Merge pull request #7 from agdamsbo/docs

Updated README and two new vignettes. A little basic for now.

.gitignore

@@ -8,3 +8,5 @@ logo.R
 .DS_Store
 docs
 drafting
+\.DS_Store
+.DS_Store

DESCRIPTION

@@ -36,11 +36,13 @@ Suggests:
     here,
     styler,
     devtools,
-    roxygen2
+    roxygen2,
+    openxlsx2,
+    rsconnect
 License: GPL (>= 3)
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.3.0
+RoxygenNote: 7.3.1
 URL: https://github.com/agdamsbo/REDCapCAST, https://agdamsbo.github.io/REDCapCAST/
 BugReports: https://github.com/agdamsbo/REDCapCAST/issues
 Imports: 
@@ -64,5 +66,6 @@ Collate:
     'redcap_wider.R'
     'redcapcast_data.R'
     'redcapcast_meta.R'
+    'shiny_cast.R'
 Language: en-US
 VignetteBuilder: knitr

NAMESPACE

@@ -6,17 +6,22 @@ export(d2w)
 export(ds2dd)
 export(ds2dd_detailed)
 export(easy_redcap)
+export(file_extension)
 export(focused_metadata)
 export(get_api_key)
 export(guess_time_only_filter)
 export(is_repeated_longitudinal)
 export(match_fields_to_form)
+export(read_input)
 export(read_redcap_instrument)
 export(read_redcap_tables)
 export(redcap_wider)
 export(sanitize_split)
+export(server_factory)
+export(shiny_cast)
 export(split_non_repeating_forms)
 export(strsplitx)
+export(ui_factory)
 importFrom(REDCapR,redcap_event_instruments)
 importFrom(REDCapR,redcap_metadata_read)
 importFrom(REDCapR,redcap_read)

R/shiny_cast.R

@@ -0,0 +1,58 @@
+#' Shiny server factory
+#'
+#' @return shiny server
+#' @export
+server_factory <- function() {
+  source(here::here("app/server.R"))
+  server
+}
+
+#' UI factory for shiny app
+#'
+#' @return shiny ui
+#' @export
+ui_factory <- function() {
+  # require(ggplot2)
+source(here::here("app/ui.R"))
+
+}
+
+#' Launch the included Shiny-app for database casting and upload
+#'
+#' @return shiny app
+#' @export
+#'
+#' @examples
+#' # shiny_cast()
+#'
+shiny_cast <- function() {
+  # shiny::runApp(appDir = here::here("app/"), launch.browser = TRUE)
+
+  shiny::shinyApp(
+    ui_factory(),
+    server_factory()
+  )
+}
+
+#' Deploy the Shiny app with rsconnect
+#'
+#' @return deploy
+#' @export
+#'
+#' @examples
+#' # deploy_shiny
+#'
+deploy_shiny <- function(path=here::here("app/"), name.app="shiny_cast"){
+  # Ensure to install latest package version
+  renv::install("agdamsbo/REDCapCAST")
+
+  # Connecting
+  rsconnect::setAccountInfo(
+    name = "cognitiveindex",
+    token = keyring::key_get(service = "rsconnect_cognitiveindex_token"),
+    secret = keyring::key_get(service = "rsconnect_cognitiveindex_secret")
+  )
+
+  # Deploying
+  rsconnect::deployApp(appDir = path,lint = TRUE,appName = name.app,)
+}

