rmarkdown
Pluto.jl
Our great sponsors
rmarkdown | Pluto.jl | |
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38 | 78 | |
2,782 | 4,847 | |
0.9% | - | |
7.6 | 9.4 | |
23 days ago | about 21 hours ago | |
R | JavaScript | |
GNU General Public License v3.0 only | MIT License |
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rmarkdown
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Pandoc
I'm surprised to see no one has pointed out [RMarkdown + RStudio](https://rmarkdown.rstudio.com) as one way to immediately interface with Pandoc.
I used to write papers and slides in LaTeX (using vim, because who needs render previews), then eventually switched to Pandoc (also vim). I eventually discovered RMarkdown+RStudio. I was looking for a nice way to format a simple table and discovered that rmarkdown had nice extensions of basic markdown (this was many years ago so maybe that is incorporated into vanilla markdown/pandoc).
The RMarkdown page claims:
> R Markdown supports dozens of static and dynamic output formats including HTML, PDF, MS Word, Beamer, HTML5 slides, Tufte-style handouts, books, dashboards, shiny applications, scientific articles, websites, and more.
...which I think is largely due to using pandoc as the core generator.
RStudio shows you the pandoc command it runs to generate your document, which I've used to figure out the pandoc command I want to run when I've switched to using pandoc directly.
This is a bit of a "lazy" way to interact with pandoc. Maybe the "laziest" aspect: when I get a new computer, I can install the entire stack by installing Rstudio, then opening a new rmarkdown document. Rstudio asks whether I'd like to install all the necessary libraries -- click "yes" and that's it. Maybe that sounds silly but it used to be a lot of work to manage your LaTeX install. These days I greatly favor things that save me time, which seems to get more precious every year.
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Weâre Washington Post reporters who analyzed Googleâs C4 data set to see which websites AI uses to make itself sound smarter. Ask us Anything!
We used R Markdown for cleaning and analysis, creating updateable web pages we could share with everyone involved. Similarwebâs categories were useful, but too niche for us. So we spent a lot of time recategorizing and redefining the groupings. We used the token count for each website â how many words or phrases â to measure itâs importance in the overall training data.
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Generating PDF đ with Python đ
R Markdown / Quarto https://quarto.org/ https://rmarkdown.rstudio.com/ ; can dynamically generate a document and compile it to HTML, PDF, others
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PYTHON CHARTS: the Python data visualization site with more than 500 different charts with reproducible code and color tools
Hi! At this moment I'm not opening the source code, but I can explain you the tech used. This site is based on another site I created before named https://r-charts.com/ and it was created with blogdown (HUGO + R Markdown). Hence, each tutorials is an R markdown file. For PYTHON CHARTS, in order to run Python within an R markdown file I had to use an R package named reticulate. In addition, the template depends on shuffle.js for filtering and fuse.js for searching
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looking for an "low dependency" or pythonesque way to generate PDF's
What you want is not Python, its R Markdown; https://rmarkdown.rstudio.com/
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LaTex alternative/replacement written in Rust?
not sure what you mean by this exactly but in my experience its far better to use Markdown + pandoc for stuff like this. Actually I use R Markdown which can compile to either HTML or PDF from the same source document, with executable code chunks embedded (to generate the document contents) ; https://rmarkdown.rstudio.com/
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Neovim support for editing Quarto (.qmd) files
Quarto is a relatively new Markdown-based file format. One of its main uses is writing reports that interleave text with code and results; it supports rendering with knitr (an engine widely used in the R community) as well as Jupyter (more popular with Python users). Since I work in data science, I use both languages regularly. For writing R reports, I've switched from R Markdown (Quarto's R-focused predecessor) to Quarto. I'd also like to start writing Python reports in Quarto using Neovim.
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How do you build and send reports to your users?
If you're not already aware of and using RMarkdown, make learning it a priority. I use both R and Python extensively. Although Jupyter Notebooks have utility, RMarkdown is the superior tool for the most flexibility in reporting.
- Ask HN: Markdown/reStructuredText to write a PhD thesis in STEM fields?
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Securing R Markdown Documents
The polished package now supports Rmarkdown documents that use the shiny runtime. This includes flexdashboard!
Pluto.jl
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Potential of the Julia programming language for high energy physics computing
I thought that notebook based development and package based development were diametrically opposed in the past, but Pluto.jl notebooks have changed my mind about this.
A Pluto.jl notebook is a human readable Julia source file. The Pluto.jl package is itself developed via Pluto.jl notebooks.
https://github.com/fonsp/Pluto.jl
Also, the VSCode Julia plugin tooling has really expanded in functionality and usability for me in the past year. The integrated debugging took some work to setup, but is fast enough to drop into a local frame.
https://code.visualstudio.com/docs/languages/julia
Julia is the first language I have achieved full life cycle integration between exploratory code to sharable package. It even runs quite well on my Android. 2023 is the first year I was able to solve a differential equation or render a 3D surface from a calculated mesh with the hardware in my pocket.
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Ask HN: Why don't other languages have Jupyter style notebooks?
Re Julia there is also pluto.jl that is another notebook-like environment for julia. It's been a few years since I played with it but it looked cool, for example it handles state differently so you don't get into the same messes as with ipython notebooks. https://plutojl.org/
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Looking for a Julia gui framework with a demo like EGUI
For this, Notebooks are often used. Julia offers a uniquely nice and interactive Pluto notebook for the web https://github.com/fonsp/Pluto.jl
- Excel Labs, a Microsoft Garage Project
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IPyflow: Reactive Python Notebooks in Jupyter(Lab)
I believe this is what Pluto sets out to do for Julia.
I used it as part of the âComputational Thinkingâ with Julia course a year or two back. Even then the beta software was very good and some of the demos the Pluto dev showed were nothing short of amazing
- For Julia is there some thing like VSCode's python interactive window?
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What have you "washed your hands of" in Python?
I think what you want is Pluto!
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Show HN: Out of order execution in Jupyter notebooks is a solved problem
I like how Pluto.jl handles this:
> Pluto offers an environment where changed code takes effect instantly and where deleted code leaves no trace. Unlike Jupyter or Matlab, there is no mutable workspace, but rather, an important guarantee:
> At any instant, the program state is completely described by the code you see.
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My Journey from R to Julia
I only used Julia for a short time, but I didn't see the blazing fast speeds I was promised. I've seen the benchmarks, of course, on which the claims are founded, but the C-like speeds weren't obvious to me in everyday data science workflows. In the end, there wasn't sufficient motivation for me to switch to Julia as my weapon of choice. I do like Pluto[0], though...
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Using Julia with Anaconda and VoilĂ
You can use https://github.com/fonsp/Pluto.jl instead of Jupyter.
What are some alternatives?
vim-slime - A vim plugin to give you some slime. (Emacs)
Weave.jl - Scientific reports/literate programming for Julia
Dash.jl - Dash for Julia - A Julia interface to the Dash ecosystem for creating analytic web applications in Julia. No JavaScript required.
IJulia.jl - Julia kernel for Jupyter
Tables.jl - An interface for tables in Julia
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
PlutoSliderServer.jl - Web server to run just the `@bind` parts of a Pluto.jl notebook
Neptune.jl - Simple (Pluto-based) non-reactive notebooks for Julia
julia - The Julia Programming Language
ThreadsX.jl - Parallelized Base functions
jupyterlab-classic - JupyterLab distribution with a retro look and feel đ
here_here - I love the here package. Here's why.