Slipstream - a python library for stateful stream processing
https://slipstream.readthedocs.io/en/1.0.1/
https://slipstream.readthedocs.io/en/1.0.1/
adk-python
An open-source, code-first Python toolkit by Google for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
https://github.com/google/adk-python
An open-source, code-first Python toolkit by Google for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
https://github.com/google/adk-python
GitHub
GitHub - google/adk-python: An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI…
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. - google/adk-python
Build a Desktop Sticky Notes Application with PySide6 & SQLAlchemy
This post provides a step-by-step guide to creating a desktop sticky notes application using PySide6, covering GUI setup, styling, and adding functionality like movable notes and a system tray icon. It explains how to build a simple, frameless note window, enable dragging, and manage multiple notes, with code examples for each stage.
https://www.pythonguis.com/examples/pyside6-desktop-sticky-notes/
This post provides a step-by-step guide to creating a desktop sticky notes application using PySide6, covering GUI setup, styling, and adding functionality like movable notes and a system tray icon. It explains how to build a simple, frameless note window, enable dragging, and manage multiple notes, with code examples for each stage.
https://www.pythonguis.com/examples/pyside6-desktop-sticky-notes/
Python GUIs
Build a Desktop Sticky Notes Application with PySide6 & SQLAlchemy
Build a desktop sticky notes application with Python and Qt6. Persistent note storage with SQLAlchemy and SQLite. Do you ever find yourself needing to take a quick note of some information but have nowhere to put it? Then this app is for you! This virtual…
Reproducing word2vec with JAX
This article reproduces the word2vec model using JAX, explaining the CBOW architecture and its implementation. It trains word embeddings and demonstrates how to find word similarities and analogies using the trained model, comparing it to modern text embeddings used in LLMs.
https://eli.thegreenplace.net/2025/reproducing-word2vec-with-jax/
This article reproduces the word2vec model using JAX, explaining the CBOW architecture and its implementation. It trains word embeddings and demonstrates how to find word similarities and analogies using the trained model, comparing it to modern text embeddings used in LLMs.
https://eli.thegreenplace.net/2025/reproducing-word2vec-with-jax/
nano-aha-moment
Single File, Single GPU, From Scratch, Efficient, Full Parameter Tuning library for "RL for LLMs"
https://github.com/McGill-NLP/nano-aha-moment
Single File, Single GPU, From Scratch, Efficient, Full Parameter Tuning library for "RL for LLMs"
https://github.com/McGill-NLP/nano-aha-moment
GitHub
GitHub - McGill-NLP/nano-aha-moment: Single File, Single GPU, From Scratch, Efficient, Full Parameter Tuning library for "RL for…
Single File, Single GPU, From Scratch, Efficient, Full Parameter Tuning library for "RL for LLMs" - McGill-NLP/nano-aha-moment
I made a simple Artificial Life simulation software with python
https://www.reddit.com/r/Python/comments/1jwzv2h/i_made_a_simple_artificial_life_simulation/
https://www.reddit.com/r/Python/comments/1jwzv2h/i_made_a_simple_artificial_life_simulation/
Reddit
From the Python community on Reddit: I made a simple Artificial Life simulation software with python
Explore this post and more from the Python community
arxiv-mcp-server
A Model Context Protocol server for searching and analyzing arXiv papers.
https://github.com/blazickjp/arxiv-mcp-server
A Model Context Protocol server for searching and analyzing arXiv papers.
https://github.com/blazickjp/arxiv-mcp-server
GitHub
GitHub - blazickjp/arxiv-mcp-server: A Model Context Protocol server for searching and analyzing arXiv papers
A Model Context Protocol server for searching and analyzing arXiv papers - blazickjp/arxiv-mcp-server
memo
Memo is a simple command-line interface (CLI) tool for managing your Apple Notes (and eventually Apple Reminders). It’s written in Python and aims to offer a fast, keyboard-driven way to create, search, and organize notes and reminders straight from your terminal.
https://github.com/antoniorodr/memo
Memo is a simple command-line interface (CLI) tool for managing your Apple Notes (and eventually Apple Reminders). It’s written in Python and aims to offer a fast, keyboard-driven way to create, search, and organize notes and reminders straight from your terminal.
https://github.com/antoniorodr/memo
GitHub
GitHub - antoniorodr/memo: Memo is a simple command-line interface (CLI) tool for managing your Apple Notes and Apple Reminders.…
Memo is a simple command-line interface (CLI) tool for managing your Apple Notes and Apple Reminders. It’s written in Python and aims to offer a fast, keyboard-driven way to create, search, and org...
curl-impersonate
A special build of curl that can impersonate Chrome & Firefox.
https://github.com/lwthiker/curl-impersonate
A special build of curl that can impersonate Chrome & Firefox.
https://github.com/lwthiker/curl-impersonate
GitHub
GitHub - lwthiker/curl-impersonate: curl-impersonate: A special build of curl that can impersonate Chrome & Firefox
curl-impersonate: A special build of curl that can impersonate Chrome & Firefox - lwthiker/curl-impersonate
Code DeepSeek V3 From Scratch in Python
This video provides a comprehensive, step-by-step coding guide to understanding and implementing DeepSeek V3, a cutting-edge deep learning model. It covers key concepts like the attention mechanism, multihead latent attention (MLA), rotary positional embeddings (RoPE), and the mixture of experts (MoE) architecture, explaining the science behind it all.
https://www.youtube.com/watch?v=5avSMc79V-w
This video provides a comprehensive, step-by-step coding guide to understanding and implementing DeepSeek V3, a cutting-edge deep learning model. It covers key concepts like the attention mechanism, multihead latent attention (MLA), rotary positional embeddings (RoPE), and the mixture of experts (MoE) architecture, explaining the science behind it all.
https://www.youtube.com/watch?v=5avSMc79V-w
YouTube
Code DeepSeek V3 From Scratch in Python - Full Course
This course is a comprehensive guide to understanding and implementing DeepSeek V3, a cutting-edge deep learning model. @vukrosic shares step-by-step coding instructions and theoretical insights.