R/utils.r

@@ -490,3 +490,53 @@ is_repeated_longitudinal <- function(data, generics = c(
   }
   any(generics %in% names)
 }
+
+
+
+#' Helper to import files correctly
+#'
+#' @param filenames file names
+#'
+#' @return character vector
+#' @export
+#'
+#' @examples
+#' file_extension(list.files(here::here(""))[[2]])[[1]]
+file_extension <- function(filenames) {
+  sub(pattern = "^(.*\\.|[^.]+)(?=[^.]*)", replacement = "", filenames, perl = TRUE)
+}
+
+#' Flexible file import based on extension
+#'
+#' @param file file name
+#' @param consider.na character vector of strings to consider as NAs
+#'
+#' @return tibble
+#' @export
+#'
+#' @examples
+#' read_input("https://raw.githubusercontent.com/agdamsbo/cognitive.index.lookup/main/data/sample.csv")
+read_input <- function(file, consider.na= c("NA", '""',"")){
+
+  ext <- file_extension(file)
+
+  tryCatch(
+    {
+      if (ext == "csv") {
+        df <- readr::read_csv(file = file,na = consider.na)
+      } else if (ext %in% c("xls", "xlsx")) {
+        df <- openxlsx2::read_xlsx(file = file, na.strings = consider.na)
+      } else if (ext == "dta"){
+        df <- haven::read_dta(file = file)
+      } else {
+        stop("Input file format has to be either '.csv', '.xls' or '.xlsx'")
+      }
+    },
+    error = function(e) {
+      # return a safeError if a parsing error occurs
+      stop(shiny::safeError(e))
+    }
+  )
+
+  df
+}

README.md

@@ -12,11 +12,11 @@ experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](h
 
 # REDCapCAST package <img src="man/figures/logo.png" align="right" />
 
-REDCap Castellated data handling when using repeated instruments.
+REDCap database casting and handling of castellated data when using repeated instruments and longitudinal projects.
 
 This package is a fork of [pegeler/REDCapRITS](https://github.com/pegeler/REDCapRITS). The REDCapRITS represents great and extensive work to handle castellated REDCap data in different programming languages. This fork is purely minded on R usage and includes a few implementations of the main `REDCap_split` function.
 
-The main goal for this project was to allow for a "minimal data" approach by allowing to filter records, instruments and variables in the export to only download data needed. I think this approach is desireable for handling sensitive, clinical data. No similar functionality is available from similar tools (like `REDCapR` or `REDCapTidieR`). Please refer to [REDCap-Tools](https://redcap-tools.github.io/) for other great tools.
+THis package is very much to be seen as an attempt at a REDCap-R foundry for handling both the transition from dataset/variable list to database and the other way, from REDCap database to a tidy dataset. The goal was also to allow for a "minimal data" approach by allowing to filter records, instruments and variables in the export to only download data needed. I think this approach is desireable for handling sensitive, clinical data. No similar functionality is available from similar tools (like `REDCapR` or `REDCapTidieR`). Please refer to [REDCap-Tools](https://redcap-tools.github.io/) for other great tools.
 
 ## Use and immprovements
 
@@ -30,8 +30,7 @@ This package is primarily relevant for working with longitudinal projects and/or
 
 * `easy_redcap()`: combines secure API key storage with the `keyring`-package, focused data retrieval and optional widening. This is the recommended approach for easy data access and analysis.
 
-
-Compared to the original `REDCapRITS`, all matching functions are improved to accept column naming of REDCap data from manual download or API export.
+...
 
 ## Future
 

REDCapCAST.Rproj

@@ -18,4 +18,4 @@ StripTrailingWhitespace: Yes
 BuildType: Package
 PackageUseDevtools: Yes
 PackageInstallArgs: --no-multiarch --with-keep.source
-PackageRoxygenize: rd,collate,namespace
+PackageRoxygenize: rd,collate,namespace,vignette

