first commit

.gitignore

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+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
+.Renviron
+.zip
+.csv

Dockerfile.app

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+# Install Java
+FROM openjdk:8
+
+# Install Ubuntu packages
+RUN apt-get update && apt-get install -y \
+    sudo \
+    gdebi-core \
+    pandoc \
+    pandoc-citeproc \
+    libcurl4-gnutls-dev \
+    libcairo2-dev \
+    libxt-dev \
+    libssl-dev \
+    libsasl2-dev \
+    r-base \
+    r-base-dev
+
+# Download and install Shiny Server
+RUN wget --no-verbose https://s3.amazonaws.com/rstudio-shiny-server-os-build/ubuntu-12.04/x86_64/VERSION -O "version.txt" && \
+    VERSION=$(cat version.txt)  && \
+    wget --no-verbose "https://s3.amazonaws.com/rstudio-shiny-server-os-build/ubuntu-12.04/x86_64/shiny-server-$VERSION-amd64.deb" -O ss-latest.deb && \
+    gdebi -n ss-latest.deb && \
+    rm -f version.txt ss-latest.deb
+
+# Config Java
+RUN sudo R CMD javareconf JAVA_HOME=$JAVA_HOME
+
+# Install R packages that are required
+RUN R -e "install.packages(c('shiny', 'bslib', 'magrittr', 'thematic', 'dbplyr', 'lubridate', 'leaflet', 'ggplot2', 'remotes'), repos='http://cran.rstudio.com/')"
+RUN R -e "remotes::install_github('deepanshu88/summaryBox')"
+RUN R -e "remotes::install_version('rJava', '0.9-11')"
+RUN R -e "install.packages('RJDBC')"
+
+# Copy configuration files into the Docker image
+COPY shiny-server.conf  /etc/shiny-server/shiny-server.conf
+COPY app.R /srv/shiny-server/
+
+# Make the ShinyApp available at port 80
+EXPOSE 8080
+
+# Copy further configuration files into the Docker image
+COPY shiny-server.sh /usr/bin/shiny-server.sh
+
+# Copy environment variables
+COPY .Renviron /srv/shiny-server/
+
+# Jar file
+COPY jars /srv/shiny-server/jars
+
+RUN ["chmod", "+x", "/usr/bin/shiny-server.sh"]
+
+CMD ["/usr/bin/shiny-server.sh"]

Dockerfile.update

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+FROM openwhisk/dockerskeleton
+RUN apk update && apk add openjdk8 openjdk8-jre R R-dev R-doc build-base tzdata
+RUN set -ex && apk --no-cache add sudo
+RUN echo "Set disable_coredump false" >> /etc/sudo.conf
+RUN sudo R CMD javareconf JAVA_HOME=/usr/lib/jvm/java-1.8-openjdk/jre && \
+sudo R -e "install.packages(c('jsonlite', 'rJava', 'RJDBC', 'dbplyr', 'tidyr', 'lubridate', 'curl'), repos = 'http://cran.rstudio.com/')"
+COPY jars /action/jars

