PythonHub

pandas-cheatsheet An interactive Pandas Cheat sheet using PyScript. https://github.com/dylanjcastillo/pandas-cheatsheet/

Someone’s Been Messing With My Subnormals! After noticing an annoying warning, I went on an absurd yak shave, and discovered that because of a tiny handful of Python packages built with an appealing-sounding but dangerous compiler option, more than 2,500 Python packages—some with more than a million downloads per month—could end up causing any program that uses them to compute incorrect numerical results. https://moyix.blogspot.com/2022/09/someones-been-messing-with-my-subnormals.html

Show HN: AutoML Python Package for Tabular Data with Automatic Documentation https://github.com/mljar/mljar-supervised

Multiprocessing Pool in Python This guide provides a detailed and comprehensive review of the multiprocessing.Pool in Python, including how it works, how to use it, common questions, and best practices. https://superfastpython.com/multiprocessing-pool-python/

Accelerate Python code 100x by import taichi as ti There is no universal solution to all optimization problems. That's partially why Python is fascinating. You can always find/create an easy-to-use tool that can precisely solve your problem at hand. In terms of scientific computing, Taichi is an ideal option within Python that can help you achieve performance comparable to C/C++. https://docs.taichi-lang.org/blog/accelerate-python-code-100x

Python in Visual Studio Code – September 2022 Release This release includes the following announcements: https://devblogs.microsoft.com/python/pvsc-sept-2022/

VNext Next-generation Video instance recognition framework on top of Detectron2 which supports SeqFormer(ECCV Oral) and IDOL(ECCV Oral)). https://github.com/wjf5203/VNext

Indoor Asset Tracking using Wi-Fi Triangulation Build a complete indoor asset tracking IoT solution using the Blues Wireless Notecard, an ESP32 host MCU, the Notecarrier-F, and Datacake. https://www.hackster.io/rob-lauer/indoor-asset-tracking-using-wi-fi-triangulation-5c5963

stable-diffusion Stable Diffusion is a latent text-to-image diffusion model. Similar to Google's Imagen, this model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text prompts. With its 860M UNet and 123M text encoder, the model is relatively lightweight and runs on a GPU with at least 10GB VRAM. https://github.com/CompVis/stable-diffusion

docquery An easy way to extract information from documents. https://github.com/impira/docquery

facebookresearch / esm Evolutionary Scale Modeling (esm): Pretrained language models for proteins https://github.com/facebookresearch/esm

Marqo Tensor search for humans. https://github.com/marqo-ai/marqo

Stable Diffusion with Diffusers In this post, we want to show how to use Stable Diffusion with the Diffusers library, explain how the model works and finally dive a bit deeper into how diffusers allows one to customize the image generation pipeline. https://huggingface.co/blog/stable_diffusion

Cog Cog is an open-source tool that lets you package machine learning models in a standard, production-ready container. https://github.com/replicate/cog

Building a backend from scratch using only OpenAI Codex Developing with Codex is a bit special, and it sometimes takes a few attempts to get it to write exactly what you want it to. But in broad strokes, getting from nothing to something in just 10 prompts is really impressive and encouraging. https://codeball.ai/blog/codex-todo-mvc

5 Tips To Achieve Low Coupling In Your Python Code In this video I share 5 tips to help you write code that has low coupling. I'll show you several examples and also share a story of a technique I used several times in the past that has really helped me reduce coupling and solve more complex software design problems. https://www.youtube.com/watch?v=qR4-PBLUZNw

pydantic / pydantic Data parsing and validation using Python type hints https://github.com/pydantic/pydantic

Unicaps A unified Python API for CAPTCHA solving services. https://github.com/sergey-scat/unicaps

The Jupyter+git problem is now solved Jupyter notebooks don’t work with git by default. With nbdev2, the Jupyter+git problem has been totally solved. It provides a set of hooks which provide clean git diffs, solve most git conflicts automatically, and ensure that any remaining conflicts can be resolved entirely within the standard Jupyter notebook environment. To https://www.fast.ai/2022/08/25/jupyter-git/

Bayesian Age/Period/Cohort Models in Python with PyMC This post shows how to use pymc to build Bayesian APC models in Python and presents a series of increasingly sophistocated systems of priors to resolve the inferential challenges these models pose. https://austinrochford.com/posts/apc-pymc.html