Python Weekly (Issue 683 January 16 2025)

Author

Rahul Chaudhary
January 16, 2025

Welcome to issue 683 of Python Weekly. Let's get straight to the links this week.

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News

The EuroPython 2025 Call for Proposals (CFP) is open and accepting proposals for talks, tutorials and posters.

Articles, Tutorials and Talks

Notebook Intelligence (NBI) is an AI coding assistant and extensible AI framework for JupyterLab. It uses GitHub Copilot under the hood and is inspired by its design principles. NBI greatly boosts the productivity of JupyterLab users with AI assistance powered by GitHub Copilot.

The article highlights uv's standout feature: the ability to run Python scripts with specific versions and dependencies using a single command, simplifying ad-hoc scripting. This functionality eliminates the need for complex environment setup, making uv more convenient than traditional methods like pip, virtual environments, and pyenv.

Enums are objects, why not give them attributes?

In this post, we will briefly introduce torchtune, the Ascend backend, and demonstrate how torchtune can be used to fine-tune models with Ascend.

The post provides an in-depth comparison of Django and FastAPI, highlighting their distinct approaches. Django excels as an all-inclusive, beginner-friendly framework with robust tools and structure, while FastAPI offers modern features, flexibility, and better async support, catering to experienced developers seeking full control. The choice depends on project requirements and desired developer experience.

If you have a good test suite, you may be able use pytest fixtures to identify memory and other resource leaks.

In this video, we'll learn about caching and how to setup and use Redis in a Django application. We'll touch upon invalidation strategies with Django signals, and the pros/cons of caching.

PyTorch users can learn about JAX in this tutorial that connects JAX concepts to the PyTorch building blocks that they’re already familiar with.

Interesting Projects, Tools, and Libraries

A powerful tool for automated LLM fuzzing. It is designed to help developers and security researchers identify and mitigate potential jailbreaks in their LLM APIs.

Multi-modal modular data ingestion and retrieval.

TabPFN is a foundation model for tabular data that outperforms traditional methods while being dramatically faster.

A family of state-of-the-art Transformer-based audio codecs for low-bitrate high-quality audio coding.

Pyper is a flexible framework for concurrent and parallel data-processing, based on functional programming patterns.

A lightning-fast Zig-powered event loop for Python's asyncio.

A sandbox environment designed for loading, running and profiling a wide range of files, including machine learning models, ELFs, Pickle, Javascript and more.

New Releases

Upcoming Events and Webinars

There will be following talks

  • Popular Python Packages Series - "uv"

  • Peaks, Valleys, and Python: Pipelining Biochemical Data Processing with hplc-py

  • Cosmograph for Python — a new library for visualizing massive network graphs and machine learning embeddings

  • DBOS Transact: Ultra-Lightweight Durable Execution for Python

There will be following talks

  • An introduction to Event Sourcing in Python

  • Applied computer vision: object detection and classification

There will be a talk, Event Sourcing and Event Modeling: Unleash the Power of Your Applications.

There will be a talk, Building an LLM-backed chatbot with Chainlit.

There will be following talks

  • 10x Easier Development for Spark and Python using Databricks Connect!

  • Orchestrating and Scaling Marketing Campaigns using Databricks & MLflow

There will be following talks

  • Notion2Pandas - A new python package to import Notion Database into Pandas framework and vice-versa

  • Beyond Deployment: Harnessing Open-Source Tools for Continuous Model Monitoring and Reliability

There will be following talks

  • Developing AI Products for the Healthcare Market: From idea to Impact

  • Writing Libraries for Any Dataframe With Narwhals

There will be following talks

  • SURE: A New Privacy and Utility Assessment Library for Synthetic Data

  • Going beyond traditional software playbook to build an effective data department

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