So I just learned they're not laptops.
Estimating Number of Jupyter Notebooks on Github
101–110 of 135 posts
Re: Estimating Number of Jupyter Notebooks on Github
#102Earlier quoted context omitted.
I think the file extension scraped on Github is only .ipynb, which is only python notebooks right?
I think most people save under this extension even if they are using a different kernel (i.e. they are running R, Julia, Matlab, etc. code in the notebook).
Yeah so its mostly a split between Jupyter and R Studio - but Jupyter can mean different languages
Re: Estimating Number of Jupyter Notebooks on Github
#103If you ever put notebooks in source control, you owe it to yourself to try the text-based notebooks supported in Visual Studio Code[1]. They're round-trippable with real (i.e. browser-based) notebooks, yet are much better for collaboration, diffing, and editing. [1] https://code.visualstudio.com/docs/python/jupyter-support
The R ecosystem also has a text-based notebook format that they call R Markdown, with a long lineage going back to the TeX days. It never caught on outside of the R community, but the format itself is language-agnostic. https://rmarkdown.rstudio.com/
I believe people underestimate what can be done in R/RStudio these days because they haven't been exposed to it.
R Markdown and its derivative are such great tools. I would also suggest xaringan if you want to present your work on a big screen.
Re: Estimating Number of Jupyter Notebooks on Github
#104OP and Founder of Kyso here - we built Kyso to make it easier to blog your notebooks to the public and also to make them easier to share in teams. The linked post is actually a Jupyter notebook itself - analysing the number of notebooks on Github. A key element with Kyso is that the code is hidden by default to make it readable to non-technical people but you can click on the "code hidden" button on the top right to…
I should not that anyone can contact me at eoin [at] kyso.io
Re: Estimating Number of Jupyter Notebooks on Github
#105So I just learned they're not laptops.
This comment made my day!
Re: Estimating Number of Jupyter Notebooks on Github
#106If you ever put notebooks in source control, you owe it to yourself to try the text-based notebooks supported in Visual Studio Code[1]. They're round-trippable with real (i.e. browser-based) notebooks, yet are much better for collaboration, diffing, and editing. [1] https://code.visualstudio.com/docs/python/jupyter-support
The jupyter support in VSCode is working very well.
I submitted this a week ago, but too bad nobody cared. https://news.ycombinator.com/item?id=19794865
Re: Estimating Number of Jupyter Notebooks on Github
#107In the same spirit as “Effective Java” and “Effective C++” we need to have a book entitled “Effective Jupyter Notebooks”. Here are some of my items below. Maybe this sub-thread can come up with an outline for this book. Item #1 Writing a notebook is foremost an exercise in expository writing. Make sure the writing is high quality is the first objective when writing a notebook. This is the Knuth’s literate programming…
See also "computational essay"[1]. It is written with Mathematica notebooks in mind, but many of the ideas carry over to Jupyter notebooks. [1] https://blog.stephenwolfram.com/2017/11/what-is-a-computatio...
and a more jupyter-centric agree/reply by Tony Hirst:
https://blog.ouseful.info/2017/11/15/programming-meh-lets-te...
Re: Estimating Number of Jupyter Notebooks on Github
#108On the topic of Jupyter Notebooks, Is there something similar to a paid version of Google's CoLab? CoLab is so awesome for creating prototypes and even better since it's free. However, there is no paid alternative that I have seen. I do not want to have to deal with setting up my own VM or server. The way that CoLab is perfect for what I need.
Gryd and CoCalc
Re: Estimating Number of Jupyter Notebooks on Github
#109Why doesn't this just use the GitHub public dataset available on Google BigQuery to have much more accurate data rather than "scraping GitHub web search results"? https://cloud.google.com/bigquery/public-data/ There are a lot of examples of people analyzing public code on GitHub efficiently for patterns and usages with BigQuery and getting pretty accurate data out of it. https://medium.com/google-cloud/analyzing-go-c…
One limitation of the BigQuery dataset is they only look at repos with a license on them[1], the scraping approach can look at all public repos.
[1] https://github.blog/2017-01-19-github-data-ready-for-you-to-...
Re: Estimating Number of Jupyter Notebooks on Github
#110In the same spirit as “Effective Java” and “Effective C++” we need to have a book entitled “Effective Jupyter Notebooks”. Here are some of my items below. Maybe this sub-thread can come up with an outline for this book. Item #1 Writing a notebook is foremost an exercise in expository writing. Make sure the writing is high quality is the first objective when writing a notebook. This is the Knuth’s literate programming…
Obligatory Joel Grus: slides from his 'I don't like notebooks' talk. He has good follow-up talks too. https://docs.google.com/presentation/d/1n2RlMdmv1p25Xy5thJUh...
...and a well-written response to that by Yihui Xie: https://yihui.name/en/2018/09/notebook-war/
Since Xie's post discusses a "meta" layer above Joel Grus, I recommend people read it before JG. This actually helps one understand the underlying thinking in JG's slides.