Voilà VS Shiny

> Works with CI/CD out of the box. Deploy to vercel, netlify, your own infra. Jupyter is suited for whatever you want to do with it. Voila exists to enable the use case of re-generating notebooks on a CI/CD system: https://github.com/voila-dashboards/voila Anyways, seems like the templating is more powerful than the one being offered by Jupyter Notebooks.... - Source: Hacker News / about 1 year ago

I don't understand why everyone isn't just using voila. it's so much better than streamlit or gradio. But that's just my opinion I guess. Source: about 1 year ago

Ill have to check it out and see how it compares to voilà and holoviz panel. What I like about Holoviz panel is you can create a data web app from code that resides in a notebook or create a completely standalone app from just plain py scripts, and it supports many different visualization backends. I have found it to be the more flexible and generalizable data web app framework among the others I have come... Source: about 1 year ago

Any insights what the differences between this and Voila are? Https://github.com/voila-dashboards/voila. Source: about 1 year ago

A nifty little alternative to voila, one might say. - Source: dev.to / over 1 year ago

A lighterweight alternative to renv is to use Posit Public Package Manage (https://packagemanager.posit.co/) with a pinned date. That doesn't help if you're installing packages from a mix of places, but if you're only using CRAN packages it lets you get everything as of a fixed date. And of course on the web side you have shiny (https://shiny.posit.co), which now also comes in a python flavour. - Source: Hacker News / about 2 months ago

Sometimes the war is lost even before the battle begins. During grad school, I wrote a whole bunch of web apps entirely in R using Shiny. It was clunky as hell, but yeah, it worked. I went looking for what's up with Shiny these days and found this - https://shiny.posit.co/ So yeah, full on pivot into python. Pip install shiny. Alright! "No web development skills required. Develop web apps entirely in R I mean... - Source: Hacker News / 9 months ago

Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: 12 months ago

We work along side bio-statisticians and data analysts, from my experience in this world I recommend to build some plots/graphs in R based on some information you find appealing. After you have some work to show off to potential employers , learn Shiny and publish those graphs online as your portfolio. Source: about 1 year ago

One of the most difficult yet most fun projects I’ve done. Using Shiny to make an app, all coded in R! Source: about 1 year ago