Mojolicious
Laravel
Dancer
Django
React
Apache HTTP Server
SUSE Linux Enterprise
Adonis JS
Shiny
Node.js
Django
Ruby on Rails
Laravel
ASP.NET
Meteor
ExpressJS
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Mojolicious might be a bit more popular than Shiny. We know about 35 links to it since March 2021 and only 32 links to Shiny. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
If you end up doing web development, check out Mojolicious: https://mojolicious.org/. - Source: Hacker News / 10 months ago
If you choose to go down the Mojolicious road, there's lots of deployment information and guides in the Mojolicious Cookbook. Source: 11 months ago
I guess this will make it harder to search for Mojo(licious)-related stuff. 😩. Source: about 1 year ago
Several! The 3 big players in order of release are Catalyst, (released in 2005), Dancer2 (Dancer was first released in 2009, but went through a complete re-write as Dancer2 around 2013), and Mojolicious (released in 2010). Source: about 1 year ago
This project sounds to me like the perfect excuse to learn Mojolicious if you're interested in converting your scripts into a web application using Perl. Source: about 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 / 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
Laravel - A PHP Framework For Web Artisans
Node.js - Node.js is a platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications
Dancer - Simple but powerful web application framework for Perl
Django - The Web framework for perfectionists with deadlines
Ruby on Rails - Ruby on Rails is an open source full-stack web application framework for the Ruby programming...
React - A JavaScript library for building user interfaces