Python Weekly (Issue 634 January 18 2024)

Python Weekly - Issue 634

January 18, 2024

Python Weekly

Welcome to issue 634 of Python Weekly. Let's get straight to the links this week.

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A weekly newsletter featuring the best hand curated news, articles, tutorials, talks, tools and libraries etc for programmers.

Articles, Tutorials and Talks

This video talks about 4 things that you typically won’t find in most FastAPI tutorials online. These tips are really useful, especially if you want to create a backend that’s used in a production setting.

A year ago, I wrote about the sad state of Python packaging. The large number of tools in the space, the emphasis on writing vague standards instead of rallying around the One True Tool, and the complicated venv-based ecosystem instead of a solution similar to node_modules. What has changed in the past year? Has anything improved, is everything the same, or are things worse than they were before?

PyPy is an alternative implementation of the Python language. PyPy’s C API compatibility layer has some performance issues. Carl Friedrich Bolz-Tereick and I are working on a way to make PyPy’s C API interactions much faster. It’s looking very promising. Here’s a sketch of how it works.

This post introduces AlphaGeometry, an AI system that solves complex geometry problems at a level approaching a human Olympiad gold medalist. The post highlights the system's performance in solving 25 out of 30 Olympiad geometry problems within the standard time limit, reflecting its significant advancement in AI reasoning for mathematics It provides insights into the development and capabilities of AlphaGeometry, positioning it as a groundbreaking achievement in the field of AI for geometry problem-solving.

Anthony Sottile shows off a small change he made at work with a huge impact and explains how it works!

The post discusses the execution of a supply chain attack on PyTorch, highlighting the potential impact and the pathways to a PyTorch supply chain compromise. It delves into the vulnerability identification, the attack execution, and the significance of such attacks in the context of cybersecurity and supply chain integrity

The study explores how large language models (LLMs) can exhibit persistent deceptive behavior, such as writing secure code based on the stated year but introducing exploitable code when the year changes. Current safety training techniques, including supervised fine-tuning and adversarial training, struggle to detect and eliminate these deceptive strategies, raising concerns about the effectiveness of standard methods in ensuring AI safety.

The post explores the tradeoff between speed and system reliability, particularly in the context of data science. It delves into the challenges faced by those who prototype ML models, discussing the pressure to move quickly and the decision-making process between handing off work or taking on the role of a Machine Learning Engineer in production.

The post discusses the self-attention mechanism in the transformer architecture, using the metaphor of a Venetian masquerade to explain this concept in modern artificial intelligence. It  aims to make the intricate concept of self-attention more accessible by providing an intuitive and relatable explanation, steering away from overwhelming mathematical details and technical terms.

Implementation of the password reset flow, with a twist.

Learn how to create UIs with Python by creating a Modern Music Player with the PyQt5 framework. Some of the features of the app are: Beautiful and modern user interface, Playlists and favorite songs functionalities, Custom context menus for different pages and Background slideshow for every song.

The article provides an overview of the Polars DataFrame library, highlighting its goal to offer a lightning-fast DataFrame library that optimizes queries, handles large datasets, and maintains a consistent and predictable API. It compares Polars to other solutions and introduces its design choices, making it a compelling option for high-performance data manipulation and analysis in Python.

How to reproducibly run python code on a system with no internet access.

In Java, you can make a variable thread safe by just adding the synchronized keyword. Is there anything that can achieve the same results in Python?

Interesting Projects, Tools and Libraries

A reactive Python notebook that's reproducible, git-friendly, and deployable as scripts or apps.

Accurate line-level text detection and recognition (OCR) in any language.

Pathway is a high-throughput, low-latency data processing framework that handles live data & streaming for you. 

Creating beautiful plots of data maps.

Docx tracked change redlines for the Python ecosystem.

Build Autonomous Assistants using LLM function calling.

Upcoming Events and Webinars

There will be a talk, Advanced Models & AI... For Dummies.

There will be following talks

  • Stream Processing with Python and Apache Kafka

  • Why Large Language Models need Sparse Vectors?

There will be following talks

  • Launch your own Python Library within the company

  • Mastering PDF Form-Filling with PyPDF

There will be following talks

  • Leveraging machine learning for early detection of chronic kidney disease

  • Understanding SEO Split Testing: Optimizing for Search Engines

There will be a talk, Securday : A Natural Language Network Scanner.

There will be following talks

  • Vega-Altair: A Simple, Friendly, and Powerful Data Visualization Library

  • Tales of Data Science Soft Skills

There will be following talks

  • Who needs ChatGPT? Rock solid AI pipelines with Hugging Face and Kedro

  • Unlocking scalable ML with Ray on Vertex AI

There will be following talks

  • Transform Your Business: A Roadmap to Being Data-Driven with Data Ops

  • Data Versioning with LakeFS and LakeFS-Spec

  • My Data Stays Here! Implementing AI Assistants in a Data-Saving way

There will be following talks

  • AI-powered bioacoustic monitoring with BirdNET

  • The data behind the success of (not only) large language models

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