app/server.R

@@ -0,0 +1,81 @@
+server <- function(input, output, session) {
+  require(REDCapCAST)
+
+  dat <- shiny::reactive({
+    shiny::req(input$ds)
+
+    read_input(input$ds$datapath)
+  })
+
+  dd <- shiny::reactive({
+    ds2dd_detailed(data = dat())
+  })
+
+
+  output$data.tbl <- shiny::renderTable({
+    dd() |>
+      purrr::pluck("data") |>
+      head(20) |>
+      dplyr::tibble()
+  })
+
+  output$meta.tbl <- shiny::renderTable({
+    dd() |>
+      purrr::pluck("meta") |>
+      dplyr::tibble()
+  })
+
+  # Downloadable csv of dataset ----
+  output$downloadData <- shiny::downloadHandler(
+    filename = "data_ready.csv",
+    content = function(file) {
+      write.csv(purrr::pluck(dd(), "data"), file, row.names = FALSE)
+    }
+  )
+
+  # Downloadable csv of data dictionary ----
+  output$downloadMeta <- shiny::downloadHandler(
+    filename = "dictionary_ready.csv",
+    content = function(file) {
+      write.csv(purrr::pluck(dd(), "meta"), file, row.names = FALSE)
+    }
+  )
+
+  output_staging <- shiny::reactiveValues()
+  output_staging$meta <- output_staging$data <- NA
+
+  shiny::observeEvent(input$upload.meta,{  upload_meta()  })
+
+  shiny::observeEvent(input$upload.data,{  upload_data()  })
+
+  upload_meta <- function(){
+
+    shiny::req(input$uri)
+
+    shiny::req(input$api)
+
+    output_staging$meta <- REDCapR::redcap_metadata_write(
+      ds = purrr::pluck(dd(), "meta"),
+      redcap_uri = input$uri,
+      token = input$api
+    )|> purrr::pluck("success")
+  }
+
+  upload_data <- function(){
+
+    shiny::req(input$uri)
+
+    shiny::req(input$api)
+
+    output_staging$data <- REDCapR::redcap_write(
+      ds = purrr::pluck(dd(), "data"),
+      redcap_uri = input$uri,
+      token = input$api
+    ) |> purrr::pluck("success")
+  }
+
+  output$upload.meta.print <- renderText(output_staging$meta)
+
+  output$upload.data.print <- renderText(output_staging$data)
+
+}

app/ui.R

@@ -0,0 +1,89 @@
+ui <- shiny::fluidPage(
+
+  ## -----------------------------------------------------------------------------
+  ## Application title
+  ## -----------------------------------------------------------------------------
+  shiny::titlePanel("Simple REDCap data base creation and data upload from data set file via API",
+                    windowTitle = "REDCap databse creator"
+  ),
+  shiny::h5("Please note, that this tool serves as a demonstration of some of the functionality
+       of the REDCapCAST package. No responsibility for data loss or any other
+       problems will be taken."),
+
+  ## -----------------------------------------------------------------------------
+  ## Side panel
+  ## -----------------------------------------------------------------------------
+
+  shiny::sidebarPanel(
+    shiny::h4("REDCap database and dataset"),
+    shiny::fileInput("ds", "Choose data file",
+                     multiple = FALSE,
+                     accept = c(
+                       ".csv",
+                       ".xls",
+                       ".xlsx",
+                       ".dta"
+                     )
+    ),
+    shiny::h6("Below you can download the dataset formatted for upload and the
+         corresponding data dictionary for a new data base."),
+    # Button
+    shiny::downloadButton("downloadData", "Download data"),
+
+    # Button
+    shiny::downloadButton("downloadMeta", "Download dictionary"),
+
+
+    # Horizontal line ----
+    shiny::tags$hr(),
+    shiny::h4("REDCap upload"),
+    shiny::textInput(
+      inputId = "uri",
+      label = "URI",
+      value = "https://redcap.au.dk/api/"
+    ),
+    shiny::textInput(
+      inputId = "api",
+      label = "API key",
+      value = "21CF2C17EA1CA4F3688DF991C8FE3EBF"
+    ),
+    shiny::actionButton(
+      inputId = "upload.meta",
+      label = "Upload dictionary", icon = shiny::icon("book-bookmark")
+    ),
+    shiny::h6("Please note, that before uploading any real data, put your project
+         into production mode."),
+    shiny::actionButton(
+      inputId = "upload.data",
+      label = "Upload data", icon = shiny::icon("upload")
+    ),
+
+    # Horizontal line ----
+    shiny::tags$hr()
+  ),
+  shiny::mainPanel(
+    shiny::tabsetPanel(
+
+      ## -----------------------------------------------------------------------------
+      ## Summary tab
+      ## -----------------------------------------------------------------------------
+      shiny::tabPanel(
+        "Summary",
+        shiny::h3("Data overview (first 20)"),
+        shiny::htmlOutput("data.tbl", container = shiny::span),
+        shiny::h3("Dictionary overview"),
+        shiny::htmlOutput("meta.tbl", container = shiny::span)
+      ),
+      ## -----------------------------------------------------------------------------
+      ## Upload tab
+      ## -----------------------------------------------------------------------------
+      shiny::tabPanel(
+        "Upload",
+        shiny::h3("Meta upload overview"),
+        shiny::htmlOutput("upload.meta.print", container = shiny::span),
+        shiny::h3("Data upload overview"),
+        shiny::htmlOutput("upload.data.print", container = shiny::span)
+      )
+    )
+  )
+)

