Eric Snow and Anthony Shaw discuss the exciting developments in Python, such as sub-interpreters, Faster CPython, async work, and the adoption of typing. They explore the concept of subinterpreters in Python processes, highlighting the benefits of isolation and enabling concurrency. The discussion also touches on consolidating global state, using sub interpreters as an API for concurrent futures, managing Python processes with sub interpreters, and implementing multi-phase init in extension modules to support sub-interpreters in Python.

Python's popularity stems from its ease of use and appeal to non-developers. Now, Python is being integrated into Excel, making it more accessible for a wider audience. Dr. Sarah Kaiser discusses the benefits, challenges, and potential of Python in Excel. They explore data manipulation, collaboration, and the limitations of package installation. The integration of AI features and graph generation using Python in Excel is also highlighted. The episode concludes with sponsor acknowledgments and recommendations for Python developer resources.

Mark Russinovich, CTO of Microsoft Azure, provides a deep look into Azure's data centers and the challenges of running code on their extensive network of servers. Topics discussed include ARM in the data center, optimization techniques, server cooling methods, and the impact of AI on product offerings.

Sydney Runkle, a successful young coder, shares her blueprint for success in the Python space. Topics include exploring the Pydantic library, learning to code expectations and error handling, understanding and working with programs, benefits of taking online courses, the supportive Python community, and a discussion on the coding tool Black and its compatibility.

In this special crossover episode, topics include the release of Hatch v1.8, a flexible service locator for Python called svcs, the results of the Steering Council 2024 term election, and when to use Python protocols in projects. The hosts also discuss PyApp, a tool for distributing Python projects, and express disappointment over selling their dream project for a low price.

Jim Crist-Harif, data exchange framework creator, discusses his super fast data modeling and validation framework called msgspec. They compare it to Python's native classes and APIs like Pydantic and Pidantic. They explore the benefits of using classes for validation in message parsing and discuss challenges in working on hobby projects. The chapter also dives into optimizing message parsing for performance and extending msgspec with new types.

Python expert Brett Cannon joins the show to discuss Python's sweet language features. They cover topics such as attribute access, binary arithmetic operations, and the import statement. They also touch on asynchronous features, memory optimization with slots and data classes, and the complexities of subtraction in Python. The conversation explores optimizations, Python imports, and the importance of specifying modules. Check out Brett's blog series on syntactic sugar for a deeper dive into Python's inner workings.

See the full show notes for this episode on the website at talkpython.fm/440

Wolf Vollprecht and Ruben Arts, developers of the pixi project, discuss their high-performance package manager for Python. They explore the future of Python packaging, the importance of reproducibility, and the functionality of Pixi. Topics also include the Pixi task system, managing dependencies, stability of Pixie, and their approach to package management.

Learn about the latest upgrades and releases of JupyterLab 4 and Jupyter notebook 7. Representatives of Quantstack discuss their work on various aspects of Jupyter. Discover the origin and development of Jupyter Lab and the improvements in JupyterLab 4 and notebook 6 releases. Discussion on the improvements made to JupyterLab 4 and Jupyter 7 releases, including the adoption of Code Mirror 6, sponsor advertisement for Python Tutor, and the new UI for settings in JupyterLab.