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News & links about Python programming. https://pythonhub.dev/ Administrator: @rukeba
speechbrain / speechbrain
A PyTorch-based Speech Toolkit
https://github.com/speechbrain/speechbrain
PyKidos, Teach Your Kid Python in the Browser
https://pykidos.github.io/
ndleah / python-mini-project
🙌 Welcome open-source Python mini-project contributions!
https://github.com/ndleah/python-mini-project
chedule-texts-from-txt
Schedule iMessage or SMS texts from .txt files.
https://github.com/reidjs/schedule-texts-from-txt
fructose
LLM calls as strongly-typed functions.
https://github.com/bananaml/fructose
Speed up Django’s collectstatic command with Collectfasta
The post introduces Collectfasta, an updated fork of Collectfast designed to enhance the performance of Django's collectstatic command. By optimizing the repository and improving performance, Collectfasta offers faster execution and efficiency compared to the standard Django command, providing a valuable tool for developers seeking enhanced performance in their Django projects.
https://jasongi.com/2024/03/04/speed-up-djangos-collectstatic-command-with-collectfasta/
Python Gevent in practice: common pitfalls to keep in mind
Learn more about the common pitfalls of using the asynchronous Python library, Gevent, and how to resolve them in this article.
https://upsun.com/blog/python-gevent-best-practices/
We Hacked Google A.I. for $50,000
This article discusses the author's experience of participating in a hacking event in Las Vegas where vulnerabilities were discovered, leading to the successful hacking of Google. Despite the initial achievement, the Google VRP team extended the competition deadline to encourage more creative findings, highlighting the ongoing challenges and opportunities in the realm of cybersecurity
https://www.landh.tech/blog/20240304-google-hack-50000
Parsing URLs in Python
https://tkte.ch/articles/2024/03/15/parsing-urls-in-python.html
openllmetry
Open-source observability for your LLM application.
https://github.com/traceloop/openllmetry
Using LLMs to Generate Fuzz Generators
The post explores the effectiveness of Large Language Models (LLMs) in generating fuzz drivers for library API fuzzing. It discusses the challenges and benefits of LLM-based fuzz driver generation, highlighting its practicality, strategies for complex API usage, and areas for improvement based on a comprehensive study and evaluation.
https://verse.systems/blog/post/2024-03-09-using-llms-to-generate-fuzz-generators
Python Hub Weekly Digest for 2024-03-17
https://pythonhub.dev/digest/2024-03-17/
Doubiiu / DynamiCrafter
DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors
https://github.com/Doubiiu/DynamiCrafter
Get started with conda environments
This post explains the benefits of virtual environments and how to use virtual environments in conda.
https://www.dataschool.io/intro-to-conda-environments/
I made a YouTube downloader with Modern UI | PyQt6 | PyTube | Fluent Design
https://www.reddit.com/r/Python/comments/1b66726/i_made_a_youtube_downloader_with_modern_ui_pyqt6/
CBScript
CBScript is a transpiled language, designed by SethBling. This compiler will compile CBScript files into Minecraft datapack zip files. It has many higher level language features that don't exist at the Minecraft command level.
https://github.com/SethBling/cbscript
LlamaGym
Fine-tune LLM agents with online reinforcement learning.
https://github.com/KhoomeiK/LlamaGym
facebookresearch / DiT
Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"
https://github.com/facebookresearch/DiT
Homebrew all the Python things
https://blog.davep.org/2024/03/10/homebrew-all-the-python-things.html
Understanding Context Manager and its Syntastic Sugar
https://bjoernricks.github.io/posts/python/context-manager/
ibis-project / ibis
the portable Python dataframe library
https://github.com/ibis-project/ibis
Large Language Models On-Device with MediaPipe and TensorFlow Lite
The article discusses the release of the experimental MediaPipe LLM Inference API, enabling Large Language Models (LLMs) to run fully on-device across platforms. This transformative capability addresses the significant memory and compute demands of LLMs, which are over a hundred times larger than traditional on-device models, achieved through optimizations like new ops, quantization, cac...
https://developers.googleblog.com/2024/03/running-large-language-models-on-device-with-mediapipe-andtensorflow-lite.html
Insecurity and Python pickles
https://lwn.net/SubscriberLink/964392/498a12fe44f51139/
Create A Machine Learning Powered NCAA Bracket
Dive into the fascinating world of machine learning and AI as we guide you through developing a model designed to predict NCAA tournament outcomes. From initial setup to final predictions, we’ll cover everything you need to create your own powerhouse model.
https://www.youtube.com/watch?v=cHtAEWkvSMU
GGUF, the long way around
This is an article about GGUF, a file format used for machine learning models. It discusses what machine learning models are and how they are produced.
https://vickiboykis.com/2024/02/28/gguf-the-long-way-around/
JSON Serialization
https://www.reddit.com/r/Python/comments/1bfs8cy/json_serialization/
EvalPlus
EvalPlus for rigourous evaluation of LLM-synthesized code.
https://github.com/evalplus/evalplus
Analyzing "Sorting a million 32-bit integers in 2MB of RAM using Python"
SummaryWe are going to revisit Guido's famous "Sorting a million 32-bit integers in 2MB of RAM ...
https://www.bitecode.dev/p/analyzing-sorting-a-million-32-bit
FujiwaraChoki / MoneyPrinter
Automate Creation of YouTube Shorts using MoviePy.
https://github.com/FujiwaraChoki/MoneyPrinter
6 ways to improve the architecture of your Python project (using import-linter)
The article discusses six ways to enhance the architecture of Python projects, focusing on maintaining clear dependency relationships between packages and modules to avoid tangled inter-module dependencies. It addresses challenges like high architectural understanding costs for newcomers and reduced development efficiency due to difficulties in locating code within large projects.
https://www.piglei.com/articles/en-6-ways-to-improve-the-arch-of-you-py-project/