Ian Maurer, an expert in building custom GPTs with Python, shares his experience creating customizable chat experiences. Topics include building custom API actions, integrating with OpenAI tools, token price comparisons, managing compute resources, challenges in language models, graph databases, and balancing speed, accuracy, and memory in vector algorithms. Insights on AI in healthcare decision-making and sponsor mentions are also discussed.

Avery Smith from Data Career Jumpstart shares tips on landing your first data job, discusses transitioning into data science, importance of learning SQL and networking, creating personal projects, and using AI tools in programming. The episode covers job requirements, networking strategies, and encouragement for pursuing a career in data science.

Explore data pipelines with Python using Dagster, featuring insights from Pedram Navid. Learn about building efficient data pipelines, orchestrating automation, optimizing deployments with Posit Connect, backfills, partitioning, and popular data tools like DBT, DuckDB, Apache Arrow, and Pollers.

Discover UV, a new lightning-fast Python package tool from Astral that rivals pip. Learn about the benefits of UV's speed and efficiency, the evolution of Python tools like Roth and the challenges of unexpected success, Python code readability, editor integrations, and the impact of UV on Python packaging tools. Explore the innovation and optimization of the UV Python package, its adoption in companies, and its potential future prospects in the Python ecosystem.

Discover the fully-async Quart framework for Flask and top Quart extensions by Philip Jones. Explore tools like Quart Tasks, Quart Minify, and Quart-CORS for enhanced web development. Learn about rate limiting, data validation, and efficient file uploads to boost website performance with async capabilities.

Discover the world of Django mentorship with the Djangonauts program, featuring insights from former participants turned mentors. Learn about the importance of community support, relationships, and engaging content creation. Explore the transition from participant to mentor roles and the value of engaging with open source projects like Django for career growth and continuous learning.

Exploring the challenges of upgrading APIs, the importance of versioning for smooth transitions, insights on API design principles, handling system behaviors with Neo4j, strategies for versioning web APIs in Python, and recommendations for choosing the right versioning approach.

Explore the limitations of existing Python platforms for web development and learn about Fast UI, a project that enables building responsive web apps using React without JavaScript or npm. Discuss the benefits of Fast UI in terms of focusing on React frontends and enhancing collaboration. Dive into the components and advantages of using Fast UI for building UIs in Python, including form development and component-based architecture. Discover how a team of 500 developers manages a Python mono repo and customizes Fast UI. Delve into challenges of rendering data with React, MIME types, and server-side validation. Learn about usability and the importance of listener contributions to a UI building tool.

Panel of guests discuss their experiences transitioning from Python side projects to full-time open source work. They explore popular libraries and projects like Ruff, Rich, and Textualize, and the challenges of monetization. They also discuss the importance of financial support, crowdfunding platforms, and GitHub sponsors. The speakers share their experiences maintaining projects, handling pull requests, and defining breaking changes. The origin story of Octoprint and attendee experiences at Python events are also discussed.

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.