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 unifies multiple existing open source math libraries and packages. It integrates with Octave, Scilab, Maxima, etc. It also integrates well with LaTeX... you can take results, format them as TeX and also render them.
Its objective is to be a replacement for Maple, Mathematica and MATLAB, which are prohibitively expensive for many people. As such, once it's installed it comes with batteries included and you can easily share workbooks that others can run without falling into a DevOps-like situation.
The DSL that is offers can be more convenient than Python.
> If you are using this on the regular, I'm curious if you have tried Julia or Mathematica, if so why do you use Sagemath over those alternatives?
Sagemath has pure math stuff. Julia does not. Sagemath can do lots of cool symbolic calculations like rings, quotient rings, algebraic curves, etc. Mathematica has some of this functionality but it's not free.
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?
Sure. I do algorithm development at a biotech company, it is 100% computational work. I am not a software developer by training, my background is in mathematics.
That will be interesting. Happy to test and share feedback. Previously, I was a part of the DataSpell and PyCharm team building notebook support.
Now working with dstack, where we support dev environments and super interested in remote support.
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.