🐍📺 In this video course, you'll learn to build professional documentation for a package using MkDocs and mkdocstrings. These tools allow you to generate modern documentation from Markdown files and, more importantly, from your code's docstrings. #python
Building Professional Documentation with MkDocs and mkdocstrings
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Tim Hopper suggests that one obstacle in the way of uv adoption is that AI agents decide on `pip install` when Python projects look like the many pre-uv projects on GitHub. Likewise, I also started my project with conda instead of uv because I was in the habit of doing data science projects. I'm glad I made the switch since I didn't end up using any data science libraries. It has sped up the GitLab CI/CD pipeline for my project because uv sets up the environment faster than conda. Check out Tim's blog post for more details on the forces hindering uv adoption. Will you be using uv for your next project? Have you already started?
Despite the rapid growth and widespread affinity for the uv package manager in Python, a recent analysis indicates the majority of new projects on GitHub aren't using it. It seems like there are a varity of reasons for this: 1. LLMs/coding agents default to pip 2. pip is the recommendation of Python docs and the official Python Packaging User Guide 3. Developer inertia compounded by this being the example seen in many popular repos Check out the blog post in the thread for more thoughts...
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Complete Python Testing Guide by Jan Giacomelli is out 🚀 Learn how to write better tests with your AI agents to deliver better software faster. Including agent files - CLAUDE .MD and .cursorrules https://lnkd.in/ecD3e9_8
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