data-raw/data-upload-examples.R

@@ -0,0 +1,5 @@
+mtcars |> dplyr::mutate(record_id=seq_len(n()),
+                        name=rownames(mtcars)
+                        ) |>
+  dplyr::select(record_id,dplyr::everything()) |>
+  write.csv(here::here("data/mtcars_redcap.csv"),row.names = FALSE)

data/mtcars_redcap.csv

@@ -0,0 +1,33 @@
+"record_id","mpg","cyl","disp","hp","drat","wt","qsec","vs","am","gear","carb","name"
+1,21,6,160,110,3.9,2.62,16.46,0,1,4,4,"Mazda RX4"
+2,21,6,160,110,3.9,2.875,17.02,0,1,4,4,"Mazda RX4 Wag"
+3,22.8,4,108,93,3.85,2.32,18.61,1,1,4,1,"Datsun 710"
+4,21.4,6,258,110,3.08,3.215,19.44,1,0,3,1,"Hornet 4 Drive"
+5,18.7,8,360,175,3.15,3.44,17.02,0,0,3,2,"Hornet Sportabout"
+6,18.1,6,225,105,2.76,3.46,20.22,1,0,3,1,"Valiant"
+7,14.3,8,360,245,3.21,3.57,15.84,0,0,3,4,"Duster 360"
+8,24.4,4,146.7,62,3.69,3.19,20,1,0,4,2,"Merc 240D"
+9,22.8,4,140.8,95,3.92,3.15,22.9,1,0,4,2,"Merc 230"
+10,19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4,"Merc 280"
+11,17.8,6,167.6,123,3.92,3.44,18.9,1,0,4,4,"Merc 280C"
+12,16.4,8,275.8,180,3.07,4.07,17.4,0,0,3,3,"Merc 450SE"
+13,17.3,8,275.8,180,3.07,3.73,17.6,0,0,3,3,"Merc 450SL"
+14,15.2,8,275.8,180,3.07,3.78,18,0,0,3,3,"Merc 450SLC"
+15,10.4,8,472,205,2.93,5.25,17.98,0,0,3,4,"Cadillac Fleetwood"
+16,10.4,8,460,215,3,5.424,17.82,0,0,3,4,"Lincoln Continental"
+17,14.7,8,440,230,3.23,5.345,17.42,0,0,3,4,"Chrysler Imperial"
+18,32.4,4,78.7,66,4.08,2.2,19.47,1,1,4,1,"Fiat 128"
+19,30.4,4,75.7,52,4.93,1.615,18.52,1,1,4,2,"Honda Civic"
+20,33.9,4,71.1,65,4.22,1.835,19.9,1,1,4,1,"Toyota Corolla"
+21,21.5,4,120.1,97,3.7,2.465,20.01,1,0,3,1,"Toyota Corona"
+22,15.5,8,318,150,2.76,3.52,16.87,0,0,3,2,"Dodge Challenger"
+23,15.2,8,304,150,3.15,3.435,17.3,0,0,3,2,"AMC Javelin"
+24,13.3,8,350,245,3.73,3.84,15.41,0,0,3,4,"Camaro Z28"
+25,19.2,8,400,175,3.08,3.845,17.05,0,0,3,2,"Pontiac Firebird"
+26,27.3,4,79,66,4.08,1.935,18.9,1,1,4,1,"Fiat X1-9"
+27,26,4,120.3,91,4.43,2.14,16.7,0,1,5,2,"Porsche 914-2"
+28,30.4,4,95.1,113,3.77,1.513,16.9,1,1,5,2,"Lotus Europa"
+29,15.8,8,351,264,4.22,3.17,14.5,0,1,5,4,"Ford Pantera L"
+30,19.7,6,145,175,3.62,2.77,15.5,0,1,5,6,"Ferrari Dino"
+31,15,8,301,335,3.54,3.57,14.6,0,1,5,8,"Maserati Bora"
+32,21.4,4,121,109,4.11,2.78,18.6,1,1,4,2,"Volvo 142E"

