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- Python Weekly (Issue 711 August 28 2025)
Python Weekly (Issue 711 August 28 2025)
Rahul Chaudhary
August 28, 2025
Welcome to issue 711 of Python Weekly. We have a packed issue this week. Enjoy it!
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This 90-minute documentary premiers today. It features Guido van Rossum, Travis Oliphant, Barry Warsaw, and many more, and they tell the story of Python’s rise, its community-driven evolution, the conflicts that almost tore it apart, and the language’s impact on... well… everything.
Articles, Tutorials and Talks
The video teaches how to write asynchronous code in Python using AsyncIO with async/await syntax. It covers core concepts like coroutines, tasks, and the event loop, shows how to convert synchronous code to async, and demonstrates performance benefits using real-world examples and animations.
This post demonstrates a powerful Python technique to dynamically patch a function's source code at runtime using compile and exec, enabling flexible AI bots that can generate and execute code within the current environment. While this approach allows unprecedented control and interactivity in AI-driven systems like ToolBot, it raises serious security concerns due to the risk of executing arbitrary code without sandboxing.
This post describes Python CLI tool for verifying assembly programs using symbolic execution with Ghidra pcode semantics. It highlights novel features like embedding formal specifications directly into assembly through macros, handling invariants via control flow graph cuts, and providing detailed verification and countermodel feedback to ensure correctness of assembly code.
Attackers can hide malicious prompts in images that become visible only after being downscaled—tricking AI systems like Gemini CLI and Vertex AI Studio into executing hidden instructions. Trail of Bits demonstrates these “image scaling” exploits and introduces Anamorpher, an open-source tool to craft and test such attacks, while also proposing defenses.
Learn how to use Python environment variables with os.environ, os.getenv, and .env files. Secure your API keys, set variables in Linux, and make your code safer and more adaptable. SPONSOR
The article analyzes the architectural advances from GPT-2 to OpenAI’s new open-weight gpt-oss models, highlighting innovations like Mixture-of-Experts, grouped query attention, and sliding-window layers for efficiency and scaling. He compares these changes with models like Qwen3 and notes how gpt-oss is optimized for reasoning, tool use, and agentic workflows, while remaining memory-efficient and open-source.
This post walks through five common pandas bottlenecks, how to recognize them, and some workarounds you can try on CPU with a few tweaks to your code plus a GPU-powered drop-in accelerator, cudf.pandas, that delivers order-of-magnitude speedups with no code changes.
Obstore is a fast, lightweight Python library for working with object storage—backed by Rust and built for clarity, speed, and interoperability. It’s already being used across cloud-native geospatial tools and supports common workflows out of the box.
The post introduces a new feature coming in pandas 3.0 — the pd.col expression syntax, which allows creating readable, composable column expressions without using opaque lambda functions. This new syntax improves usability by enabling delayed evaluation of column operations, avoids scoping pitfalls of lambdas, and opens the door to more powerful dataframe operations like multi-column manipulations.
PyPI has implemented new security measures to prevent domain resurrection attacks, where expired domains are re-registered by attackers to hijack accounts via password resets. Since June 2025, PyPI has unverified over 1,800 email addresses tied to expiring domains, blocking these addresses from being used for account recovery and enhancing account security.
The video teaches how to write effective and maintainable unit tests in Python, focusing on practical techniques such as mocking, monkey patching, fixtures, and parametrization with pytest. It uses a realistic WeatherService example to demonstrate these concepts, emphasizing best practices for robust testing and improving code quality in production systems.
You can heavily customize your IPython shell experience when using it inside Docker or in a Docker Compose project. Without your personal preferences annoying your teammates!
The video demonstrates building a multi-step, scalable AI research agent in Python using LangGraph. The agent can pull live search data from sources like Google, Bing, and Reddit, aggregate and analyze the information, and provide comprehensive answers, showcasing advanced Python coding, complex architecture, and effective use of APIs like Bright Data and OpenAI GPT. The tutorial covers project setup, architecture, coding, and integration of live web data for a powerful research assistant.
Python namespace packages allow a single package to be split across multiple directories on disk, enabling modular and scalable code organization without requiring an init.py file. They come in two types: explicit (using pkgutil or pkg_resources to extend paths) and implicit (PEP 420–style) namespace packages, but both introduce complexity and potential pitfalls, so many recommend avoiding them if possible.
A guide to migrating from pip-tools to uv in Python projects, focusing on preserving pinned versions.
This article discusses how AI/web crawlers create excessive sessions that push legitimate user sessions out of cache, degrading user experience on sites like e-commerce platforms. It suggests configuring Redis with an LFU (Least Frequently Used) eviction policy, rather than the common LRU (Least Recently Used), to preferentially keep frequently used sessions (like those of real users) while expiring one-time bot sessions, improving cache efficiency and user retention.
The tutorial walks through building a baby version of the Claude Code AI coding agent from scratch in Python, covering creating a reasoning brain, instructions, tools, and memory with a ReAct loop for interactive coding tasks. It also progresses to adding safe code execution, sandboxing, and context management to handle large codebases, enabling the agent to write, test, debug, and iterate code safely and effectively.
Learn Python loops the fun way by rolling dice, casting fireballs, and finally understanding what continue really does.
A Guide to Building and Scaling Production-Ready CUDA Kernels
Instacart’s Maple platform streamlines large-scale LLM processing by automating, monitoring, and scaling language model workflows, enabling efficient personalization and intelligent recommendations for millions of items and users. This infrastructure reduces complexity and cost, making LLM-powered features deployable across Instacart’s grocery platform.
Interesting Projects, Tools, and Libraries
A Frontier Long Conversational Text-to-Speech Model.
MCP Servers are shaping the future of software. MCPMark is a comprehensive, stress-testing benchmark and a collection of diverse, verifiable tasks designed to evaluate model capabilities in real-world MCP use.
A powerful coding agent toolkit providing semantic retrieval and editing capabilities (MCP server & Agno integration)
Parallel thinking for LLMs. Confidence-gated, strategy-driven, offline-friendly.
Agent Laboratory is an end-to-end autonomous research workflow meant to assist you as the human researcher toward implementing your research ideas.
Lemonade helps users run local LLMs with the highest performance by configuring state-of-the-art inference engines for their NPUs and GPUs.
A post-modern terminal file explorer.
Digital twin for async backends: build topologies, simulate traffic, and get per-server and full system latency/throughput insights.
Fully local, temporally aware natural language file search on your pc! even without a GPU. find relevant files using natural language in less than 1 second.
A benchmark for LLMs on complicated tasks in the terminal.
Tensorlake is a Document Ingestion API and a serverless platform for building data processing and orchestration APIs
11 Lessons to Get Started Building AI Agents.
Git Based Memory Storage for Conversational AI Agent.
Build reliable AI and agentic applications with DataFrames.
Upcoming Events and Webinars
There will be following talks
Skrub: Machine Learning with DataFrames
Breaking the Black Box - How to Evaluate Your Agents... in Real Time Too!
From RNNs to Reliable Agents: Context Engineering, Roles, and What 1M-Token Windows Don’t Fix
The Apprenticeship Pathway Into Data Science
There will be following talks
Architecture of the Transformer model
HTMX
Memory Graph: Teaching tool and debugging aid in context of references, mutable data types, and shallow and deep copy
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