codelion / openevolve
Open-source implementation of AlphaEvolve
https://github.com/codelion/openevolve
Open-source implementation of AlphaEvolve
https://github.com/codelion/openevolve
GitHub
GitHub - codelion/openevolve: Open-source implementation of AlphaEvolve
Open-source implementation of AlphaEvolve. Contribute to codelion/openevolve development by creating an account on GitHub.
AI-Trader
Five AIs battle for NASDAQ 100 supremacy. Zero human input. Pure competition.
https://github.com/HKUDS/AI-Trader
Five AIs battle for NASDAQ 100 supremacy. Zero human input. Pure competition.
https://github.com/HKUDS/AI-Trader
GitHub
GitHub - HKUDS/AI-Trader: "AI-Trader: Can AI Beat the Market?" Live Trading Bench: https://hkuds.github.io/AI-Trader/
"AI-Trader: Can AI Beat the Market?" Live Trading Bench: https://hkuds.github.io/AI-Trader/ - HKUDS/AI-Trader
Introducing FlashPack: Lightning-Fast Model Loading for PyTorch
The FlashPack package dramatically speeds up PyTorch model loading by flattening all weights into a single contiguous stream, memory-mapping the file, and overlapping disk, CPU, and GPU operations with CUDA streams. This approach yields 3-6× faster loading compared to traditional methods like loadstatedict(), reducing GPU idle time and improving overall performance, especially on syste...
https://blog.fal.ai/introducing-flashpack-lightning-fast-model-loading-for-pytorch
The FlashPack package dramatically speeds up PyTorch model loading by flattening all weights into a single contiguous stream, memory-mapping the file, and overlapping disk, CPU, and GPU operations with CUDA streams. This approach yields 3-6× faster loading compared to traditional methods like loadstatedict(), reducing GPU idle time and improving overall performance, especially on syste...
https://blog.fal.ai/introducing-flashpack-lightning-fast-model-loading-for-pytorch
fal.ai Blog | Generative AI Model Releases & Tutorials
Introducing FlashPack: Lightning-Fast Model Loading for PyTorch
When using machine learning models in the real world, performance isn’t just about how fast your GPU can crunch numbers — it’s also about how quickly you can get your model there. Every second spent waiting on a checkpoint to load is a second your GPUs sit…
The Building Blocks of Agentic AI: From Kernels to Clusters
The PyTorch Native Agentic Stack is a scalable, PyTorch-integrated framework designed for building and deploying autonomous AI agents across thousands of GPUs. It simplifies complex distributed reinforcement learning workflows by orchestrating large-scale models, providing abstractions for services, fault tolerance, and efficient state management to accelerate AI research and deployment.
https://ai.meta.com/blog/introducing-pytorch-native-agentic-stack
The PyTorch Native Agentic Stack is a scalable, PyTorch-integrated framework designed for building and deploying autonomous AI agents across thousands of GPUs. It simplifies complex distributed reinforcement learning workflows by orchestrating large-scale models, providing abstractions for services, fault tolerance, and efficient state management to accelerate AI research and deployment.
https://ai.meta.com/blog/introducing-pytorch-native-agentic-stack
Meta AI
The Building Blocks of Agentic AI: From Kernels to Clusters
At PyTorch Conference 2025 in San Francisco, we unveiled five new projects spanning kernel languages, distributed systems, reinforcement learning, agentic frameworks, and edge AI deployment.
Nyno
Create and Run Linux Workflows without Limits. Short for "nine" / "yaml" / "no-code" / "automation".
https://github.com/empowerd-cms/nyno
Create and Run Linux Workflows without Limits. Short for "nine" / "yaml" / "no-code" / "automation".
https://github.com/empowerd-cms/nyno
GitHub
GitHub - empowerd-cms/nyno: Create and Run Linux Workflows without Limits. Short for "nine" / "yaml" / "no-code" / "automation".
Create and Run Linux Workflows without Limits. Short for "nine" / "yaml" / "no-code" / "automation". - GitHub - empowerd-cms...
