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- Python Weekly (Issue 695 April 17 2025)
Python Weekly (Issue 695 April 17 2025)
Rahul Chaudhary
April 17, 2025
Welcome to issue 695 of Python Weekly. Let's get straight to the links this week.
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News
PEP 750 introduces template strings (t-strings), a new string literal type in Python 3.14 that generalizes f-strings by producing a Template object containing both the string parts and their interpolated expressions before evaluation. This allows safer and more flexible string processing, enabling use cases such as domain-specific languages, safer SQL or HTML templating, and structured logging by separating the template structure from its runtime values.
Articles, Tutorials and Talks
This video offers a beginner-friendly, step-by-step guide to training a large language model from scratch. It covers essential topics such as data preparation, tokenization, model selection, and fine-tuning, providing practical insights for those interested in customizing LLMs for specific applications.
This video explores the inner workings of Jupyter with contributors Afshin Darian and Sylvain Corlay, diving into its architecture and execution protocols. It also discusses Jupyter's evolution from a notebook interface to a powerful framework for interactive, collaborative applications.
This post highlights 14 advanced Python features that go beyond basic syntax, focusing on concepts like metaprogramming, decorators, and optimization techniques. The article targets intermediate-to-advanced developers seeking to deepen their understanding of Python's powerful but less commonly used capabilities.
A deep dive into the transformer architecture and how to implement it from scratch in Python.
This course teaches robust data ingestion techniques using Python, focusing on API extraction, schema management, and scalable workflows. It’s designed to help engineers build reliable pipelines with modern tools like dlt, covering incremental loading, data normalization, orchestration, and even LLM-assisted automation.
A quick-start guide to create a web map with images, using the Python-based Django web framework, leveraging its GeoDjango module, and Pillow, the Python imaging library, to extract GPS information from images.
This video explains Git concepts such as merging, rebasing, and fast-forwarding through a practical FastAPI project example, using GitKraken to visualize and clarify these workflows. The video also compares GitFlow and trunk-based development, discussing their advantages and best use cases for managing branches and releases effectively.
This post highlights how to use GitHub Models, which offers free, high-quality AI models, with popular Python AI frameworks by leveraging its OpenAI-compatible endpoints. It provides code examples for frameworks like AutoGen, LangGraph, and Llamaindex, showing how to connect them to GitHub Models using an API key and base URL.
A series of presentations and talks from the Conf42 Python 2025 conference.
Interesting Projects, Tools, and Libraries
An open protocol enabling communication and interoperability between opaque agentic applications.
A simple CLI to help you remember commands.
Turn docstrings into LLM-functions.
mcp-use is the easiest way to interact with mcp servers with custom agents.
PDF craft can convert PDF files into various other formats. This project will focus on processing PDF files of scanned books.
A security scanning tool for MCP servers.
A Real-time interactive world model on Minecraft
A CLI tool for threat modeling and visualizing AI agents built using popular frameworks like LangGraph, AutoGen, CrewAI, and more.
Open Source Version Of Generating BrainRot Videos from reddit url.
An open and fair framework for everyone to build AI agents equipped with powerful skills. Launch your agent, improve the world, your wallet, or both!
Upcoming Events and Webinars
There will be following talks
Beyond LEGB, LEGBI
Instructor instructing instructors (Pydantic'ly)
There will be a talk, What HTMX and Web Components taught me about Python.
There will be a talk, Introduction to using SQL in Python.
There will be following talks
AI vs. Bureaucracy: How Did We Safely Automate Government Reports?
Traffic signal control using reinforcement learning
There will be following talks
Graph Neural Networks: Successes and Challenges in the Analysis of Energy Grids
It's RAG time: Turn your Docs into an Interactive Knowledge Base with the triple O combo (Onyx, Ollama, Open WebUI)
How Bayesian thinking helps me navigate uncertainty as a leader?
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