PythonHub

Python Hub Weekly Digest for 2023-09-03 https://pythonhub.dev/digest/2023-09-03/

A Comprehensive Guide to Python Logging with Structlog Structlog is an open-source logging tool for Python known for its simple API, performance, and quality of life features. This tutorial explores the essential aspects of Structlog. https://betterstack.com/community/guides/logging/structlog/

karpathy / llama2.c Inference Llama 2 in one file of pure C https://github.com/karpathy/llama2.c

Structuring your Infrastructure as Code The author proposes a layered approach to IaC, with each layer representing a different aspect of your infrastructure. This approach makes it easy to isolate changes to different parts of your infrastructure, and to reuse code across different environments. https://leebriggs.co.uk/blog/2023/08/17/structuring-iac

seamless_communication SeamlessM4T is designed to provide high quality translation, allowing people from different linguistic communities to communicate effortlessly through speech and text. https://github.com/facebookresearch/seamless_communication

Fixit 2: Meta’s next-generation auto-fixing linter Fixit is dead! Long live Fixit 2 – the latest version of our open-source auto-fixing linter. Fixit 2 allows developers to efficiently build custom lint rules and perform auto-fixes for their codebases. https://engineering.fb.com/2023/08/07/developer-tools/fixit-2-linter-meta/

Composition over inheritance: The case for function-based views The author shares some of his thoughts re. function- vs class-based views in Django. https://406.ch/writing/composition-over-inheritance-the-case-for-function-based-views/

How to implement CommandBus in Python CommandBus is a communication mechanism used to decouple the sender of a command from its handler or executor. It is a part of the Command Pattern and is commonly used in applications that follow the CQRS (Command Query Responsibility Segregation) pattern or other similar architectural styles. This article provides a comprehensive guide on implementing the CommandBus in Python https://blog.szymonmiks.pl/p/how-to-implement-commandbus-in-python/

hegelai / prompttools Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB). https://github.com/hegelai/prompttools

facefusion Next generation face swapper and enhancer. https://github.com/facefusion/facefusion

Understanding Immortal Objects in Python 3.12: A Deep Dive into Python Internals A detailed examination of Python 3.12's internal changes featuring the concept of 'immortal' objects, for performance enhancements https://codeconfessions.substack.com/p/understanding-immortal-objects-in

Understanding Automatic Differentiation in 30 lines of Python https://vmartin.fr/understanding-automatic-differentiation-in-30-lines-of-python.html

Asyncio, twisted, tornado, gevent walk into a bar... SummaryConcurrency has a lot to do with sharing one resource, and Python has dedicated tools to ... https://www.bitecode.dev/p/asyncio-twisted-tornado-gevent-walk

Build Apps in Python with Dara https://www.reddit.com/r/Python/comments/1614om5/build_apps_in_python_with_dara/

nl2query A framework for converting natural language text inputs to corresponding Pandas, MongoDB, Kusto and Neo4j (Cypher) queries. https://github.com/Chirayu-Tripathi/nl2query

VisionScript A high-level programming language for using computer vision. https://github.com/capjamesg/visionscript

GPU-Accelerated, Deterministic ML Dev Environments with Docker and CUDA A Better Way to Build Your AI Enhanced Project. https://www.makeartwithpython.com/blog/developing-machine-learning-applications/

Collection of stand-alone Python machine learning recipes (2021) https://github.com/rougier/ML-Recipes

Development with Large Language Models Tutorial – OpenAI, Langchain, Agents, Chroma Throughout this course, you will complete hands-on projects will help you learn how to harness LLMs for your own projects. You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers. https://www.youtube.com/watch?v=xZDB1naRUlk

Shell-AI Shell-AI (shai) is a CLI utility that brings the power of natural language understanding to your command line. Simply input what you want to do in natural language, and shai will suggest single-line commands that achieve your intent. https://github.com/ricklamers/shell-ai