Python Weekly (Issue 610 July 27 2023)

Python Weekly - Issue 610

July 27, 2023

Python Weekly

Welcome to issue 610 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

The article outlines the development process of Jsonic, a custom JSON-like language, from its simple form to more advanced features, providing insights into language design and parsing techniques. It showcases how the language evolves and gains complexity while maintaining its JSON-like structure and usefulness for specific use cases.

In this post, we'll review common patterns and types of IDOR vulnerabilities and how to protect against them.

In part two of their conversation, Ben and Kyle chat with Python core developer and Steering Council member Pablo Galindo Salgado about balancing consistency and new features in language design, the importance of gathering community feedback on new iterations, and why he’s focused on making Python faster.

Django admin panel is one of the biggest strengths on Django. It allows quickly have interface access data stored in DB, have forms to add and edit data and manage users. But since in its default state Django Admin Site is quite basic, so in this article I want to go over all the ways to make the most out of it by customizing it.

pathlib is an interesting, object-oriented take on the filesystem paths. With plenty of functions to create, delete, move, rename, read, write, find, or split files, pathlib is an excellent replacement for the os module. But is it faster? 

The article describes how to use the cProfile module to profile a section of Python code. The cProfile module provides a detailed breakdown of the time spent in each function in the profiled code.

The article describes how the sqlite-utils library now supports plugins. Plugins are a way to extend the functionality of sqlite-utils by adding new commands or features.

The post compares the performance of Polars and Pandas libraries within an AWS Lambda environment, evaluating their capabilities and efficiency for data manipulation tasks, providing valuable insights for users seeking to optimize data processing in serverless setups. It explores the strengths and limitations of each library, helping readers make informed decisions when working with large datasets in resource-constrained environments.

A demonstration of quantum-resistant encryption using the well-known “Learning with Errors” problem.

The article discusses how to overcome performance bottlenecks in CPU-bound code using asynchronous programming in Python. The author provides a deep dive into the concepts of asynchronous programming and how they can be used to improve the performance of CPU-bound code.

The article discusses how to use the fork() system call to speed up Python test iteration. The technique can improve test iteration times by up to 10x.

Interesting Projects, Tools and Libraries

Deploy a private ChatGPT alternative hosted within your VPC. Connect it to your organization's knowledge base and use it as a corporate oracle. Supports open-source LLMs like Llama 2, Falcon, and GPT4All.

Marsha is a functional, higher-level, English-based programming language that gets compiled into tested Python software by an LLM 

Towards Richest and Most Diverse Unified Dataset Collection and Instruction-Aware Models for Conversational AI.

Build lightweight, extensible, and testable LLM Agents.

MS Paint in your terminal. 

A biased barometer for gauging the relative speed of some regex engines on a curated set of tasks.

FastAPI to the Cloud, Batteries Included!

Upcoming Events and Webinars

There will be following talks

  • Code AI: Reimagining Software Development with Generative Models 

  • Web Scraping Your Government with Python

  • GenAI in AWS

  • Generating music videos using Stable Diffusion

  • Open-Source, Community Innovation, and A.I. 

Are you excited about LLMs or has their rise to fame disheartened you? Join us for a round-table discussion on the current state of ML and AI. With the rise to fame of LLMs many machine learning and data science specialist have had mixed feelings about where the industry is going. If you are not a part of a company on the cutting edge of AI research where does that leave you?

There will be a talk, Business automation made easy using SpiffWorkflow.

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