app.R

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+require(bslib)
+require(shiny)
+require(magrittr)
+require(thematic)
+
+readRenviron(".Renviron")
+
+drv <-
+  RJDBC::JDBC("com.ibm.db2.jcc.DB2Driver", "jars/db2jcc4.jar")
+
+db2 <-
+  DBI::dbConnect(drv,
+                 Sys.getenv("DB2_HOST"),
+                 user = Sys.getenv("DB2_USER"),
+                 password = Sys.getenv("DB2_PASSWORD"))
+
+# theme
+theme <- bs_theme(
+  bg = "#0b3d91", fg = "white", primary = "#FCC780",
+  base_font = font_google("Space Mono"),
+  code_font = font_google("Space Mono")
+)
+
+thematic_on(
+  bg = "auto", 
+  fg = "auto", 
+  accent = "auto", 
+  font = "auto"
+)
+
+# ui
+ui <- fluidPage(
+  navbarPage("Covid 19"),
+  theme = theme,
+  sidebarLayout(
+    sidebarPanel(
+      selectizeInput("country", "País:",
+                     dplyr::tbl(db2, "AVG_SA_COVID19") %>% 
+                       dplyr::distinct(COUNTRY) %>% 
+                       dplyr::pull()),
+      dateInput("data", "Data")
+
+    ),
+
+    mainPanel(
+      uiOutput("summarybox"),
+      tabsetPanel(id = "panel",
+                  tabPanel("Plot", 
+                           tags$h4("Distribuição do número médio de mortes"),
+                           plotOutput("delta_plot")),
+                  tabPanel("Mapa", 
+                           tags$h4("Variação % comparando semana anterior"),
+                           leaflet::leafletOutput("mapa")))
+    )
+  )
+)
+
+# server
+server <- function(input, output) {
+
+  output$delta_plot <- renderPlot({
+
+    data_avg <- dplyr::tbl(db2, "AVG_SA_COVID19") %>% 
+      dplyr::as_tibble()
+
+    last <- 
+      data_avg %>% 
+      dplyr::filter(COUNTRY == input$country,
+                    WEEK == lubridate::week(input$data), 
+                    YEAR == lubridate::year(input$data)) %>% 
+      dplyr::select(YEAR, WEEK, AVG_VALUE)
+
+    data_avg %>% 
+      dplyr::filter(COUNTRY == input$country) %>% 
+      ggplot2::ggplot(ggplot2::aes(WEEK, AVG_VALUE)) + 
+      ggplot2::geom_line() +
+      ggplot2::labs(x = "Semanas", y = "Número médio de mortes") +
+      ggplot2::geom_label(data = last, ggplot2::aes(WEEK, AVG_VALUE, label = round(AVG_VALUE, 0))) +
+      ggplot2::facet_grid(~YEAR)
+
+  })
+
+  delta_avg_sa <- reactive({
+
+    dplyr::tbl(db2, "AVG_SA_COVID19") %>% 
+      dplyr::as_tibble() %>% 
+      dplyr::filter(WEEK == lubridate::week(input$data), YEAR == lubridate::year(input$data))
+
+  })
+
+
+  output$mapa <- leaflet::renderLeaflet({
+
+    conpal <- 
+      leaflet::colorNumeric(palette = "Reds", 
+                            domain = delta_avg_sa()$DELTA, 
+                            na.color = "black")
+
+    delta_avg_sa() %>% 
+      leaflet::leaflet() %>% 
+      leaflet::addProviderTiles("CartoDB.DarkMatter") %>% 
+      leaflet::addCircleMarkers(~LONG, ~LAT, 
+                                label = paste(delta_avg_sa()$COUNTRY, "|", 
+                                              round(delta_avg_sa()$DELTA, 1)), 
+                                color = ~conpal(delta_avg_sa()$DELTA)) %>% 
+      leaflet::addLegend(position = "bottomleft", 
+                         title = "Delta %",
+                         pal = conpal, 
+                         values = delta_avg_sa()$DELTA,
+                         opacity = 0.5)
+
+  })
+
+  output$summarybox <- 
+    renderUI({ 
+
+      sa <- dplyr::tbl(db2, "SA_COVID19") %>% 
+        dplyr::as_tibble() %>% 
+        dplyr::filter(COUNTRY == input$country) %>% 
+        dplyr::slice(dplyr::n())
+
+
+      fluidRow(
+        summaryBox::summaryBox("Última atualização", sa$DATE, width = 3, icon = "fas fa-calendar", style = "info"),
+        summaryBox::summaryBox("Número de mortes no último dia", sa$VALUE, width = 3, icon = "fas fa-chart-bar", style = "warning"),
+        summaryBox::summaryBox("Número total de mortes", sa$CUMULATE, width = 3, icon = "fas fa-chart-bar", style = "danger")
+      )})
+
+}
+
+shinyApp(ui, server)
+
+

covid19.Rproj

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+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 4
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX

exec

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+#!/bin/bash
+
+# get data
+wget -q https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv -O time_series_covid19_deaths_global.csv
+
+# run R script
+chmod +x read_update_data.R # turn executable
+./read_update_data.R # run script