Detecting object wrappers
The wrapt library's version 2.0.0 changed its object proxy class hierarchy, breaking checks that detect if an object is already wrapped, causing repeated wrapping and performance issues. The best practice is to use custom wrapper types and traverse wrapper chains via the wrappedattribute to reliably detect wrapping, emphasizing careful version pinning and cautious monkey patching in ...
https://grahamdumpleton.me/posts/2025/10/detecting-object-wrappers/
The wrapt library's version 2.0.0 changed its object proxy class hierarchy, breaking checks that detect if an object is already wrapped, causing repeated wrapping and performance issues. The best practice is to use custom wrapper types and traverse wrapper chains via the wrappedattribute to reliably detect wrapping, emphasizing careful version pinning and cautious monkey patching in ...
https://grahamdumpleton.me/posts/2025/10/detecting-object-wrappers/
grahamdumpleton.me
Detecting object wrappers - Graham Dumpleton
How to detect if an object has already been wrapped.
pip 25.3
The pip 25.3 release is the final major pip update of 2025, featuring the removal of non-PEP 517 package build support and non-PEP 660 editable installs, meaning pip no longer calls legacy setup.py commands. It adds the new --build-constraint option for specifying build-time constraints separately, improves caching and metadata handling, supports editable requirements as Direct URLs, and...
https://discuss.python.org/t/announcement-pip-25-3-release/104550
The pip 25.3 release is the final major pip update of 2025, featuring the removal of non-PEP 517 package build support and non-PEP 660 editable installs, meaning pip no longer calls legacy setup.py commands. It adds the new --build-constraint option for specifying build-time constraints separately, improves caching and metadata handling, supports editable requirements as Direct URLs, and...
https://discuss.python.org/t/announcement-pip-25-3-release/104550
Discussions on Python.org
Announcement: pip 25.3 release!
On behalf of the PyPA, I am pleased to announce that the pip team has just released pip 25.3. This is the fourth and final major release of pip for the year 2025. You can read more about our versioning, deprecation policy, and release process here. Highlights…
Wheels for free-threaded Python now available for psutil
https://gmpy.dev/blog/2025/wheels-for-free-threaded-python-now-available-in-psutil
https://gmpy.dev/blog/2025/wheels-for-free-threaded-python-now-available-in-psutil
EuroPython 2025 Videos
Here are all the videos for the conference, brought to you by the EuroPython 2025 Team and the EuroPython Society.
https://www.youtube.com/playlist?list=PL8uoeex94UhFQY9cYBQOVkj9fSHMHf5x9
Here are all the videos for the conference, brought to you by the EuroPython 2025 Team and the EuroPython Society.
https://www.youtube.com/playlist?list=PL8uoeex94UhFQY9cYBQOVkj9fSHMHf5x9
YouTube
EuroPython 2025
Welcome to EuroPython 2025, held in Prague, the Czech Republic from 14 - 20 July 2025! Here are all the videos for the conference, brought to you by the Euro...
👍1👏1
Helion: A High-Level DSL for Performant and Portable ML Kernels
Helion is a Python-embedded high-level DSL that compiles to optimized Triton kernels, blending the simplicity of PyTorch syntax with powerful autotuning to deliver high-performance, portable machine learning kernels across hardware architectures. It automates complex tasks like tensor indexing, memory management, and hardware-specific tuning, enabling developers to write efficient kernel...
https://pytorch.org/blog/helion/
Helion is a Python-embedded high-level DSL that compiles to optimized Triton kernels, blending the simplicity of PyTorch syntax with powerful autotuning to deliver high-performance, portable machine learning kernels across hardware architectures. It automates complex tasks like tensor indexing, memory management, and hardware-specific tuning, enabling developers to write efficient kernel...
https://pytorch.org/blog/helion/
The Best Way to Share Code Between Python Apps
The video explains how to use UV workspaces to manage multiple Python applications with shared code and dependencies in a single repository. It demonstrates structuring a project with CLI and FastAPI apps, extracting shared logic into internal packages, and managing dependencies efficiently to avoid duplication and conflicting environments. The approach simplifies development and scaling...
https://www.youtube.com/watch?v=N_ypJwV8Q8I
The video explains how to use UV workspaces to manage multiple Python applications with shared code and dependencies in a single repository. It demonstrates structuring a project with CLI and FastAPI apps, extracting shared logic into internal packages, and managing dependencies efficiently to avoid duplication and conflicting environments. The approach simplifies development and scaling...
https://www.youtube.com/watch?v=N_ypJwV8Q8I
YouTube
The Best Way to Share Code Between Python Apps
✅ Learn how to build robust and scalable software architecture: https://arjan.codes/checklist.
In this video, I show you how to use uv workspaces to manage multiple Python apps—like a CLI tool and a FastAPI app—with shared dependencies and shared logic.…
In this video, I show you how to use uv workspaces to manage multiple Python apps—like a CLI tool and a FastAPI app—with shared dependencies and shared logic.…