Explore >> Select a destination
|
You are here 
|
tomaugspurger.net | ||
| | | | |
blog.reviewnb.com
|
|
| | | | | Let's look at all the tools you can leverage to make notebooks play nicely with modern version control systems like git... | |
| | | | |
www.peterbaumgartner.com
|
|
| | | | | Recently I've been using Quarto to generate HTML reports to share with stakeholders and I'd like to share a workflow and configuration that has worked for me. Background Most of my programming I do in VSCode. A typical workflow involves using an IPython REPL for exploratory coding, organizing commonly used code into a package, and creating CLI functions with typer as an abstraction for common tasks. This approach solves 90% of my problems on data science projects and gives me a replicable workflow that's easily modified. | |
| | | | |
vickiboykis.com
|
|
| | | | | 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. | |
| | | | |
www.softdevtube.com
|
|
| | | Programming history is filled with bugs that turned out to be features and limitations that pushed developers to make even more interesting products. We'll journey through code that was so 'bad' it was actually good. Along the way we'll look at the important role failure plays in learning. Then we'll tame our inner perfectionists and | ||
