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# Before running the code...
# 1. Set VPN function in Opera
# 2. Download Opera Webdriver from https://github.com/operasoftware/operachromiumdriver/releases
# 3. Type about://about in Opera and get profile path and installation path.
# 4. Set the variables.
# opera_profile = r"C:\profile path"
# options._binary_location = r"C:\\installation path."

from selenium import webdriver

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rm(list=ls())
options(stringsAsFactors = F)

library(RSelenium)

# One can make terminal invisible but initially it helps in detecting any potential problem
# Use proper path for Selenium and geckodriver.exe.
# remember to rename the donwloaded Selenium

sel <- startServer(dir = "C:/Dev/Selenium/", 

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library(inline)

inc <- '
/* This is taken from envir.c in the R 2.15.1 source 
   https://github.com/SurajGupta/r-source/blob/master/src/main/envir.c
*/
#define FRAME_LOCK_MASK (1<<14)
#define FRAME_IS_LOCKED(e) (ENVFLAGS(e) & FRAME_LOCK_MASK)
#define UNLOCK_FRAME(e) SET_ENVFLAGS(e, ENVFLAGS(e) & (~ FRAME_LOCK_MASK))
'

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doInstall <- TRUE  # Change to FALSE if you don't want packages installed.
toInstall <- c("sna", "ggplot2", "Hmisc", "reshape2")
if(doInstall){install.packages(toInstall, repos = "http://cran.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

# Empty ggplot2 theme
new_theme_empty <- theme_bw()
new_theme_empty$line <- element_blank()
new_theme_empty$rect <- element_blank()
new_theme_empty$strip.text <- element_blank()

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library(RDCOMClient)

convert_xls_to_xlsx<- function(in_folder,out_folder, delete_xls=F){
  
  if(missing(out_folder)){
    out_folder<- in_folder
  }
  
  all_xls<- list.files(in_folder, pattern = ".xls$")
  

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/*====================================================================
 Title: Computes Longest Repeated Substring from a given string
 Complexity: O(n.log(n))
 Author : Sudipto Chandra (Dipu)
 =====================================================================*/
#include <bits/stdc++.h>
using namespace std;
#define mem(a,b) memset(a, b, sizeof(a))
#define loop(i, x) for(__typeof((x).begin()) i=(x).begin(); i!=(x).end(); ++i)
#define rloop(i, x) for(__typeof((x).rbegin()) i=(x).rbegin(); i!=(x).rend(); ++i)

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#
# This Shiny web application demonstrates the use of custom image files
# in place of icons for value boxes in Shiny Dashboard by overriding two
# functions:
#
# 'icon' from the shiny package and 'valueBox' from the shinydashboard package.
#
# Each function adds minimal, specific additional handling of image files.
# Note: A custom css file must also be included so that value boxes can
# display the icons. For that reason, do not expect images in place of icons to

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library(sp)
library(rgeos)
library(rgdal)
library(maptools)
library(dplyr)
library(leaflet)
library(scales)
### Begin data prep
# Grab air/water quality data from the EPA
url = "https://data.cdc.gov/api/views/cjae-szjv/rows.csv?accessType=DOWNLOAD"

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progress_print <- function(){
  L <- list(init = function(x) {M <<- x}, step = function() NULL, term = function() NULL)
  itr <- 0
  M <- 1
  L$step <- function(){
    itr <<- itr + 1
    cat(paste0("Job ", itr, " out of ", M, "\n"))
  }
  return(L)
}

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library(shiny)
library(datasets)
Logged = FALSE;
PASSWORD <- data.frame(Brukernavn = "withr", Passord = "25d55ad283aa400af464c76d713c07ad")
# Define server logic required to summarize and view the selected dataset
shinyServer(function(input, output) {
  source("www/Login.R",  local = TRUE)
  
  observe({
    if (USER$Logged == TRUE) {