PythonHub Logo Python Hub Weekly Digest for 2022-09-11

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Python in Visual Studio Code – September 2022 Release
This release includes the following announcements:

pydantic / pydantic
Data parsing and validation using Python type hints

An easy way to extract information from documents.

Cog is an open-source tool that lets you package machine learning models in a standard, production-ready container.

A unified Python API for CAPTCHA solving services.

📖 Articles

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.

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.

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.

facebookresearch / esm
Evolutionary Scale Modeling (esm): Pretrained language models for proteins

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.

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

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.

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++.

⚙️ Projects

Next-generation Video instance recognition framework on top of Detectron2 which supports SeqFormer(ECCV Oral) and IDOL(ECCV Oral)).

A privacy-focused and secure CMS, Blog and Portfolio made with Python & Django. Designed with developers and IT professionals in mind.

Tensor search for humans.

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.

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