org-mode
RCall.jl
Our great sponsors
org-mode | RCall.jl | |
---|---|---|
34 | 8 | |
330 | 309 | |
- | 1.3% | |
9.6 | 5.5 | |
2 days ago | about 2 months ago | |
Emacs Lisp | Julia | |
GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
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.
org-mode
- DONE tasks show up in Org Agenda, but [X] don't
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Guide to Org Cite
It would be even better if you turn appropriate parts of the article into a patch to Org manual. We currently lack detailed description of citations, unfortunately. See https://orgmode.org/worg/org-contribute.html
- New package: Forgecast - cast resources to their forges
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How do I build a filename for org capture purposes?
Yes, this part of my configuration predates the change made in org-capture.el in November of 2016: https://github.com/bzg/org-mode/commit/b89dfaa904d32b645b975ef363d0eb192581408a
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Possible to display errors in src block results?
I quickly looked through ob-python.el. I feel that errors are simply not recognised when parsing python output. Patches are welcome! (see https://orgmode.org/worg/org-contribute.html)
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Footnotes now supported in GitHub Markdown
Org mode has supported footnotes since 2008:
https://github.com/bzg/org-mode/commit/40a149354c4e5992abac4...
- Why does org-mode have so few github stars?
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Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?
Well you could look at the source for org-mode, which does what Jupyter does but in Emacs, and using plain-text files.
RCall.jl
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Makie, a modern and fast plotting library for Julia
I don't use it personally, but RCall.jl[1] is the main R interop package in Julia. You could call libraries that have no equivalent in Julia using that and write your own analyses in Julia instead.
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Making Python 100x faster with less than 100 lines of Rust
You can have your cake and eat it with the likes of
* PythonCall.jl - https://github.com/cjdoris/PythonCall.jl
* NodeCall.jl - https://github.com/sunoru/NodeCall.j
* RCall.jl - https://github.com/JuliaInterop/RCall.jl
I tend to use Julia for most things and then just dip into another language’s ecosystem if I can’t find something to do the job and it’s too complex to build myself
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Interoperability in Julia
To inter-operate Julia with the R language, the RCall package is used. Run the following commands on the Julia REPL
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Convert Random Forest from Julia to R
https://github.com/JuliaInterop/RCall.jl may help
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I'm considering Rust, Go, or Julia for my next language and I'd like to hear your thoughts on these
If you need to bindings to your existing R packages then Julia is the way. Check out RCall.jl
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Julia 1.6: what has changed since Julia 1.0?
You can use RCall to use R from Julia: https://github.com/JuliaInterop/RCall.jl
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Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?
I worked with R and Python during the last 3 years but learning and dabbling with Julia since 0.6. Since the availability of [PyCall.jl] and [RCall.jl], the transition to Julia can already be easier for Python/R users.
I agree that most of the time data wrangling is super confortable in R due to the syntax flexibility exploited by the big packages (tidyverse/data.table/etc). At the same time, Julia and R share a bigger heritage from Lisp influence that with Python, because R is also a Lisp-ish language (see [Advanced R, Metaprogramming]). My main grip from the R ecosystem is not that most of the perfomance sensitive packages are written in C/C++/Fortran but are written so deeply interconnect with the R environment that porting them to Julia that provide also an easy and good interface to C/C++/Fortran (and more see [Julia Interop] repo) seems impossible for some of them.
I also think that Julia reach to broader scientific programming public than R, where it overlaps with Python sometimes but provides the Matlab/Octave public with an better alternative. I don't expected to see all the habits from those communities merge into Julia ecosystem. On the other side, I think that Julia bigger reach will avoid to fall into the "base" vs "tidyverse" vs "something else in-between" that R is now.
[PyCall.jl]: https://github.com/JuliaPy/PyCall.jl
[RCall.jl]: https://github.com/JuliaInterop/RCall.jl
[Julia Interop]: https://github.com/JuliaInterop
[Advanced R, Metaprogramming] by Hadley Wickham: https://adv-r.hadley.nz/metaprogramming.html
What are some alternatives?
vscode-org-mode - Emacs Org Mode for Visual Studio Code
org-roam - Rudimentary Roam replica with Org-mode
preview-org-html-mode - Emacs minor mode for an (optionally) live preview of Org exports to HTML using Xwidgets.
vim-orgmode - Text outlining and task management for Vim based on Emacs' Org-Mode
Makie.jl - Interactive data visualizations and plotting in Julia
elfeed-org - Configure the Elfeed RSS reader with an Orgmode file
org-clock-csv - Export Emacs org-mode clock entries to CSV format.
ox-bb - BBCode export for Org
cmark-gfm - GitHub's fork of cmark, a CommonMark parsing and rendering library and program in C
PyCall.jl - Package to call Python functions from the Julia language
Chain.jl - A Julia package for piping a value through a series of transformation expressions using a more convenient syntax than Julia's native piping functionality.
Dash.jl - Dash for Julia - A Julia interface to the Dash ecosystem for creating analytic web applications in Julia. No JavaScript required.