What Every Python Developer Should Know About the CPython ABI
https://labs.quansight.org/blog/python-abi-abi3t
https://labs.quansight.org/blog/python-abi-abi3t
🤯1
ProtoLink
Build autonomous Python agents with native Agent-to-Agent (A2A) communication.
https://github.com/nMaroulis/protolink
Build autonomous Python agents with native Agent-to-Agent (A2A) communication.
https://github.com/nMaroulis/protolink
GitHub
GitHub - nMaroulis/protolink: Build autonomous Python agents with native Agent-to-Agent (A2A) communication
Build autonomous Python agents with native Agent-to-Agent (A2A) communication - nMaroulis/protolink
tempolocus
Tempolocus is a time-series activity patterns and approximate location inference
https://github.com/ail-project/tempolocus
Tempolocus is a time-series activity patterns and approximate location inference
https://github.com/ail-project/tempolocus
GitHub
GitHub - ail-project/tempolocus: Tempolocus is a time-series activity patterns and approximate location inference
Tempolocus is a time-series activity patterns and approximate location inference - ail-project/tempolocus
Ban commits/transactions using AST analysis and linters
The post explains why database commits and transactions should be owned only by the DB access layer, because hidden commits and leaking DB models can silently break atomicity or lose data. It shows how to enforce those boundaries with AST tests, flake8 rules, and a narrow LLM review step to catch DB models being returned where domain models should be used.
https://www.droppedasbaby.com/posts/db-commits/
The post explains why database commits and transactions should be owned only by the DB access layer, because hidden commits and leaking DB models can silently break atomicity or lose data. It shows how to enforce those boundaries with AST tests, flake8 rules, and a narrow LLM review step to catch DB models being returned where domain models should be used.
https://www.droppedasbaby.com/posts/db-commits/
droppedasbaby - engineering blog | home of swe word vomit
Stop fucking around with database commits and transactions
A stray commit buried multiple levels deep cost me months. Why the DB layer must own every commit and transaction plus how to enforce these rules using AST and linters.
Ossie
Apache Ossie is a vendor-neutral standard for sharing semantic metadata across analytics, AI, and BI tools. Its goal is to define metrics and business meaning once, then reuse them everywhere.
https://github.com/apache/ossie
Apache Ossie is a vendor-neutral standard for sharing semantic metadata across analytics, AI, and BI tools. Its goal is to define metrics and business meaning once, then reuse them everywhere.
https://github.com/apache/ossie
GitHub
GitHub - apache/ossie: Apache Ossie, industry wide specification effort to standardize how we exchange semantic metadata across…
Apache Ossie, industry wide specification effort to standardize how we exchange semantic metadata across analytics, AI and BI platforms, providing a vendor neutral, single source of truth for seman...
👎1
yifanfeng97 / Hyper-Extract
Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.
https://github.com/yifanfeng97/Hyper-Extract
Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.
https://github.com/yifanfeng97/Hyper-Extract
GitHub
GitHub - yifanfeng97/Hyper-Extract: Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs.…
Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command. - yifanfeng97/Hyper-Extract
👌1
Python 3.15’s Ultra-Low Overhead Interpreter Profiling Mode
The post explains how CPython 3.15’s JIT uses a low-overhead interpreter profiling mode based on swapping dispatch tables instead of running a separate profiling interpreter or adding branches to the normal interpreter. It shows how this “dual dispatch” design lets Python record execution traces for JIT compilation with much lower overhead, while raising the tradeoff between performance ...
https://fidget-spinner.github.io/posts/ultra-fast-tracing.html
The post explains how CPython 3.15’s JIT uses a low-overhead interpreter profiling mode based on swapping dispatch tables instead of running a separate profiling interpreter or adding branches to the normal interpreter. It shows how this “dual dispatch” design lets Python record execution traces for JIT compilation with much lower overhead, while raising the tradeoff between performance ...
https://fidget-spinner.github.io/posts/ultra-fast-tracing.html
Ken Jin’s Blog
Python 3.15’s Ultra-Low Overhead Interpreter Profiling Mode
⚡2
Lucen a Python compiler that parallelizes for-loops via comment pragmas
https://github.com/fcmv/lucen
https://github.com/fcmv/lucen
GitHub
GitHub - fcmv/lucen: Parallelize Python loops by adding two comments - and it's guaranteed bit-identical to running sequentially.…
Parallelize Python loops by adding two comments - and it's guaranteed bit-identical to running sequentially. Same floats, same order. No rewrite, no locks, no wrong answers. - fcmv/lucen
❤2
In-House LLM Serving at Netflix
Netflix built an in-house LLM serving platform using vLLM and NVIDIA Triton, integrating self-hosted models into its existing production infrastructure through unified gRPC and OpenAI-compatible APIs. The article details production lessons around model packaging, version compatibility, zero-downtime deployments, observability, and scaling constrained decoding by moving bottlenecks from s...
