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- Python Weekly (Issue 723 November 20 2025)
Python Weekly (Issue 723 November 20 2025)
Rahul Chaudhary
November 20, 2025
Welcome to issue 723 of Python Weekly. Let's get straight to the links this week.
74% of Companies Are Seeing ROI from AI.
Incomplete data wastes time and stalls ROI. Bright Data connects your AI to real-time public web data so you launch faster, make confident decisions, and achieve real business growth.
Articles, Tutorials and Talks
The Hachi project is an end-to-end, fast, self-hosted semantic and metadata search engine designed to enable comprehensive search across all types of media by extracting independent information from distributed personal data. It prioritizes minimal external dependencies, hackability, and the integration of machine learning models to fuse deterministic and semantic attributes, aiming for a highly flexible and extensible personal search solution.
The video explains the real learning curve of Python from beginner basics to writing professional, testable code. It covers mastering Python fundamentals, writing Pythonic code, understanding types and abstractions, designing better software, and incorporating testing for maintainable and scalable Python development.
Learn how to use UUIDv7 today with stable releases of Python 3.14, Django 5.2 and PostgreSQL 18. A step by step guide showing how to generate UUIDv7 in Python, store them in Django models, use PostgreSQL native functions and build time ordered primary keys without writing SQL.
Learn how to implement and use the floodfill algorithm in Python.
The article highlights Nano Banana’s capability for exceptionally nuanced AI image generation, leveraging a large 32,768-token context window to enable highly detailed and controlled prompts. These features allow for precise adjustments and creative experimentation, pushing the boundaries of prompt engineering in AI art.
The article provides an introduction to Graph Neural Networks (GNNs), explaining how graphs are represented for machine learning and introducing the mathematical intuition behind GNNs. It covers key concepts such as nodes, edges, and the message-passing mechanism, helping readers understand how GNNs learn from graph-structured data.
The article presents a method for AI agents to progressively load capabilities on-demand through a three-level system—metadata discovery, detailed documentation loading, and executable tool registration. This approach significantly reduces token usage in large language model contexts, enhances extensibility, and improves efficiency by isolating skills in subprocesses and using keyword-based relevance detection to optimize what gets loaded during conversations.
Heartbeats in distributed systems are periodic signals sent by nodes to indicate they are alive and functioning, enabling monitoring systems to detect failures or unresponsiveness promptly. These heartbeats help maintain system health, support fault detection, load balancing, and consistency by allowing systems to respond timely to node failures or network partitions.
The article describes a seamless approach to upgrading a major version of Aurora RDS Postgres from v13 to v16 alongside a Django application model upgrade. It highlights challenges like long migration times and schema rewrites, and outlines a strategy using logical replication with schema adjustments, custom publications, subscription management, and sequence synchronization to minimize downtime and enable an almost seamless switchover.
Interesting Projects, Tools, and Libraries
Ax is an accessible, general-purpose platform for understanding, managing, deploying, and automating adaptive experiments.
A Python toolkit for hardware engineering.
Use mkslides to easily turn markdown files into beautiful slides using the power of Reveal.js!
RLinf is a flexible and scalable open-source infrastructure designed for post-training foundation models (LLMs, VLMs, VLAs) via reinforcement learning.
Fully automatic censorship removal for language models.
Recovering the Visual Space from Any Views.
A character-level language diffusion model trained on Tiny Shakespeare.
Self-contained Python distribution for Linux.
New Releases
This release includes the following announcements:
Add Copilot Hover Summaries as docstring
Localized Copilot Hover Summaries
Convert wildcard imports Code Action
Debugger support for multiple interpreters via the Python Environments Extension
Upcoming Events and Webinars
There will be following talks
Forged in Rust, Spoken in Python
Dealing with today's web scraping challenges in Python
In this workshop, we will first study the relationship between an AI Agent and an AI model. Then, by some hands-on exercises, we will learn how to choose the right model for building your own AI Agent; and how to build an AI Agent from scratch.
There will be following talks
Lessons Learned - MCP & Agents @inovexGPT
How applications travel to the end user
There will be following talks
Beyond Human Perception - XR
Graphs on big data: Why don't you use Neo4j?
There will be following talks
Your Model is Confused (And That's a Good Thing): An Intro to Active Learning
Libero: The Insurance Broker’s Best Ally
There will be following talks
Extreme Hail Risk Estimation for Utility-scale Solar Parks
Autocurator: AI-Powered Knowledge Extraction for RAG Systems
There will be a talk, Building a Chat Agent Using Chainlit.
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