The web interface was the main reason I never really used the tool for more than a few test runs. Writing code in the browser combines bad usability and performance with a lack of useful dev tools. Which brings me to the question whether I can edit the code in a text editor as well or I have to write it as shown in the animation. It would be really helpful if there was a shortcut to open the current (code) section in…
Use the qt-console, best of both worlds.
Nbterm: Jupyter Notebooks in the Terminal
61–70 of 76 posts
Re: Nbterm: Jupyter Notebooks in the Terminal
#62Earlier quoted context omitted.
So Notebook Ninja has a flag that means write the notebook and its calculated cells to an html page or some other form that would capture a snapshot at a particular step in the process, and thus be suitable to be served by a web server without being "re-executed" ? Why doesn't nbterm allow for production execution of code ? I thought that was the point of its existence, just that they are done in an terminal window r…
In essence, yes. Ninja is based around the idea of reproducable science: a given execution of a notebook is immutable and accessible consistently. It writes out cell outputs depending on their mimetype (this is included in Jupyter Notebook metadata). It writes out all declared variables, per-cell, and makes them accessible in several formats (for pre-alpha, as JSON objects). It then exposes all of these via our web s…
Re: Nbterm: Jupyter Notebooks in the Terminal
#63Slightly tangent, but has anyone figured out a good solution for version controlling jupyter notebooks? The closest thing that we've found has been to use the notebook percent format in a simple .py file [0][1]. It plays with git much nicer than an .ipynb and it is still interactive enough for rapid prototyping. However, it would be nice to have some first-class support from Jupyter on this. [0] https://jupytext.read…
You can configure so they don't save their output, then the ipynb diffs will be readable.
Re: Nbterm: Jupyter Notebooks in the Terminal
#64Very cool to see this – but will only be successful with great terminal plotting tools. The ones the author mentions like the matplotlib interface clearly won't do[0] due to lack of resolution A perfect use case for unicode plotting [1] (shameless plug) [0] https://github.com/domitry/matascii [1] https://github.com/olavolav/uniplot
Re: Nbterm: Jupyter Notebooks in the Terminal
#65Slightly tangent, but has anyone figured out a good solution for version controlling jupyter notebooks? The closest thing that we've found has been to use the notebook percent format in a simple .py file [0][1]. It plays with git much nicer than an .ipynb and it is still interactive enough for rapid prototyping. However, it would be nice to have some first-class support from Jupyter on this. [0] https://jupytext.read…
Re: Nbterm: Jupyter Notebooks in the Terminal
#66The web interface was the main reason I never really used the tool for more than a few test runs. Writing code in the browser combines bad usability and performance with a lack of useful dev tools. Which brings me to the question whether I can edit the code in a text editor as well or I have to write it as shown in the animation. It would be really helpful if there was a shortcut to open the current (code) section in…
The motivation behind this was to have some basic interaction with existing ipynb files on a remote server without having to run the jupyter server (and set up port forwarding etc.) It's worth noting that the `jupytext.vim plugin is most useful if you're actually not running `jupytext` within jupyter; If you are, you could just directly open the .py or .md files linked to any .ipynb in your editor.
I've used `jupytext.vim` to edit existing notebooks and then run them through `jupyter nbconvert --to notebook --execute`. It's also great for refactoring: moving code from a notebook files into a module, between notebooks, or to create a new notebook as a variation of an existing one.
Re: Nbterm: Jupyter Notebooks in the Terminal
#67Very cool to see this – but will only be successful with great terminal plotting tools. The ones the author mentions like the matplotlib interface clearly won't do[0] due to lack of resolution A perfect use case for unicode plotting [1] (shameless plug) [0] https://github.com/domitry/matascii [1] https://github.com/olavolav/uniplot
Re: Nbterm: Jupyter Notebooks in the Terminal
#68Slightly tangent, but has anyone figured out a good solution for version controlling jupyter notebooks? The closest thing that we've found has been to use the notebook percent format in a simple .py file [0][1]. It plays with git much nicer than an .ipynb and it is still interactive enough for rapid prototyping. However, it would be nice to have some first-class support from Jupyter on this. [0] https://jupytext.read…
Until recently, I also thought this was a major problem. My old solution was to always pair .ipynb files with proper .py modules of the same name, so the .ipynb always starts with `%run foo.py` and just calls functions. However, I recently started using VSCode Insiders the preview release of VSCode, which has amazing support for Jupyter notebooks in the editor. You can use your normally configured linters, auto-forma…
That's an interesting solution. I believe this is similar to what Joel Grus does [0], except %s/jupyter/ipython.
Re: Nbterm: Jupyter Notebooks in the Terminal
#69Slightly tangent, but has anyone figured out a good solution for version controlling jupyter notebooks? The closest thing that we've found has been to use the notebook percent format in a simple .py file [0][1]. It plays with git much nicer than an .ipynb and it is still interactive enough for rapid prototyping. However, it would be nice to have some first-class support from Jupyter on this. [0] https://jupytext.read…
I think jupytext is already as close to "first-class" support as you're going to get. Personally, I'd be happy to see the project included with Jupyter, but you'll have to pester the Jupyter devs for that ;-)
Re: Nbterm: Jupyter Notebooks in the Terminal
#70Slightly tangent, but has anyone figured out a good solution for version controlling jupyter notebooks? The closest thing that we've found has been to use the notebook percent format in a simple .py file [0][1]. It plays with git much nicer than an .ipynb and it is still interactive enough for rapid prototyping. However, it would be nice to have some first-class support from Jupyter on this. [0] https://jupytext.read…
https://nbdev.fast.ai/
FWIW my team uses bitbucket and the PR experience is significantly worse than github/gitlab unfortunately.