Python Weekly (Issue 654 June 13 2024)

Python Weekly - Issue 654

June 13, 2024

Python Weekly

Welcome to issue 654 of Python Weekly. Let's get straight to the links this week.

Articles, Tutorials and Talks

In this video, Andrej Karpathy demonstrates how to reproduce the GPT-2 (124M) model, covering topics like parameter sharing, model initialization, mixed precision training, optimizations like flash attention, and hyperparameter tuning.

Learn how to solve the scheduling problem in the Hay Day game using Mixed-integer linear programming and Google OR-Tools.

A detailed code walkthrough of how CPython implements memory management, including reference counting and garbage collection.

The post discusses the lack of a canonical form for Python wheel filenames, highlighting that despite standardization in package names and versions, wheel filenames require parsing for equivalence. This lack of canonicalization, especially with compressed tag sets, poses challenges in certain contexts like cryptographic verification. 

This video is a Python tutorial that teaches how to build a SaaS app with Django, Stripe, Neon PostgreSQL, TailwindCSS, and GitHub Actions. It covers topics like Django web development, sending emails, user authentication, deployment, database integration, static files, and subscription management.

The article provides optimal SQLite settings for Django applications, aimed at enhancing performance and reliability for smaller deployments. It includes specific PRAGMA configurations and a simple backup strategy, highlighting the potential of SQLite when correctly tuned for production use.

Simple and modular prompt engineering for efficient Python charting results.

This video shows how you can convert a traditional Django form to an HTMX modal element in just a few quick steps.

An in-depth review of Microsoft's new Python in Excel functionality.

Interesting Projects, Tools and Libraries

Python scraper based on AI. Just say which information you want to extract and the library will do it for you!

The tiniest PaaS you've ever seen. Piku allows you to do git push deployments to your own servers.

AI-Powered Jupyter Notebook built using React.

Inspectus is a versatile visualization tool for large language models. It runs smoothly in Jupyter notebooks via an easy-to-use Python API. Inspectus provides multiple views, offering diverse insights into language model behaviors.

Burr makes it easy to develop applications that make decisions (chatbots, agents, simulations, etc...) from simple python building blocks.

Type `pytest --edit` to open the failing test code.

LLM-powered lossless compression tool.

New Releases

This release includes the following announcements:

  • VS Code Native REPL for Python with Intellisense and syntax highlighting

  • Pytest improvements in the testing rewrite

Upcoming Events and Webinars

There will be following talks

  • Building Intelligent Applications with LangChain

  • Transformers and the Attention Mechanism - The Core Components of LLMs

There will be a talk, pytest: an exemplary framework for testing.

There will be following talks

  • How Data Improves Your Life in Prague

  • DuckDB Intro with Case Study from Keboola

There will be following talks

  • FormatAI: Structuring Unstructured Text using generative AI

  • Probably Fun - games to teach statistics

There will be following talks

  • Building Intelligent Applications with LangChain

  • Transformers and the Attention Mechanism - The Core Components of LLMs

There will be a talk, Polars and Time Series: what it can do, and how to overcome any limitation.

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