/explore
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scripter.co | ||
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johnfraney.ca
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| | | | | Poetry, a next-generation Python packaging tool, makes it easy to create and publish a Python package. | |
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vickiboykis.com
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| | | | | When I'm working with Jupyter notebooks, I often want to work with them from within a virtual environment. The general best practice is that you should always use either virtual environments or Docker containers for working with Python, for reasons outlined in this post, or you're gonna have a bad time. I know I have. The workflow is a little long, so I thought I'd document it for future me here. | |
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www.ethanrosenthal.com
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| | | | | I make Python packages for everything. Big projects obviously get a package, but so does every tiny analysis. Spinning up a quick jupyter notebook to check something out? Build a package first. Oh yeah, and every package gets its own virtual environment. Let's back up a little bit so that I can tell you why I do this. After that, I'll show you how I do this. Notably, my workflow is set up to make it simple to stay consistent. | |
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www.andrlik.org
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| | | I've been using uv in my Github Actions workflows for a while now to speed up my runner environment creation, and I wanted to do the same for my publishing workflows. So, I created the following workflow for each of my PyPI packages. | ||
