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Python Weekly

Welcome to issue 613 of Python Weekly. Let's get straight to the links this week.

Articles, Tutorials and Talks

How to write Python code people actually want to use

In this video, we adapt a clumsy, non-Pythonic API into an easy to use, easy to understand Pythonic one. We use magic methods such as _getitem__, __len__, __enter__, and __exit_ to make our objects a context manager and support the len() function and square bracket indexing. And in the end, we turn what once was ugly, difficult to maintain code into something that other developers would actually want to use.

Introducing Immortal Objects for Python
Instagram has introduced Immortal Objects – PEP-683 – to Python. Now, objects can bypass reference count checks and live throughout the entire execution of the runtime, unlocking exciting avenues for true parallelism.

The complex simplicity of my static websites
A deep dive into using indentation-based languages like Python and Slim, to build beautiful websites and love the work of doing it till the end.

Harvard CS50’s Artificial Intelligence with Python

This course from Harvard University explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like large language models, game-playing engines, handwriting recognition, and machine translation.

Weird Python "Features" That Might Catch You By Surprise
From time to time, when coding, we all run into weird behaviours of the programming language. Sometimes it's a "feature" we weren't aware of, sometimes it's just quirky behaviour of the language, and sometimes it's borderline bug. Python - as any other programming language - has these eyebrows-raising quirks, so here's a list of weird Python "features" that might catch you off-guard.

Unlocking Insights: Estimating Causal Effect Using Propensity Score Matching
At the end of reading this post, you will be able to understand how to estimate a causal effect with retrospective data, get familiar with the concept of confounders, learn how to balance your data using Propensity Score Matching, and most importantly, you will have fully available code to use for your research. If you feel comfortable with Propensity Score Matching, skip to the real-life example and use the code snippets.

Practical Business Jinja

A talk covering how to automate document creation using Python-docx and Jinja.

Eliminating hallucinations (fast!) in Large Language Models with Finite State Machines
In this blog, we introduce our method for regex-guided generation implemented in Outlines.

End-to-end Testing with Python and Playwright
Want to learn how to use Python and Playwright to automate end-to-end testing using GitHub Actions? This post shows you how to get started with Playwright, add an end-to-end test to help test an existing project that is hosted on GitHub, and automate running it using GitHub Actions.

Identify and Fix Django Database Performance Problems
Optimizing Django query performance is critical for building performant web applications. Django provides many tools and methods for optimizing database queries in its Database access optimization documentation. In this blog post, we will explore a collection of additional and essential tips I’ve compiled over the years to help you pinpoint and resolve your inefficient Django queries.

Hacking Github AWS integrations again
Github supports roles instead of credentials of integrating CI/CD with AWS. It’s easy to misconfigure so let’s show the impact.

Growing Bonsai Networks with RNNs
This writeup introduces what the author calls Bonsai Networks - extremely sparse computational graphs produced by training and pruning RNNs. They provide an interpretable view into the solutions learned by networks for simple logic problems, breaking out of the black box neural networks typically reside in.

Interesting Projects, Tools and Libraries

LearnDB
Learn database internals by implementing it from scratch.

pixi
pixi is a cross-platform, multi-language package manager and workflow tool build on the shoulders of the conda ecosystem. pixi supports Python, R, C/C++, Rust, Ruby, and many other languages.

Prism
Prism is the easiest way to develop, orchestrate, and execute data pipelines in Python.

FaceChain
FaceChain is a deep-learning toolchain for generating your Digital-Twin.

Nemesis
An offensive data enrichment pipeline.

Fooocus
Focus on prompting and generating.

viberary
Viberary is a search engine that recommends books based not on genre or title, but vibe by performing semantic search across a set of learned embeddings on a dataset of books from Goodreads and their metadata.

Opendream
An extensible, easy-to-use, and portable diffusion web UI.

youre-the-os
A game where you are a computer's OS and you have to manage processes, memory and I/O events.

AudioLDM2
Text-to-Audio/Music Generation.

Upcoming Events and Webinars

San Diego Python Meetup August 2023
There will be a talk, How to create Interactive Runbooks Built with Markdown using Runme.

Python Glasgow Meetup August 2023
There will be following talks

Dynamic Modification of Python Programs - the how and the why??
Python-Powered Intelligence: Exploring AI and ML Applications

PyData Südwest Meetup August 2023
There will be following talks

Beyond Toy Datasets: Timeseries Forecasting for Real Business Problems
How to Leverage the Full Potential of LLMs for Your Business with Langchain

PyData Stockholm Meetup August 2023
There will be following talks

Personalized LLMs with a Feature Store
Large Language models and Generative AI at Google

PyData Chicago Meetup August 2023
There will be a talk, PyDDA: A Python package for multi-Doppler wind retrievals.

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Python Weekly - Python Weekly - Issue 613

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