manifest.yml

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+---
+applications:
+- name: dash-covid
+  memory: 256M
+  random-route: true

read_update_data.R

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+#!/usr/bin/env Rscript
+
+# config
+options(warn = -1)
+Sys.setenv(TZ = "America/Sao_Paulo")
+
+readRenviron(".Renviron")
+
+# packages
+require(magrittr, include.only = "%>%", quietly = TRUE)
+
+# read data
+covid19 <- 
+  read.csv("time_series_covid19_deaths_global.csv", stringsAsFactors = FALSE)
+
+# prepare data
+sa <- 
+  covid19 %>% 
+  dplyr::filter(Country.Region %in%  c("Brazil", "Peru", "Bolivia", 
+                                       "Chile", "Argentina", "Colombia",
+                                       "Venezuela", "Ecuador", "Uruguay",
+                                       "Paraguay")) %>% 
+  dplyr::select(- Province.State) %>% 
+  tidyr::pivot_longer(!Country.Region:Long, 
+                      names_to = "date", 
+                      values_to = "cumulate") %>% 
+  dplyr::group_by(Country.Region) %>% 
+  dplyr::mutate(date = gsub("X", "", date) %>% 
+                  gsub("\\.", "-", .) %>% 
+                  lubridate::mdy(),
+                value = cumulate - dplyr::lag(cumulate)) %>% 
+  dplyr::rename(country = Country.Region)
+
+avg_sa <- 
+  sa %>% 
+  dplyr::mutate(week = lubridate::week(date),
+                year = lubridate::year(date)) %>% 
+  dplyr::group_by(country, year, week, Lat, Long) %>% 
+  dplyr::summarise(avg_value = mean(value, na.rm = TRUE), .groups = "drop") %>% 
+  dplyr::group_by(country) %>%
+  dplyr::mutate(delta = (avg_value - dplyr::lag(avg_value))/dplyr::lag(avg_value) * 100) %>% 
+  dplyr::ungroup() %>% 
+  dplyr::mutate(delta = ifelse(is.finite(delta) & !is.na(delta), delta, 0))
+
+# write data
+require(dbplyr, quietly = TRUE)
+
+readRenviron(".Renviron")
+
+drv <-
+  RJDBC::JDBC("com.ibm.db2.jcc.DB2Driver", "jars/db2jcc4.jar")
+
+db2 <-
+  DBI::dbConnect(drv,
+                 Sys.getenv("DB2_HOST"),
+                 user = Sys.getenv("DB2_USER"),
+                 password = Sys.getenv("DB2_PASSWORD"))
+
+DBI::dbWriteTable(db2, "AVG_SA_COVID19", value = avg_sa, overwrite = TRUE)
+DBI::dbWriteTable(db2, "SA_COVID19", value = sa, overwrite = TRUE)
+
+# test
+update <- sa %>% dplyr::pull(date) %>% range() %>% .[2]
+
+# response
+jsonlite::stream_out(data.frame(update = update), verbose = FALSE)
+

shiny-server.conf

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+# Define the user we should use when spawning R Shiny processes
+run_as shiny;
+
+# Define a top-level server which will listen on a port
+server {
+  # Instruct this server to listen on port 80. The app at dokku-alt need expose PORT 80, or 500 e etc. See the docs
+  listen 8080;
+
+  # Define the location available at the base URL
+  location / {
+
+    # Run this location in 'site_dir' mode, which hosts the entire directory
+    # tree at '/srv/shiny-server'
+    site_dir /srv/shiny-server;
+
+    # Define where we should put the log files for this location
+    log_dir /var/log/shiny-server;
+
+    # Should we list the contents of a (non-Shiny-App) directory when the user 
+    # visits the corresponding URL?
+    directory_index on;
+  }
+}

shiny-server.sh

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+#!/bin/sh
+
+# Make sure the directory for individual app logs exists
+mkdir -p /var/log/shiny-server
+chown shiny.shiny /var/log/shiny-server
+
+exec shiny-server >> /var/log/shiny-server.log 2>&1