🔗 paper - https://arxiv.org/pdf/2412.19437
💻 https://git…
🔗 paper - https://arxiv.org/pdf/2412.19437
💻 https://git…
llm-compressor
Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM.
https://github.com/vllm-project/llm-compressor
Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM.
https://github.com/vllm-project/llm-compressor
GitHub
GitHub - vllm-project/llm-compressor: Transformers-compatible library for applying various compression algorithms to LLMs for optimized…
Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM - vllm-project/llm-compressor
VeOmni
Scaling any Modality Model Training to any Accelerators with PyTorch native Training Framework.
https://github.com/ByteDance-Seed/VeOmni
Scaling any Modality Model Training to any Accelerators with PyTorch native Training Framework.
https://github.com/ByteDance-Seed/VeOmni
GitHub
GitHub - ByteDance-Seed/VeOmni: VeOmni: Scaling any Modality Model Training to any Accelerators with PyTorch native Training Framework
VeOmni: Scaling any Modality Model Training to any Accelerators with PyTorch native Training Framework - ByteDance-Seed/VeOmni
User Onboarding Tips and Tricks for Django Developers
This video explains how to implement anonymous onboarding in Django apps, allowing users to try the app without creating an account. It covers storing temporary data in the session and seamlessly transferring it to a user account once created, enhancing the initial user experience.
https://www.youtube.com/watch?v=gFnE6a9-kLw
This video explains how to implement anonymous onboarding in Django apps, allowing users to try the app without creating an account. It covers storing temporary data in the session and seamlessly transferring it to a user account once created, enhancing the initial user experience.
https://www.youtube.com/watch?v=gFnE6a9-kLw
YouTube
User Onboarding Tips and Tricks for Django Developers
In this video I run through some of the details of the onboarding flow for my new app, Life in Weeks, which one person said "made the difference between me trying it at all versus sending the app to a few friends."
The key is letting people play with the…
The key is letting people play with the…
MedReason
Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs.
https://github.com/UCSC-VLAA/MedReason
Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs.
https://github.com/UCSC-VLAA/MedReason
GitHub
GitHub - UCSC-VLAA/MedReason: MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs
MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs - UCSC-VLAA/MedReason
meta-llama / llama-models
Utilities intended for use with Llama models.
https://github.com/meta-llama/llama-models
Utilities intended for use with Llama models.
https://github.com/meta-llama/llama-models
GitHub
GitHub - meta-llama/llama-models: Utilities intended for use with Llama models.
Utilities intended for use with Llama models. Contribute to meta-llama/llama-models development by creating an account on GitHub.
Python 3.14 | Upcoming Changes
This video discusses the upcoming features, performance improvements, and other changes in Python 3.14, including the tail call interpreter, JIT compiler, and free threading. It also covers minor updates and deprecations, providing a comprehensive overview of the new release.
https://www.youtube.com/watch?v=hzys1_xmLPc
This video discusses the upcoming features, performance improvements, and other changes in Python 3.14, including the tail call interpreter, JIT compiler, and free threading. It also covers minor updates and deprecations, providing a comprehensive overview of the new release.
https://www.youtube.com/watch?v=hzys1_xmLPc
YouTube
Python 3.14. What's new?
So, in one month Python 3.14b1 will be released, and in this video I'll show you off most of the important changes that's coming.
00:00 - Intro
00:10 - Schedule
00:26 - PEP 765
01:30 - PEP 648
02:16 - PEP 758
02:45 - Performance
04:12 - Tail-call interpreter…
00:00 - Intro
00:10 - Schedule
00:26 - PEP 765
01:30 - PEP 648
02:16 - PEP 758
02:45 - Performance
04:12 - Tail-call interpreter…
How to Extract GPS Coordinates from a Photo: The USAID Mystery
This post explains how to extract GPS coordinates from a photo using Python and plot them on a map, using libraries like Pillow, ExifRead, and Folium. It challenges the reader to analyze the location of a USAID nutrition pack to determine if the aid is being distributed appropriately.
https://www.marsja.se/how-to-extract-gps-coordinates-from-a-photo-the-usaid-mystery/
This post explains how to extract GPS coordinates from a photo using Python and plot them on a map, using libraries like Pillow, ExifRead, and Folium. It challenges the reader to analyze the location of a USAID nutrition pack to determine if the aid is being distributed appropriately.
https://www.marsja.se/how-to-extract-gps-coordinates-from-a-photo-the-usaid-mystery/
Erik Marsja
How to Extract GPS Coordinates from a Photo: The USAID Mystery
We used Python to uncover where a USAID nutrition pack ended up—learn how to extract GPS data from photos and map it step-by-step.
open-rag-eval
Evaluate and improve your Retrieval-Augmented Generation (RAG) pipelines with open-rag-eval, an open-source Python evaluation toolkit.
https://github.com/vectara/open-rag-eval
Evaluate and improve your Retrieval-Augmented Generation (RAG) pipelines with open-rag-eval, an open-source Python evaluation toolkit.
https://github.com/vectara/open-rag-eval
GitHub
GitHub - vectara/open-rag-eval: Open source RAG evaluation package
Open source RAG evaluation package. Contribute to vectara/open-rag-eval development by creating an account on GitHub.