Some notes on how to ship fast and why it matters. This is from my perspective as a indie dev and a startup founder, but I think some lessons here for everyone.
When the engineering department of a company is not the major lever in the company's growth this philosophy might be fine. That's the case of many large enterprise and probably many startups too.
When the competitive advantage is not the technology, it is probably smart to make the engineering department dumb.
Clearly that leaves the company exposed to challengers who will outcompete them with technology. But not all markets work like that.
Creating and using virtual environments in Jupyter has always felt a little painful. Now thanks to uv things can be so much better. I've integrated uv into my Jupyter notebook client, Satyrn. It makes quick experiments in a fresh virtual environment so much easier.
Thank you for the advice. I get how this might be better suited for a regular blog post rather than Show HN. I will repost it in a month or so. Hopefully some people might find it interesting.
Great feedback, thank you. I've heard this before. I'm thinking of keeping the default but adding an option in settings to "ask before installation" for users who prefer that behaviour (similar to VS Code).
Thanks! I just used the builtin MacOS screenshot tool to take the screenshots. I used Tailwind to style the page. I really like the default shadow that the "selected window" screenshot adds, but since there are also "selected area" screenshots I decided to take them without the default shadow (by holding option) and then add it in using Tailwind.
The logo was done with ChatGPT and my friend editing it with some graphic design software :)
This project is unrelated to those others. I like the branching code idea tho, would love to have something like that. I'd love it if you could rewind your code execution to a point in time and then play it forward differently. I suppose that would be a pretty big memory overhead tho.
Even as a command line power user, I still wish it were easier to install dependencies while working in a notebook. If I'm working on a project I don't want to have to switch to my terminal if I can solve the problem in one command from my notebook.
With a little careful thought into good UX I don't see why it can't be easy for a beginner at the same time useful to a pro user (and still compatible with any virtual environment).
When I learned to program I was working as a scientist. I was relying on OriginLab (a scientific version of Excel) for my data analysis and it was a real pain. I decided to start using python for analysis and plotting and started with scripts and terminal interactivity, but found it too clunky. Jupyter feels more interactive when you are working with data because you need to explore the data and experiment with data manipulation in a way I found quite natural to do in a notebook.
Since then I've moved into software development where I rely on my IDE for any coding that involves working with more than a few modules. And as I got better working with an IDE I did gravitate toward making a script for certain kinds of tasks where I use to reach for a notebook, but there are still many data analysis tasks that I would much prefer a notebook for.
It's also quite nice to share a notebook with someone to show them how you arrived at your conclusions, and it's nice for them to be able to take your analysis and modify it or test their own ideas on top of yours. Obviously the notebooks are not great for collaboration without some fiddling around with git, but they are still very good for this kind of collaboration.
It can be confusing. The key is that you probably have multiple versions of python installed on your computer (that's normal). Secondly, the default "kernel" in Jupyter was probably not the one you used to install torch.
Satyrn makes it easier to add virtual environments as a kernel, but you still will need to create the virtual environment and install torch there yourself.
That's a really great point you made about how confusing it is to pip install stuff with `!pip` when working in the notebook. Right now Satyrn does not support the `!` commands, but I will add this soon and try to make it so `!pip` works with the expected virtual environment you are working with.
If you'd be happy to share: I'm curious to know what scientific field you work in? Do you do 100% computational work, or is it a mixture of experimental and computational?