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Python Weekly

Welcome to issue 596 of Python Weekly. Let's get straight to the links this week.

From Our Sponsor

Deep dive into the most prevalent critical and high open source vulnerabilities found by Snyk scans of Python apps. Learn more about how these high risk vulnerabilities might be impacting open source packages you are using today and how to fix them.

News

The EU's Proposed CRA Law May Have Unintended Consequences for the Python Ecosystem
The European Union's proposed Cyber Resilience Act and Product Liability Act may have unintended consequences for the Python ecosystem. The PSF is concerned that overly broad policies will unintentionally harm the users they are intended to protect. For example, the proposed laws could make it more difficult for open source projects to be updated and maintained, and could lead to increased legal costs for developers. The PSF is calling on the EU to reconsider these proposals and to work with the open source community to develop policies that are both effective and fair.

Articles, Tutorials and Talks

Building LLM applications for production
This post discusses the challenges of productionizing large language model (LLM) applications. It covers topics such as prompt engineering, cost and latency, task composability, and promising use cases for LLMs. The post argues that LLMs can be powerful tools for a variety of tasks, but that they require careful engineering to be used effectively in production.

Mandala: Python programs that save, query and version themselves
Your code and its execution traces contain enough information to save, query and version computations without extra boilerplate. mandala is a persistent memoization cache on steroids that lets you tap into this information. This post walks you through mandala to give you an idea of its general spirit and the particular ways in which it simplifies computational data management.

How to Use Pandas With Pandera to Validate Your Data in Python

Type hints and annotations are not enough when you are using pandas for data analysis in Python. You need validation! Today I’ll show you how to work with Pandera to quickly and easily validate your dataframes.

Building reproducible Python environments with XARs
The post discusses how to build reproducible Python environments using xars, a tool developed by Jane Street. Xars are self-contained archives of Python packages and their dependencies, allowing for easy distribution and reproducibility across different machines.

Building A ChatGPT-enhanced Python REPL
This article shares the author's experience in building a Python REPL augmented with ChatGPT. He explores how the application is built, and speculates on software engineering patterns and paradigms that might emerge in systems built on Large Language Models (LLMs).

Improving messages and types in GDB’s Python API
The post describes improvements made to the Python API of GDB, a popular debugger. Specifically, the post discusses improvements to the type and message handling within the API, making it easier for developers to use GDB in their Python projects.

The fastest way to read a CSV file in Pandas 2.0
It turns out that the fastest way to create a Pandas DataFrame from a CSV file is to use an entirely different library.

A Practical Introduction to Polars for Python Data Processing
This post is a brief tour of how to set up and use Polars, working through a pragmatic example of the things you might do in a typical data exploration project.

Algebraic Data Types in (typed) Python
Algebraic data types (ADTs) are a way of representing data that can be in one of a few different, mutually exclusive, forms. In Python, ADTs can be represented using the typing module. ADTs can help to make code more clear and concise, and can also help to prevent errors.

Running Python micro-benchmarks using the ChatGPT Code Interpreter alpha

PyCascades 2023 Videos

Dependency Injection in Python

Interesting Projects, Tools and Libraries

Megabots
State-of-the-art, production ready bots made mega-easy, so you don't have to build them from scratch.

Polyfactory
Polyfactory is a simple and powerful mock data generation library, based around type hints and supporting dataclasses, typed-dicts, Pydantic models and more.

web-llm
Bringing large-language models and chat to web browsers. Everything runs inside the browser with no server support.

openai_pricing_logger
openai_pricing_logger is a Python package that logs OpenAI API costs and timestamps. It's designed to help you keep track of API usage and related costs, providing an easy way to monitor and analyze the expenses.

txtinstruct
txtinstruct is a framework for training instruction-tuned models.

markdown-code-runner
Automatically execute code blocks within a Markdown file and update the output in-place.

AutoResearcher
Automating scientific workflows with AI.

LLMZoo
LLM Zoo is a project that provides data, models, and evaluation benchmark for large language models.

poe-api
A reverse engineered Python API wrapper for Quora's Poe, which provides free access to ChatGPT, GPT-4, and Claude.

Semaphore
A full-body keyboard using gestures to type through computer vision.

Wolverine
Give your python scripts regenerative healing abilities!

pyobsplot
Observable Plot in Jupyter notebooks and Quarto documents.

New Releases

pip 23.1
This is the second release of pip for the year 2023. You can find the full list of changes in the changelog.

Upcoming Events and Webinars

PyData NYC Meetup April 2023
There will be following talks

Play in your neighbor's backyard for fun! Different projects, same methods
IBM Call for Code, Sustainability, and AI (Watson Assistant)
Predicting temperatures using linear regression with Python

PyData Chicago Meetup April 2023
There will be a talk, Design and Analysis of Experiments with R and Python.

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