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Based on our record, Shiny seems to be a lot more popular than Dash by Plotly. While we know about 34 links to Shiny, we've tracked only 1 mention of Dash by Plotly. 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.
There is a lot of way and the most common is shiny (https://shiny.posit.co/) but with a biais towards data app. Not having a Django-like or others web stack python may have talks more about the users of R than the language per se. Its background was to replace S which was a proprietary statistics language not to enter competition with Perl used in CGI and early web. R is very powerful and is Lisp in disguise... - Source: Hacker News / 26 days ago
In R, you can build Single Page Applications with Shiny, created by Posit https://shiny.posit.co/ It is very useful, if you don't know HTML,JS,CSS and want to create an interactive dashboard, showcasing your analysis, models, visualizations, or even to create an internal tool for your organization. It seems that reactR provides functions for building react components directly from R that can be used in Shiny apps. - Source: Hacker News / 8 months 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 1 year 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 / almost 2 years 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: almost 2 years ago
Of course there are valid use cases for splitting frontend and backend technologies. NiceGUI is for those who don’t want to leave the Python ecosystem and like to reap the benefits of having all code in one place. There are other options like Streamlit, Dash, Anvil, JustPy, and Pynecone. But we initially created NiceGUI to easily handle the state of external hardware like LEDs, motors, and cameras. Additionally,... Source: about 2 years ago
Node.js - Node.js is a platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications
Streamlit - Turn python scripts into beautiful ML tools
Django - The Web framework for perfectionists with deadlines
Streamsync - Streamsync is an open-source framework for creating data apps. Build user interfaces using a visual editor; write the backend code in Python.
Ruby on Rails - Ruby on Rails is an open source full-stack web application framework for the Ruby programming...
Panel - High-level app and dashboarding solution for Python