man/file_extension.Rd

@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/utils.r
+\name{file_extension}
+\alias{file_extension}
+\title{Helper to import files correctly}
+\usage{
+file_extension(filenames)
+}
+\arguments{
+\item{filenames}{file names}
+}
+\value{
+character vector
+}
+\description{
+Helper to import files correctly
+}
+\examples{
+file_extension(list.files(here::here(""))[[2]])[[1]]
+}

man/read_input.Rd

@@ -0,0 +1,22 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/utils.r
+\name{read_input}
+\alias{read_input}
+\title{Flexible file import based on extension}
+\usage{
+read_input(file, consider.na = c("NA", "\\"\\"", ""))
+}
+\arguments{
+\item{file}{file name}
+
+\item{consider.na}{character vector of strings to consider as NAs}
+}
+\value{
+tibble
+}
+\description{
+Flexible file import based on extension
+}
+\examples{
+read_input("https://raw.githubusercontent.com/agdamsbo/cognitive.index.lookup/main/data/sample.csv")
+}

man/server_factory.Rd

@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/shiny_cast.R
+\name{server_factory}
+\alias{server_factory}
+\title{Shiny server factory}
+\usage{
+server_factory()
+}
+\value{
+shiny server
+}
+\description{
+Shiny server factory
+}

man/shiny_cast.Rd

@@ -0,0 +1,18 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/shiny_cast.R
+\name{shiny_cast}
+\alias{shiny_cast}
+\title{Launch the included Shiny-app for database casting and upload}
+\usage{
+shiny_cast()
+}
+\value{
+shiny app
+}
+\description{
+Launch the included Shiny-app for database casting and upload
+}
+\examples{
+# shiny_cast()
+
+}

man/ui_factory.Rd

@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/shiny_cast.R
+\name{ui_factory}
+\alias{ui_factory}
+\title{UI factory for shiny app}
+\usage{
+ui_factory()
+}
+\value{
+shiny ui
+}
+\description{
+UI factory for shiny app
+}

renv.lock

@@ -428,13 +428,13 @@
     },
     "renv": {
       "Package": "renv",
-      "Version": "1.0.3",
+      "Version": "1.0.4",
       "Source": "Repository",
       "Repository": "CRAN",
       "Requirements": [
         "utils"
       ],
-      "Hash": "41b847654f567341725473431dd0d5ab"
+      "Hash": "11abaf7c540ff33f94514d50f929bfd1"
     },
     "rlang": {
       "Package": "rlang",
@@ -512,7 +512,7 @@
     },
     "tidyr": {
       "Package": "tidyr",
-      "Version": "1.3.0",
+      "Version": "1.3.1",
       "Source": "Repository",
       "Repository": "CRAN",
       "Requirements": [
@@ -531,7 +531,7 @@
         "utils",
         "vctrs"
       ],
-      "Hash": "e47debdc7ce599b070c8e78e8ac0cfcf"
+      "Hash": "915fb7ce036c22a6a33b5a8adb712eb1"
     },
     "tidyselect": {
       "Package": "tidyselect",

renv/activate.R

@@ -2,7 +2,7 @@
 local({
 
   # the requested version of renv
-  version <- "1.0.3"
+  version <- "1.0.4"
   attr(version, "sha") <- NULL
 
   # the project directory
@@ -31,6 +31,14 @@ local({
     if (!is.null(override))
       return(override)
 
+    # if we're being run in a context where R_LIBS is already set,
+    # don't load -- presumably we're being run as a sub-process and
+    # the parent process has already set up library paths for us
+    rcmd <- Sys.getenv("R_CMD", unset = NA)
+    rlibs <- Sys.getenv("R_LIBS", unset = NA)
+    if (!is.na(rlibs) && !is.na(rcmd))
+      return(FALSE)
+
     # next, check environment variables
     # TODO: prefer using the configuration one in the future
     envvars <- c(
@@ -50,9 +58,22 @@ local({
 
