Python 3.14 Released and Other Python News for November 2025

Python 3.14 is out now, bringing t-strings, deferred annotations, better error messages, and plenty more to explore. As developers start adopting the new version, Python 3.15 begins its alpha phase, and Python 3.9 officially retires. Meanwhile, Django 6.0 enters beta, new PEPs propose lazy imports and changes to the assert syntax, and the PSF makes waves with a notable funding decision. Here’s what’s been happening in the world of Python! Python Releases Last month’s headline news was the release of […]

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When industry knowledge meets PIKE-RAG: The innovation behind Signify’s customer service boost

As a world leader in connected LED lighting products, systems, and services, Signify (formerly Philips Lighting) serves not only everyday consumers but also a large number of professional users who have stringent requirements for technical specifications and engineering compatibility. Faced with thousands of product models, complex component parameters, and technical documentation spanning multiple versions, delivering accurate, professional answers efficiently has become  

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Quiz: Python MarkItDown: Convert Documents Into LLM-Ready Markdown

Interactive Quiz ⋅ 8 QuestionsBy Leodanis Pozo Ramos Share In this quiz, you’ll test your understanding of the Python MarkItDown: Convert Documents Into LLM-Ready Markdown tutorial. By working through this quiz, you’ll revisit how to install MarkItDown, convert documents to Markdown for your LLM workflows, and more. The quiz contains 8 questions and there is no time limit. You’ll get 1 point for each correct answer. At the end of the quiz, you’ll receive a total score. The maximum score […]

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Python MarkItDown: Convert Documents Into LLM-Ready Markdown

The MarkItDown library lets you quickly turn PDFs, Office files, images, HTML, audio, and URLs into LLM-ready Markdown. In this tutorial, you’ll compare MarkItDown with Pandoc, run it from the command line, use it in Python code, and integrate conversions into AI-powered workflows. By the end of this tutorial, you’ll understand that: You can install MarkItDown with pip using the [all] specifier to pull in optional dependencies. The CLI’s results can be saved to a file using the -o or […]

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Magentic Marketplace: an open-source simulation environment for studying agentic markets

Autonomous AI agents are here, and they’re poised to reshape the economy. By automating discovery, negotiation, and transactions, agents can overcome inefficiencies like information asymmetries and platform lock-in, enabling faster, more transparent, and more competitive markets. We are already seeing early signs of this transformation in digital marketplaces. Customer-facing assistants like OpenAI’s Operator and Anthropic’s Computer Use can navigate websites and complete purchases.  

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Building UIs in the Terminal With Python Textual

Have you ever wanted to create an app with an appealing interface that works in the command line? Welcome to Textual, a Python toolkit and framework for creating beautiful, functional text-based user interface (TUI) applications. The Textual library provides a powerful and flexible framework for building TUIs. It offers a variety of features that allow you to create interactive and engaging console applications. In this video course, you’ll learn how to create, style, and enhance Textual apps with layouts, events, […]

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RedCodeAgent: Automatic red-teaming agent against diverse code agents

Introduction Code agents are AI systems that can generate high-quality code and work smoothly with code interpreters. These capabilities help streamline complex software development workflows, which has led to their widespread adoption. However, this progress also introduces critical safety and security risks. Existing static safety benchmarks and red-teaming methods—in which security researchers simulate real-world attacks to identify security vulnerabilities—often fall short when evaluating code agents. They may fail to detect emerging real-world risks, such as the  

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Quiz: A Close Look at a FastAPI Example Application

Interactive Quiz ⋅ 10 QuestionsBy Martin Breuss Share In this quiz, you’ll test your understanding of the FastAPI example project that can shuffle lists, pick random items, and generate random numbers. By working through this quiz, you’ll revisit how path parameters and type hints enable automatic validation, how request bodies model data, how async endpoints improve performance, and how CORS allows safe cross-origin requests. To go deeper, read A Close Look at a FastAPI Example Application. You can also review […]

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A Close Look at a FastAPI Example Application

Now that you have a working FastAPI application, it’s time to add some functionality to your API. You’ll add endpoints that demonstrate different FastAPI features while creating a randomizer API. Each endpoint you create will showcase a different aspect of FastAPI, from handling dynamic URLs to processing complex request data. Declare Path and Query Parameters With Types FastAPI’s path parameters allow your API to handle dynamic URLs. For your randomizer API, you’ll create an endpoint that generates random numbers within […]

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Speed Up Python With Concurrency

Concurrency is the act of having your computer do multiple things at the same time. If you’ve heard a lot of talk about asyncio being added to Python but are curious how it compares to other concurrency methods or are wondering what concurrency is and how it might speed up your program, you’ve come to the right place. In this course, you’ll learn the following: How I/O bound programs are effected by latency Which concurrent programming patterns to use What […]

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