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BDAccess/app.R

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library(shiny)
library(rhandsontable)
print(getwd())
print(file)
source("../sqlFunctions.R", encoding = "UTF-8")
DF<-data.frame("NHC"="","Samples"="")
samples<-data.frame("UMID"="","UM"="")
CLINICS<-data.frame("UMID"="","UM"="")
cnag<-data.frame("UMID"="","UM"="")
rna<-data.frame("UMID"="","UM"="")
# Cargar dependencias
sqlInitialize(ruta="../ruta_database.R")
ui <- fluidPage(
# Application title
titlePanel("BDAccess"),
sidebarLayout(
sidebarPanel(
selectInput("dbtype", "", selected="UM", choices=c("UM", "OV")),
checkboxInput(inputId = "backup", label="Backup", value=F),
actionButton("butdbtype", "Carrega BD"),
hr(),
fileInput(inputId = "file_query", label = "Plantilla", multiple = F),
actionButton("impNHC", "Importa NHC"),
actionButton("goButton", "Genera UMID"),
hr(),
actionButton("filltemplate", "Plantilla"),
hr(),
actionButton("synctemplate", "Sincronizar")
),
mainPanel(
tabsetPanel(
tabPanel("NHC", rHandsontableOutput("hot")),
tabPanel("Samples",rHandsontableOutput("samples")),
tabPanel("CLINICS",rHandsontableOutput("CLINICS")),
tabPanel("CNAG",rHandsontableOutput("cnag")),
tabPanel("RNADNA",rHandsontableOutput("rna")),
)
)
)
)
# Define server logic required to draw a histogram
server <- function(input, output) {
values <- reactiveValues()
values[["DF"]]<-DF
values[["samples"]]<-samples
values[["CLINICS"]]<-CLINICS
values[["cnag"]]<-cnag
values[["rna"]]<-rna
values[["Excel"]]<-""
observeEvent(input$butdbtype, {
dta<<-odbcConnectAccess2007(access.file = file,
pwd = .rs.askForPassword("Enter password:"))
print(dta)
if (input$backup == T){
sqlBackUp()
}
})
# observe({
# if (!is.null(input$file_access)){
# # Inicializar conexión
# dta<<-odbcConnectAccess2007(access.file = file,
# pwd = .rs.askForPassword("Enter password:"))
# print(dta)
# sqlBackUp()
# }
# })
observe({
if (!is.null(input$file_query)){
## Importamos los NHC de las muestras nuevas
values[["Excel"]]<-read.xlsx(input$file_query$datapath, sheet = "NHC") %>% pull(NHC) %>% as.character()
}
})
observeEvent(input$impNHC, {
values[["DF"]]$NHC<-values[["Excel"]]
})
## Handsontable
observe({
if (!is.null(input$hot)) {
DF = hot_to_r(input$hot)
} else {
if (is.null(values[["DF"]])){
DF <- DF
}
else{
DF <- values[["DF"]]
}
}
values[["DF"]] <- DF
})
output$hot <- renderRHandsontable({
if (!is.null(DF)){
rhandsontable(values[["DF"]], stretchH = "all", readOnly = F, useTypes = T)
}
})
observe({
print(1)
if (!is.null(input$samples)) {
samples = hot_to_r(input$samples)
} else {
if (is.null(values[["samples"]])){
samples <- samples
}
else{
samples <- values[["samples"]]
}
}
values[["samples"]] <- samples
})
output$samples <- renderRHandsontable({
if (!is.null(samples)){
rhandsontable(values[["samples"]], stretchH = "all", readOnly = F, useTypes = T)
}
})
observe({
if (!is.null(input$CLINICS)) {
CLINICS = hot_to_r(input$CLINICS)
} else {
if (is.null(values[["CLINICS"]])){
CLINICS <- CLINICS
}
else{
CLINICS <- values[["CLINICS"]]
}
}
values[["CLINICS"]] <- CLINICS
})
output$CLINICS <- renderRHandsontable({
if (!is.null(CLINICS)){
rhandsontable(values[["CLINICS"]], stretchH = "all", readOnly = F, useTypes = T)
}
})
observe({
if (!is.null(input$cnag)) {
cnag = hot_to_r(input$cnag)
} else {
if (is.null(values[["cnag"]])){
cnag <- cnag
}
else{
cnag <- values[["cnag"]]
}
}
values[["cnag"]] <- cnag
})
output$cnag <- renderRHandsontable({
if (!is.null(cnag)){
rhandsontable(values[["cnag"]], stretchH = "all", readOnly = F, useTypes = T)
}
})
observe({
if (!is.null(input$rna)) {
rna = hot_to_r(input$rna)
} else {
if (is.null(values[["rna"]])){
rna <- rna
}
else{
rna <- values[["rna"]]
}
}
values[["rna"]] <- rna
})
output$rna <- renderRHandsontable({
if (!is.null(rna)){
