Git Product home page Git Product logo

streamlit-shiny-dash's Introduction

Data App Comparison

This repo illustrates some differences between

To get started set up a virtual environment and install requirements with

pip install -r requirements.txt

Dash

The Dash app can be run with python dash-app.py

Panel

The Panel app can be run with panel serve panel-app.py.

You can add the --autoreload flag while developing.

Streamlit

To run the streamlit app call streamlit run streamlit-app.py

Shiny for Python

The python shiny app can be run with shiny run shiny-app.py --reload.

Shiny for R

The R shiny app can be run with R -e "shiny::runApp('app.R')".

streamlit-shiny-dash's People

Contributors

gshotwell avatar marcskovmadsen avatar daattali avatar

Stargazers

Michael Kaufman avatar Gaurav avatar Pohan avatar Andrea Di Francia avatar  avatar peterh avatar  avatar Franky1 avatar Yuichiro Tachibana (Tsuchiya) avatar Guido Schulz avatar Lei Zhou avatar Jieqiang He avatar  avatar Dag Wästberg avatar Steven Pawley avatar Thabang  avatar Piotr avatar

Watchers

 avatar  avatar

streamlit-shiny-dash's Issues

General data apps comparison repo

It would be great if we had a data apps comparison repo similar to https://eugenkiss.github.io/7guis/ or https://todomvc.com/ to let people compare implementations of python web application frameworks. Some requirements would be:

  1. Hosted by a neutral org (Numfocus? PyOpenSci?) or at least have maintainers from multiple application frameworks
  2. Host multiple problem sets for example:
  • Sampling application
  • Todo list
  • Add and remove UI
  • CSS customizations
  1. Allow people to propose new problems
  2. Clear scoring criteria for each problem

@MarcSkovMadsen what do you think?

Add R-Shiny equivalent, for comparison purposes?

Ill leave this here, in case you want to add it. I personally find it useful to compare different tools across languages. I tried staying as close as possible to the py-shiny app, both code-wise and look-wise.

library(shiny)
library(ggplot2)

ui <- fluidPage(
  sidebarLayout(
    sidebarPanel(
      sliderInput("sample", "Sample Size", 0, 1, value = 0.1),
      checkboxInput("log", "Log Scale")
    ),
    mainPanel(
      h3(textOutput("first_taxi_id")),
      plotOutput("tip_plot"),
      plotOutput("amount_histogram")
    )
  )
)

server <- function(input, output, session) {
  dat <- reactive({
    read.csv("nyc-taxi.csv")
  })
  
  sampled_dat <- reactive({
    dplyr::slice_sample(dat(), prop = input$sample)
  })
  
  output$first_taxi_id <- renderText({
    paste("First taxi ID:", sampled_dat()$taxi_id[1])
  })
  
  output$tip_plot <- renderPlot({
    plot <- ggplot(sampled_dat(), aes(tip_amount, total_amount)) +
      geom_point(size = 3) +
      theme_bw(20)
    if (input$log) {
      plot <- plot +
        scale_x_log10() +
        scale_y_log10()
    }
    plot
  })
  
  output$amount_histogram <- renderPlot({
    plot <- ggplot(sampled_dat(), aes(x = total_amount)) +
      geom_histogram(binwidth = 5) +
      theme_bw(20)
    plot
  })
}

shinyApp(ui, server)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.