Is it possible to convert .scala to .ipynb notebook? I have been looking through the internet to find a converter or a code but, to no avail none is showed
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has someone encountered tweaking preview for jupyter notebook files in github ?
It's actually much faster than on this gif and makes it's impossible to read anything
I would need to programmatically check that I am running code in a jupyter notebook from Julia. One way would be using
isdefined(Main, :IJulia)
However this does not work for notebooks within vscode since they are run from outside IJulia is there a check that would work in this case as well?
What about #__FILE__ this yields REPL[_] in Julia REPL, In[_] in Jupyter and "/path/to/file.jl#==#hashocde" in Pluto so the test could be:
match(r"^In\[[0-9]*\]$", #__FILE__) != nothing
and in VSCode:
so you can check if the file ends with ".ipynb" if you want to find VSCode. Moreover: isdefined(Main, :VSCodeServer) yields true if you run from VSCode.
I uploaded my first Jupyter Notebook to Github here:
https://github.com/Athelian/OkCupid/blob/master/OkC%20Analysis.ipynb
But I cannot figure out how to get syntax highlighting to display in the preview after clicking the link. I've noticed others don't have this issue when they upload .ipynb files.
Is there any way to get it display like a real notebook?
Probably a silly question, but I couldn't find it. Visual Studio Code editor has a really nice way to work with Jupyter Notebooks. I can edit the cells directly in vscode and run them. Now it would be easy to work with version control.
But I couldn't find a way to convert it back to a Notebook! How do I generate a notebook back from the generated python file?
I understand that the notebook wouldn't have the output cells in it.
There is an option in the interactive Python window that has the notebook output:
This is really cool, now you can work in a Python file and have a really nice interface with your version configuration system (Git).
Yes, it was a silly question :-)
The Jupytext library supports the percent-based cell format used by VSCode-Python, as well as other text-based notebook interchange formats:
https://github.com/mwouts/jupytext
If you need more control over how conversion to ipynb is done (or you need to have cross-references) then you can give a try to Pandoctools. It can export VSCode *.py documents to any Pandoc output format or to Jupyter notebook.
For example you can create and register Jupyter kernel. For example is can be named "nn". That should be the same kernel that you selected in VSCode (there you select it by path but VSCode still uses installed kernels specs under the hood). Then add hat to the Python file, split document to cells, provide settings and set Markdown cells (commented metadata line would export to pdf instead of ipynb; I recommend to open ipynb in nteract native app):
"""
---
kernels-map:
py: nn
jupyter:
kernelspec:
display_name: nn
language: python
name: nn
pandoctools:
# out: "*.pdf"
out: "*.ipynb"
...
# Markdown section title 1
Some **static** Markdown text.
"""
# %% {echo=False}
import IPython.display as ds
import math
import sugartex as stex
# %% {markdown}
"""
# Markdown section title 2
The quick brown Fox jumps over the lazy dog.
"""
# %%
ds.Markdown(stex.pre(f'''
Some **dynamic** Markdown text with SugarTeX formula: ˎα^˱{math.pi:1.3f}˲ˎ.
It works because of the `Markdown` display option and `sugartex` Pandoc filter.
Acually `stex.pre` is redundant here but it is needed when the text is imported
or read from somewhere instead of being written in the same document.
'''))
Then convert the file via pandoctools: drag and drop file to pandoctools shortcut/executable or "open with" pandoctools executable.
Also see:
Two introduction articles are at the beginning of this README,
examples of input to output conversion that have cross-references!
how to use Pandoctools and it's CLI,
how to use Knitty that collects Jupyter outputs and change it's settings.
Use jupytext library:
Install:
pip install jupytext
Now open CMD or internal terminal to the folder with your .py file
Run this:
jupytext --set-formats py:percent,ipynb filename.ipynb
I'm trying to troubleshoot an issue where my Jupyter Notebook can't find an installed module, and I'm surprised that I can't find this basic information anywhere in the documentation. How do I specify where any given instance of Jupyter Notebook should look for modules?
A possibly related question: When I use jupyter --path, I see a listing of directories under the "data" heading. Is this where Jupyter looks for modules, and if so, what file do I edit to change it?
Edit I'm starting to understand, and I think I asked the wrong question. Jupyter loads a Python interpreter, and the interpreter is what deals with modules. How a Python interpreter finds modules is well-covered territory, but I still don't understand the first part. So, I should have asked, "How does Jupyter determine which Python executable to use?"