rhandsontable(values[["rna"]], stretchH = "all", readOnly = F, useTypes = T)
}
})
observeEvent(input$goButton, {
print(dta)
sqlGenOVID(nhcs = values[["DF"]]$NHC, sinc=T)
values[["DF"]]<-merge(values[["DF"]], sqlFetch(dta, "UMID"))
print(values[["DF"]])
})
observeEvent(input$filltemplate,{
today=T
upd.umid<-sqlFetch(dta, "UMID") %>% filter(NHC %in% values[["DF"]]$NHC)
## Generar código para las nuevas muestras
samples<-sqlFetch(dta, "MUESTRAS")
if(sum(grepl(paste0("UM",Sys.time() %>% format("%y")), samples$CODIGO)) > 0){
next.samp<-gsub(paste0("UM",Sys.time() %>% format("%y")),"", samples$CODIGO) %>% as.numeric %>% max(na.rm=T)+1
}else{
next.samp<-1
}
last.samp<-next.samp+(length(values[["DF"]]$NHC)-1)
new.samp<-sprintf("UM%s%02d",Sys.time() %>% format("%y"),next.samp:last.samp)
new.samp.df<-data.frame("NHC"=values[["DF"]]$NHC, "CODIGO"=new.samp) %>% merge(sqlFetch(dta,"UMID"), all.x=T) %>% arrange(CODIGO)
samples.exp<-merge(samples %>% slice(0), new.samp.df %>% select(-NHC), all=T) %>% select(colnames(samples)) %>% arrange(CODIGO)
if (today==TRUE){
samples.exp$FECHA_RECEPCION<-format(Sys.Date(), "%d/%m/%y")
}
nhc.table<-values[["DF"]]
if (any(sapply(nhc.table$Samples, function(x) "cnag" %in% strsplit(x,",")[[1]]) == T)){
nhcs.cnag<-nhc.table[sapply(nhc.table$Samples, function(x) "cnag" %in% strsplit(x,",")[[1]]),"NHC"]
umid.cnag<-sqlFetch(dta, "UMID") %>% filter(NHC %in% nhcs.cnag) %>% pull(UMID)
sample.cnag<-samples.exp %>% filter(UMID %in% umid.cnag) %>% pull(CODIGO)
cnag.exp<-merge(data.frame("UMID"=umid.cnag, "CODIGO"=sample.cnag), sqlFetch(dta, "CNAG") %>% slice(0), all=T)
if (today==TRUE){
cnag.exp$FECHA_ENVIO<-format(Sys.Date(), "%d/%m/%y")
}
}else{
cnag.exp<-sqlFetch(dta, "CNAG") %>% slice(0) %>%
mutate(across(lubridate::is.POSIXct, as.character))
}
if (any(sapply(nhc.table$Samples, function(x) "rna" %in% strsplit(x,",")[[1]]) == T)){
nhcs.rna<-nhc.table[sapply(nhc.table$Samples, function(x) "rna" %in% strsplit(x,",")[[1]]),"NHC"]
umid.rna<-sqlFetch(dta, "UMID") %>% filter(NHC %in% nhcs.rna) %>% pull(UMID)
sample.rna<-samples.exp %>% filter(UMID %in% umid.rna) %>% pull(CODIGO)
rna.exp<-merge(data.frame("UMID"=umid.rna, "CODIGO"=sample.rna), sqlFetch(dta, "RNADNA") %>% slice(0)%>%
mutate(across(lubridate::is.POSIXct, as.character)), all=T)
}else{
rna.exp<-sqlFetch(dta, "RNADNA") %>% slice(0) %>%
mutate(across(lubridate::is.POSIXct, as.character))
}
## Importar los datos clínicos de pacientes existentes y generar nueva entrada par los nuevos
upd.clinics<-sqlFetch(dta, "CLINICOS")
umid.new<-sqlFetch(dta, "UMID") %>% filter(NHC %in% values[["DF"]]$NHC)
upd.clinics<-merge(umid.new,upd.clinics, all.x=T, by="UMID")
upd.clinics$NHC<-as.character(upd.clinics$NHC)
for (i in colnames(upd.clinics)[sapply(upd.clinics, lubridate::is.POSIXct)]){upd.clinics[,i]<-as.Date(upd.clinics[,i])}
values[["samples"]]<-samples.exp
values[["CLINICS"]]<-upd.clinics
values[["cnag"]]<-cnag.exp
values[["rna"]]<-rna.exp
print(values[["rna"]] %>% sapply(class))
})
observeEvent(input$synctemplate,{
# conn=dta, filetemp="queryOV.xlsx", sinc.samples=F, sinc.clinics=F, dbtype=NULL
## Nuevas entradas en MUESTRAS
nsamples<-values[["samples"]] %>% nrow
upd.samples<-values[["samples"]]
if (nrow(upd.samples) > 0){rownames(upd.samples)<-(nsamples+1):(nsamples+nrow(upd.samples)) %>% as.character}
if (nrow(upd.samples) > 0){
upd.samples$FECHA_RECEPCION<-lubridate::parse_date_time(upd.samples$FECHA_RECEPCION, c("d/m/Y","d/m/y")) %>% as.Date()
upd.samples$TIPO<-as.character(upd.samples$TIPO)
upd.samples$OBS<-as.character(upd.samples$OBS)
### !! Atención, esto cambia la base de datos:
print(upd.samples)
sqlSave(dta, upd.samples, tablename="MUESTRAS", append = T, varTypes = c("FECHA_RECEPCION"="Date"), rownames = F)
print("Tabla MUESTRAS sincronizada.")
