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News & links about Python programming.
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How we made Python's packaging library 3x faster

Henry Schreiner and Damian Shaw significantly improved the performance of the Python packaging library by using new profiling tools to eliminate redundant regular expressions. The update delivers speed increases up to 5x for version filtering which helps resolve dependencies much faster within the Python ecosystem.

https://iscinumpy.dev/post/packaging-faster/
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Supercharging LLMs: Scalable RL with torchforge and Weaver

PyTorch has introduced torchforge and Weaver, a new open-source stack designed to simplify and scale reinforcement learning for large language models across hundreds of GPUs. The system uses Weaver to provide reliable reward signals without human annotations, while torchforge provides the native primitives to manage complex distributed coordination and fault tolerance.

https://pytorch.org/blog/supercharging-llms-scalable-rl-with-torchforge-and-weaver/
mealie-recipes / mealie

Mealie is a self hosted recipe manager and meal planner with a RestAPI backend and a reactive frontend application built in Vue for a pleasant user experience for the whole family. Easily add recipes into your database by providing the url and mealie will automatically import the relevant data or add a family recipe with the UI editor

https://github.com/mealie-recipes/mealie
Rust-powered FM-index for fast substring search

High-performance FM-index powered by Rust, enabling fast substring search and count/locate queries.

https://pypi.org/project/fm-index/
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Can LLMs translate Polars code to SQL?

Th post explores how large language models can translate natural language and Polars DataFrame expressions into equivalent SQL queries, bridging Python-centric data manipulation and SQL for analytics. It demonstrates how combining Polars’ in-memory performance with LLMs can help users leverage familiar SQL patterns without writing raw SQL themselves.

https://labs.quansight.org/blog/llm_polars_to_sql
Opticol

Optimized collections (opticol) for Python. This package provides memory-efficient, slot-based implementations of Python's standard collection types.

https://github.com/lessico/opticol/
Learn NumPy in 40 Minutes

The video introduces the core concepts of NumPy and shows how its array operations form the foundation of numerical computing in Python. It emphasizes why NumPy is a must-learn tool for data science, AI, machine learning, and scientific workflows.

https://www.youtube.com/watch?v=zI5ducyfyNc
django-polymorphic - Polymorphic models in Django

The video explains Django model inheritance and polymorphic models, showing how django-polymorphic returns the correct subclass types when querying a base model through the ORM. It also covers Django Admin support and integrations with other Django ecosystem packages to make polymorphic models easier to manage.

https://www.youtube.com/watch?v=d8MC2FQ_nqU