https://netflixtechblog.com/in-house-llm-serving-at-netflix-a5a8e799ea2c
Netflix built an in-house LLM serving platform using vLLM and NVIDIA Triton, integrating self-hosted models into its existing production infrastructure through unified gRPC and OpenAI-compatible APIs. The article details production lessons around model packaging, version compatibility, zero-downtime deployments, observability, and scaling constrained decoding by moving bottlenecks from s...
https://netflixtechblog.com/in-house-llm-serving-at-netflix-a5a8e799ea2c
Medium
In-House LLM Serving at Netflix
By AI Platform’s Model Runtime team and Inference team
google / agents-cli
The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying AI agents on Google Cloud.
https://github.com/google/agents-cli
The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying AI agents on Google Cloud.
https://github.com/google/agents-cli
GitHub
GitHub - google/agents-cli: The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying…
The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying AI agents on Google Cloud. - google/agents-cli
Reusable scenario based test framework
Write your tests once. Run them on every product variant, device or technology — without rewriting a single line.
https://github.com/balder-dev/balder
Write your tests once. Run them on every product variant, device or technology — without rewriting a single line.
https://github.com/balder-dev/balder
GitHub
GitHub - balder-dev/balder: Python Test Framework, allowing tests to be written once and used on different product or technology…
Python Test Framework, allowing tests to be written once and used on different product or technology variants - without any code duplicates - balder-dev/balder
Building Agentic Workflows in Python with LangGraph
In this article, you will learn how to build a complete agentic workflow in Python with LangGraph, from a single model call to a tool-using agent with persistent conversation memory.
https://machinelearningmastery.com/building-agentic-workflows-in-python-with-langgraph/
In this article, you will learn how to build a complete agentic workflow in Python with LangGraph, from a single model call to a tool-using agent with persistent conversation memory.
https://machinelearningmastery.com/building-agentic-workflows-in-python-with-langgraph/
⚡1
venv_manager
A powerful CLI tool for managing Python virtual environments with ease.
https://github.com/jacopobonomi/venv_manager
A powerful CLI tool for managing Python virtual environments with ease.
https://github.com/jacopobonomi/venv_manager
GitHub
GitHub - jacopobonomi/venv_manager: A powerful CLI tool for managing Python virtual environments with ease.
A powerful CLI tool for managing Python virtual environments with ease. - jacopobonomi/venv_manager
Django: introducing django-crawl
Adam Johnson introduces django-crawl, a tool that uses Django’s test client to crawl a site and uncover broken links, exceptions, and other hidden issues without making real HTTP requests. It can run as a management command or automated test, providing a fast safety net that found seven bugs even in a project with 100% test coverage.
https://adamj.eu/tech/2026/07/22/introducing-django-crawl/
Adam Johnson introduces django-crawl, a tool that uses Django’s test client to crawl a site and uncover broken links, exceptions, and other hidden issues without making real HTTP requests. It can run as a management command or automated test, providing a fast safety net that found seven bugs even in a project with 100% test coverage.
https://adamj.eu/tech/2026/07/22/introducing-django-crawl/
adamj.eu
Django: introducing django-crawl - Adam Johnson
I recently migrated one of my client projects from the legacy django-csp package to Django 6.0’s built-in Content Security Policy (CSP) support (release note). This security header is a powerful tool for preventing unwanted content from being loaded on your…
LLVMLITE in the Browser
This notebook explores how LLVM's optimization pipeline transforms a simple loop, step by step, using llvmlite running entirely in the browser via WebAssembly. We follow one small C++ function through three distinct stages — from source to raw stack-based IR (Intermediate Representation), through SSA form, to a closed-form calculation. After each stage, we inspect the control flow graph ...
https://notebook.link/@anutosh491/llvmlite
This notebook explores how LLVM's optimization pipeline transforms a simple loop, step by step, using llvmlite running entirely in the browser via WebAssembly. We follow one small C++ function through three distinct stages — from source to raw stack-based IR (Intermediate Representation), through SSA form, to a closed-form calculation. After each stage, we inspect the control flow graph ...
https://notebook.link/@anutosh491/llvmlite
Notebook.link
Notebook.link - Run & Share Jupyter Notebooks Instantly
A fully interactive, scalable, and language-agnostic computing environment that operates entirely in your browser. Supports Python, R, C++, and GNU Octave. Share a link — anyone can run it instantly.
Python automations are so much better than AI Agents and LLMs
https://www.reddit.com/r/Python/comments/1v7tfx9/python_automations_are_so_much_better_than_ai/
https://www.reddit.com/r/Python/comments/1v7tfx9/python_automations_are_so_much_better_than_ai/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community