Python Weekly (Issue 586 February 2 2023)

Python Weekly - Issue 586

February 02, 2023

Python Weekly

Welcome to issue 586 of Python Weekly. Let's get straight to the links this week.

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News

The Security Developer-in-Residence will work full-time during the initiative to formalize existing security practices and become more proactive in Python-related security improvements. The new role will be responsible for addressing security issues across PSF projects such as CPython and PyPI, and applying knowledge and expertise and working with volunteers to implement key improvements in a timely manner. 

Articles, Tutorials and Talks

Generating pre-labeled data with Matplotlib, optimizing code for real-time performance, and training an object detection model to control a DS emulator and become an expert in playing the Super Mario 64 DS minigame, “Wanted!”

A response to Hillel Wayne’s “

” post.

Python decorators are a great way to add functionality to your Python functions. In this video, I'll show you what they are, how they work, and some of the most useful decorators you can use in your code.

In the paper, we create a large synthetic dataset with 24,126 pairs of non-idiomatic and functionally-equivalent idiomatic code for the nine unique Python idioms identified in Zhang et al., and reuse a large real-project dataset of 54,879 such code pairs provided by Zhang et al. We develop a reliable performance measurement method to compare the speedup or slowdown by idiomatic code against non-idiomatic counterpart, and analyze the performance discrepancies between the synthetic and real-project code, the relationships between code features and performance changes, and the root causes of performance changes at the bytecode level. We summarize our findings as some actionable suggestions for using Python idioms.

In this blog post, you will learn about the basic usage of the library by working with API objects, attributes, pagination and resultsets, and dive into more concrete use cases collecting data, printing summaries and writing data to the API to create comments and commits.

This post provides an introduction to cuNumeric, an endeavoring drop-in replacement for NumPy based on the Legion programming system. It transparently accelerates and distributes NumPy programs to machines of any scale and capability, typically by changing a single module import statement. cuNumeric achieves this by translating the NumPy application interface into the Legate programming model and leveraging the performance and scalability of the Legion runtime.

Is it a copy or a view? Should I merge or join? And what the heck is MultiIndex?

How we used a CLIP-inspired model to suggest keywords for template labeling in multiple languages.

Learn the basics of Django by building a simple online marketplace where people can buy and sell items. You will learn how to implement: Authentication, Communication between users, Dashboard for your items, Form handling and customizations and more.

Interesting Projects, Tools and Libraries

Scalable Python data science, in an API compatible & lightning fast way.

Prompt Engineering, Solve NLP Problems with LLM's & Easily generate different NLP Task prompts for popular generative models like GPT, PaLM, and more with Promptify.

Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch.

A powerful and modular stable diffusion GUI.

AI imagined images. Pythonic generation of stable diffusion images.

UpTrain is an open-source tool for machine learning model monitoring and refinement.

Gracy helps you handle failures, logging, retries, throttling, and tracking for all your HTTP interactions. Gracy uses httpx under the hood.

Rename multiple audio/music files based on the ID3 tag at once. Written in Python3.

Wonderful rich-text editing for your Django project.

New Releases

SQLAlchemy 2.0 includes many more features and with new architectures and a lot of older baggage being shed, hopes to have plenty of room for the future.

Upcoming Events and Webinars

There will be a talk, Learn how AI technologies like ChatGPT can be used to enhance their code writing, debugging, documenting, and testing processes.

There will be following talks

  • A Story from Back to Front: Python in the Browser

  • Python, Rust and Regexes: A Retrospective

There will be following talks

  • Robust Python and Why It Matters

  • Review: "The Art of Clean Code" by Christian Mayer. 17 principles of clean code.

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