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Source channel @githubtrending · Post #15513 · Feb 20

#python#agents#claude#cursor#databricks#vibecoding The Databricks AI Dev Kit enhances AI-driven development by providing your coding assistant (Claude Code, Cursor, etc.) with trusted Databricks knowledge and best practices. It includes a Python library, MCP server with 50+ tools, markdown skills teaching Databricks patterns, and a web-based builder app. You can build Spark pipelines, jobs, dashboards, knowledge assistants, and deploy ML models faster and smarter. The benefit is that your AI coding assistant gains direct access to Databricks functionality and patterns, enabling you to develop data and AI applications more efficiently with built-in governance and best practices. https://github.com/databricks-solutions/ai-dev-kit

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djangoproject

@djangoproject · Post #164 · 09/17/2016, 10:20 AM

https://www.buzzfeed.com/andrewkelleher/deep-exploration-into-python-lets-review-the-dict-module?utm_term=.rhDeZBxA8#.bgB5DM0Z9 In this series, we’ll take a look at various modules and pieces of functionality of the #Python language. We’ll look at design choices, their impact, and their evolution. We’ll also look at the design of the language itself and learn about the operations of the interpreter as it parses the language all the way to the main eval loop. Finally, we’ll attempt to give practical takeaways that fall out of a deeper understanding of the language. The #cpython implementation of Python (which is the standard on most machines) has been ported over to GitHub from its home in Mercurial. I think it also had a time under #SVN, but the engineers managed to preserve (for the most part) the commit logs.