}
## Entradas modificadas en CLINICOS
upd.clinics<-values[["CLINICS"]]
umid.mod<-upd.clinics$UMID[upd.clinics$UMID %in% (sqlFetch(dta, "CLINICOS") %>% pull(UMID))]
rnames<-sqlFetch(dta, "CLINICOS") %>% filter(UMID %in% umid.mod) %>% rownames
clinics.mod<-upd.clinics %>% filter(UMID %in% umid.mod) %>% select(-NHC)
rownames(clinics.mod)<-rnames
### !! Atención, esto cambia la base de datos:
fechas<-colnames(clinics.mod)[grepl("date|MET_DX|DoB", colnames(clinics.mod), ignore.case = T)]
for (i in fechas){
clinics.mod[,i]<-lubridate::parse_date_time(clinics.mod[,i], c("d/m/Y","d/m/y")) %>% as.Date()
}
sqlUpdate(dta, clinics.mod,"CLINICOS", index="UMID")
print("Tabla CLINICOS modificada.")
## Nuevas entradas en CLINICOS
nsamples.clin<-sqlFetch(dta, "CLINICOS") %>% nrow
umid.new<-upd.clinics$UMID[!upd.clinics$UMID %in% (sqlFetch(dta, "CLINICOS") %>% pull(UMID))]
clinics.new<-upd.clinics %>% filter(UMID %in% umid.new) %>% select(-NHC)
if (length(umid.new) > 0){rownames(clinics.new)<-(nsamples.clin+1):(nsamples.clin+nrow(clinics.new)) %>% as.character}
### !! Atención, esto cambia la base de datos:
fechas<-colnames(clinics.new)[grepl("date|MET_DX|DoB", colnames(clinics.new), ignore.case = T)]
varTypes<-rep("Date",length(fechas))
names(varTypes)<-fechas
for (i in fechas){
clinics.new[,i]<-lubridate::parse_date_time(clinics.new[,i], c("d/m/Y","d/m/y")) %>% as.Date()
}
sqlSave(dta, clinics.new, tablename="CLINICOS", append = T, varTypes = varTypes, rownames = F)
print("Tabla CLINICOS sincronizada.")
## Nuevas entradas en CNAG
if (nrow(values[["cnag"]]) > 0){
cnag.sync<-values[["cnag"]]
fechas<-colnames(cnag.sync)[sqlFetch(dta, "CNAG") %>% sapply(lubridate::is.POSIXct)]
varTypes<-rep("Date",length(fechas))
names(varTypes)<-fechas
print(fechas)
for (i in fechas){
cnag.sync[,i]<-lubridate::parse_date_time(cnag.sync[,i], c("d/m/Y","d/m/y")) %>% as.Date()
}
sqlSave(dta, cnag.sync, tablename="CNAG", append = T, varTypes = varTypes, rownames = F)
}
## Nuevas entradas en RNADNA
if (nrow(values[["rna"]]) > 0){
rna.sync<-values[["rna"]]
fechas<-colnames(rna.sync)[sqlFetch(dta, "RNADNA") %>% sapply(lubridate::is.POSIXct)]
varTypes<-rep("Date",length(fechas))
names(varTypes)<-fechas
for (i in fechas){
rna.sync[,i]<-lubridate::parse_date_time(rna.sync[,i], c("d/m/Y","d/m/y")) %>% as.Date()
}
sqlSave(dta, rna.sync, tablename="RNADNA", append = T, varTypes = varTypes, rownames = F)
}
})
}
# Run the application
shinyApp(ui = ui, server = server)

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