here_here
jupytext
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
here_here
- Trying to understand an invalid path argument error
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alternate to using setwd to access subfolders.
Ode to the {here} package - Jenny Bryan
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What could would you use to tell rstudio "go to the current folder where this R script file is, and read X .csv file in this folder"? Also, what would you have googled to find this out? Windows laptop
This x1000. Remember kids, if you use setwd(), Jenny Bryan will set fire to your computer
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Is there easier way to change working directory?
You can navigate fairly easy within a project because here is unchanging. Some details: https://github.com/jennybc/here_here
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R Markdown: The Definitive Guide
You can avoid project related issues by using the here package.
https://github.com/jennybc/here_here
jupytext
- The Jupyter+Git problem is now solved
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Do you git commit jupyter notebooks?
Jupytext (https://github.com/mwouts/jupytext) has been designed exactly for this
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The hatred towards jupyter notebooks
jupytext is your friend.
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Edit notebooks in Google cloud
So if you run your own jupyter server, -jupy+text can be a great workflow : it takes your notebook synchronized with other formats (python file, makdown, ...), so you can edit your py/md file with neovim, and refresh the browser to execute the notebook.
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Rant: Jupyter notebooks are trash.
Automatically convert ipynb files to py when saving them on JupyterLab
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Two questions regarding working with jupyter notebooks (git, vim)
I don't use Jupyter so I don't know for sure, but on a quick glance you might want to look at https://github.com/mwouts/jupytext to see if that could help at all.
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JupyterLite is a JupyterLab distribution that runs in the browser
The format is only partially invented, it follows Jupytext [0], but adds support for cell metadata. There is no obvious way to get that in fenced codeblocks, especially with the ability to spread it over multiple lines so it plays well with version control.
One more consideration is that it's not "Markdown with code blocks interspersed", one might as well use plaintext or AsciiDoc.
Of course there are tradeoffs.. I wish I had more time to work on it.
[0]: https://github.com/gzuidhof/starboard-notebook/blob/master/d...
[1]: https://github.com/mwouts/jupytext
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Many write research papers in R Markdown - What is the alternative setup in Python?
Using jupytext (allows you to open .md files as notebooks) + jupyter gives you pretty much the same experience. The main issue is that the cell's output will be discarded. To fix it, you can use ploomber to generate an output HTML, so the workflow goes like this:
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Jupyter Notebooks.
First, the format. The ipynb format does not play nicely with git since it stores the cell's source code and output in the same file. But Jupyter has built-in mechanisms to allow other formats to look like notebooks. For example, here's a library that allows you to store notebooks on a postgres database (I know this isn't practical, but it's a great example). To give more practical advice, jupytext allows you to open .py files as notebooks. So you can develop interactively but in the backend, you're storing .py files.
What are some alternatives?
rmarkdown - Dynamic Documents for R
jupyter - An interface to communicate with Jupyter kernels.
ISLR - Introduction to Statistical Learning
Neptune.jl - Simple (Pluto-based) non-reactive notebooks for Julia
sagemaker-run-notebook - Tools to run Jupyter notebooks as jobs in Amazon SageMaker - ad hoc, on a schedule, or in response to events
nbdev - Create delightful software with Jupyter Notebooks
papermill - 📚 Parameterize, execute, and analyze notebooks
nbdime - Tools for diffing and merging of Jupyter notebooks.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
vim-ipython-cell - Seamlessly run Python code in IPython from Vim
jupyterlite - Wasm powered Jupyter running in the browser 💡