PythonHub

Mutmut – Python Mutation Tester https://github.com/boxed/mutmut

Unravelling t-strings PEP 750 introduced t-strings for Python 3.14. In fact, they are so new that as of Python 3.14.0b1 there still isn't any documentation yet for t-strings. As such, this blog post will hopefully help explain what exactly t-strings are and what you might use them for by unravelling the syntax and briefly talking about potential uses for t-strings. https://snarky.ca/unravelling-t-strings/

Python in LibreOffice (LibrePythonista Extension) https://extensions.libreoffice.org/en/extensions/show/99231

Datatune Perform transformations on your data with natural language using LLMs https://github.com/vitalops/datatune

Flowfile Flowfile is a visual ETL tool combining drag-and-drop workflows with the speed of Polars dataframes. Build and analyze data pipelines without code. Perfect for analysts and engineers needing fast, intuitive data processing. Designed to run locally or deploy to production environments. https://github.com/Edwardvaneechoud/Flowfile/

Python Tooling at Scale: LlamaIndex’s Monorepo Overhaul https://www.llamaindex.ai/blog/python-tooling-at-scale-llamaindex-s-monorepo-overhaul

nlweb Building conversational interfaces for websites is hard. NLWeb seeks to make it easy for websites to do this. And since NLWeb natively speaks MCP, the same natural language APIs can be used both by humans and agents. https://github.com/microsoft/nlweb

Machine Learning Prototyping with DuckDB and scikit-learn In this post, we prototype a machine learning workflow using DuckDB for data handling and scikit-learn for modeling. https://duckdb.org/2025/05/16/scikit-learn-duckdb.html

Turning Data into Insight The article demonstrates how to build a flexible, modern data lakehouse architecture using open-source tools like MinIO, Apache Iceberg, Airflow, dbt, Spark, Pandera, and Superset. By integrating these technologies with Docker for easy deployment, it shows how to orchestrate robust data pipelines, ensure data quality, and enable scalable analytics from raw ingestion to interactive dashboards. https://towardsdev.com/turning-data-into-insight-flexible-lakehouse-with-minio-iceberg-airflow-dbt-spark-pandera-409d036e5542

Web Apps for Python Devs with Auto-Generated UI https://davia.ai/

pyfuze pyfuze makes your Python project run anywhere. https://github.com/TanixLu/pyfuze

Juvio UV kernel for Jupyter. https://github.com/OKUA1/juvio

LiveSplat Live Gaussian Splatting for RGBD Camera Streams. https://github.com/axbycc/LiveSplat

I don't like NumPy The author, once a fan of NumPy, now criticizes its complexity and opacity when working with high-dimensional arrays, arguing that common operations often become unreadable and error-prone due to confusing broadcasting, indexing, and function conventions. While NumPy excels at simple cases, the post contends that its design choices—especially around implicit broadcasting and lack of expl... https://dynomight.net/numpy/

muscle-mem A cache for AI agents to learn and replay complex behaviors. https://github.com/pig-dot-dev/muscle-mem

Voice_Extractor Extract voice segments of a target speaker from podcasts - Useful for creating speech datasets. https://github.com/ReisCook/Voice_Extractor

sre-bot A Google Agent Development Kit (ADK) powered assistant designed to help Site Reliability Engineers (SREs) with operational tasks and monitoring, particularly focused on Kubernetes interactions. https://github.com/serkanh/sre-bot

OpenThinkIMG OpenThinkIMG is an end-to-end open-source framework that empowers LVLMs to think with images. https://github.com/zhaochen0110/OpenThinkIMG

Dagster - Data Orchestration and Pipelines with Python & DAGs This video is a practical introduction to using Dagster for Python-based data orchestration, covering core concepts like assets, definitions, scheduling, and the Dagster UI. Through hands-on examples—including building a pipeline with Polars and DuckDB—the tutorial demonstrates how to define, manage, and automate complex data workflows in modern data engineering. https://www.youtube.com/watch?v=sKqDq4TFbmY

Modern Python Boilerplate - good package basic structure https://www.reddit.com/r/Python/comments/1krsxut/modern_python_boilerplate_good_package_basic/