I finally learned what Scrapy's extension points are actually for.
Array API adoption: what to do with compiled code
The post examines how Array API compatibility and JIT compilation can modernize legacy scientific Python code for GPUs and multicore CPUs. The results suggest developers can achieve significant performance gains across hardware platforms without maintaining specialized accelerator-specific code.
https://labs.quansight.org/blog/array-api-aot-jit
The post examines how Array API compatibility and JIT compilation can modernize legacy scientific Python code for GPUs and multicore CPUs. The results suggest developers can achieve significant performance gains across hardware platforms without maintaining specialized accelerator-specific code.
https://labs.quansight.org/blog/array-api-aot-jit
The Fastest Python Struct?
The article explores the performance tradeoffs of Python's various struct-like types, focusing on startup and type-definition costs rather than runtime business logic. Extensive benchmarks reveal that NamedTuple sits in the middle of the pack, while msgspec and C-backed implementations deliver the fastest type creation and startup times.
https://www.crumpledpaper.tech/2026-06-21-python-struct-profiling/
The article explores the performance tradeoffs of Python's various struct-like types, focusing on startup and type-definition costs rather than runtime business logic. Extensive benchmarks reveal that NamedTuple sits in the middle of the pack, while msgspec and C-backed implementations deliver the fastest type creation and startup times.
https://www.crumpledpaper.tech/2026-06-21-python-struct-profiling/
Crumpled Paper
The Fastest Python Struct?
An adventure in Python struct benchmarking: slotted class, NamedTuple, dataclass, attrs, msgspec, record-type, and a new C extension based on record-type and msgspec. Focus is on import-time, type-construction, memory, and instantiation cost, NOT DE/SERIALIZATION…
Write a coding agent from first principles
This tutorial will show you how to create your own coding agent from first principles. By doing so, you'll understand how coding agents work under the hood.
https://mathspp.com/blog/write-a-coding-agent-from-first-principles
This tutorial will show you how to create your own coding agent from first principles. By doing so, you'll understand how coding agents work under the hood.
https://mathspp.com/blog/write-a-coding-agent-from-first-principles
Mathspp
Write a coding agent from first principles
Learn how to write a coding agent in this Python tutorial that teaches how to interact with an LLM through an API, how to manage the conversation context,...
PixelRAG
PixelRAG replaces traditional text-based web RAG with a pixel-native approach that retrieves and reasons over webpage screenshots. By preserving visual structure and using vision-language models, it aims to improve retrieval accuracy and web understanding.
https://github.com/StarTrail-org/PixelRAG
PixelRAG replaces traditional text-based web RAG with a pixel-native approach that retrieves and reasons over webpage screenshots. By preserving visual structure and using vision-language models, it aims to improve retrieval accuracy and web understanding.
https://github.com/StarTrail-org/PixelRAG
GitHub
GitHub - StarTrail-org/PixelRAG: The end of web parsing. The beginning of scalable pixel-native search. link: https://pixelrag.ai/
The end of web parsing. The beginning of scalable pixel-native search. link: https://pixelrag.ai/ - StarTrail-org/PixelRAG
Wagtail as Django admin on steroids
Wagtail can be used as a drop-in replacement for Django Admin, providing a more polished UI and powerful customization capabilities. The article demonstrates how developers can adopt Wagtail incrementally while retaining their existing Django architecture.
https://timonweb.com/wagtail/wagtail-as-django-admin-on-steroids/
Wagtail can be used as a drop-in replacement for Django Admin, providing a more polished UI and powerful customization capabilities. The article demonstrates how developers can adopt Wagtail incrementally while retaining their existing Django architecture.
https://timonweb.com/wagtail/wagtail-as-django-admin-on-steroids/
timonweb.com
Wagtail as Django admin on steroids
Discover how Wagtail transforms Django admin into a sleek, user-friendly interface with powerful features and easy customization.
NVlabs / Eagle
Eagle: Frontier Vision-Language Models with Data-Centric Strategies
https://github.com/NVlabs/Eagle
Eagle: Frontier Vision-Language Models with Data-Centric Strategies
https://github.com/NVlabs/Eagle
GitHub
GitHub - NVlabs/Eagle: Eagle: Frontier Vision-Language Models with Data-Centric Strategies
Eagle: Frontier Vision-Language Models with Data-Centric Strategies - NVlabs/Eagle
Optocam Zero
Optocam Zero is a Raspberry Pi Zero based compact digital camera made using off the shelf components.
https://github.com/dorukkumkumoglu/optocamzero
Optocam Zero is a Raspberry Pi Zero based compact digital camera made using off the shelf components.
https://github.com/dorukkumkumoglu/optocamzero
GitHub
GitHub - dorukkumkumoglu/optocamzero: Optocam Zero is a Raspberry Pi Zero based compact digital camera made using off the shelf…
Optocam Zero is a Raspberry Pi Zero based compact digital camera made using off the shelf components. - dorukkumkumoglu/optocamzero