Python Hub Weekly Digest for 2023-12-03
💖 Most Popular
Python Is Easy. Go Is Simple. Simple != Easy
How many Python core devs use typing?
Python 3.12 Generic Types Explained
This video explores how generic types in Python 3.12 work, and what the advantage is over just using the Any types.
screenshot-to-code
Drop in a screenshot and convert it to clean HTML/Tailwind/JS code.
A JIT Compiler for CPython
Brandt Bucher discusses the development of a Just-In-Time (JIT) compiler for CPython. The talk delves into the challenges and intricacies of implementing a JIT compiler specifically for CPython, the default Python interpreter.
📖 Articles
Building a Neural Network with PyTorch
Building your first neural network could seem like a formidable undertaking, but deep learning frameworks like PyTorch have made the task more accessible than ever. This article explains how to build a neural network using PyTorch.
Django 5.0 release candidate 1 released
Two kinds of threads pools, and why you need both
How big should your thread pool be? It depends on your use case.
The Categories of Bugs in Python Apps
When writing a Python program, errors are inevitable. However, we can manage the types of errors we produce. Let’s explore a simple model categorizing these errors, from best to worst, and discuss how mindful tool usage can improve software quality.
Let's Code an AI Search Engine with LLM Embeddings, Django, and pgvector
Large Language Models (LLMs) can be leveraged for business applications, such as content matching and job search. William Huster demonstrates how to build a prototype application that utilizes LLMs for job search.
GitHub OAuth in your Python Flask app
A step-by-step guide on building Login with Github into your Python apps.
How to Create a Subscription SaaS Application with Django and Stripe
All the technical details of creating a subscription SaaS business using the Python-based Django web framework and Stripe payment processor.
Inserting data via the PostgREST API using Python
Azure-Samples / chat-with-your-data-solution-accelerator
A Solution Accelerator for the RAG pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. This includes most common requirements and best practices.
Pythonicity: Composition vs. Inheritance
Four Kinds of Optimisation
This article discusses four approaches to optimize programs: using a better algorithm, using a better data structure, using a lower-level system, or accepting a less precise solution.
Proposal for Software Bill-of-Materials for CPython
Data Parallel Extensions for Python
Python Hub Weekly Digest for 2023-11-26
Orca-2-13B Runs Directly on Rust+WASM – No Python/C++ Hassles
⚙️ Projects
Generative AI for Beginners
A 12 Lesson course teaching everything you need to know to start building Generative AI applications.
stateless
Statically typed, purely functional effects for Python.
PyNest
PyNest is a Python framework built on top of FastAPI that follows the modular architecture of NestJS.
pytest-patterns
pytest-patterns is a plugin for pytest that provides a pattern matching engine optimized for testing.
Google-Colab-Selenium
The best way to use Selenium in Google Colab Notebooks!
sqlalchemy_data_model_visualizer
Automatically turn your SQLalchemy Data Models into a Nice SVG Diagram
NeumAI
Neum AI is a best-in-class framework to manage the creation and synchronization of vector embeddings at large scale.
LoRAX
Serve 100s of Fine-Tuned LLMs in Production for the Cost of 1.
AIConfig
Config-driven, source control friendly AI application development.
ai-exploits
A collection of real world AI/ML exploits for responsibly disclosed vulnerabilities.
StyleTTS 2
Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models
Project by Ruslan Keba. Since 2012. Powered by Python. Made in 🇺🇦Ukraine.