   })
 
-  if (!enabled)
+  # bail if we're not enabled
+  if (!enabled) {
+
+    # if we're not enabled, we might still need to manually load
+    # the user profile here
+    profile <- Sys.getenv("R_PROFILE_USER", unset = "~/.Rprofile")
+    if (file.exists(profile)) {
+      cfg <- Sys.getenv("RENV_CONFIG_USER_PROFILE", unset = "TRUE")
+      if (tolower(cfg) %in% c("true", "t", "1"))
+        sys.source(profile, envir = globalenv())
+    }
+
     return(FALSE)
 
+  }
+
   # avoid recursion
   if (identical(getOption("renv.autoloader.running"), TRUE)) {
     warning("ignoring recursive attempt to run renv autoloader")
@@ -1041,7 +1062,7 @@ local({
     # if jsonlite is loaded, use that instead
     if ("jsonlite" %in% loadedNamespaces()) {
   
-      json <- catch(renv_json_read_jsonlite(file, text))
+      json <- tryCatch(renv_json_read_jsonlite(file, text), error = identity)
       if (!inherits(json, "error"))
         return(json)
   
@@ -1050,7 +1071,7 @@ local({
     }
   
     # otherwise, fall back to the default JSON reader
-    json <- catch(renv_json_read_default(file, text))
+    json <- tryCatch(renv_json_read_default(file, text), error = identity)
     if (!inherits(json, "error"))
       return(json)
   
@@ -1063,14 +1084,14 @@ local({
   }
   
   renv_json_read_jsonlite <- function(file = NULL, text = NULL) {
-    text <- paste(text %||% read(file), collapse = "\n")
+    text <- paste(text %||% readLines(file, warn = FALSE), collapse = "\n")
     jsonlite::fromJSON(txt = text, simplifyVector = FALSE)
   }
   
   renv_json_read_default <- function(file = NULL, text = NULL) {
   
     # find strings in the JSON
-    text <- paste(text %||% read(file), collapse = "\n")
+    text <- paste(text %||% readLines(file, warn = FALSE), collapse = "\n")
     pattern <- '["](?:(?:\\\\.)|(?:[^"\\\\]))*?["]'
     locs <- gregexpr(pattern, text, perl = TRUE)[[1]]
   
@@ -1118,14 +1139,14 @@ local({
     map <- as.list(map)
   
     # remap strings in object
-    remapped <- renv_json_remap(json, map)
+    remapped <- renv_json_read_remap(json, map)
   
     # evaluate
     eval(remapped, envir = baseenv())
   
   }
   
-  renv_json_remap <- function(json, map) {
+  renv_json_read_remap <- function(json, map) {
   
     # fix names
     if (!is.null(names(json))) {
@@ -1152,7 +1173,7 @@ local({
     # recurse
     if (is.recursive(json)) {
       for (i in seq_along(json)) {
-        json[i] <- list(renv_json_remap(json[[i]], map))
+        json[i] <- list(renv_json_read_remap(json[[i]], map))
       }
     }
   

vignettes/Database creation.Rmd

@@ -0,0 +1,81 @@
+---
+title: "Database casting"
+output: rmarkdown::html_vignette
+vignette: >
+  %\VignetteIndexEntry{Database casting}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+---
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>"
+)
+```
+
+```{r setup}
+library(REDCapCAST)
+```
+
+# Easy data set to data base workflow
+
+THe first iteration of a dataset to data dictionary function is the `ds2dd()`, which creates a very basic data dictionary with all variables stored as text. This is sufficient for just storing old datasets/spreadsheets securely in REDCap.
+
+```{r}
+mtcars |>
+  dplyr::mutate(record_id = seq_len(dplyr::n())) |>
+  ds2dd()
+```
+
+The more advanced `ds2dd_detailed()` is a natural development. It will try to apply the most common data classes for data validation and will assume that the first column is the id number. It outputs a list with the dataset with modified variable names to comply with REDCap naming conventions and a data dictionary. 
+
+The dataset should be correctly formatted for the data dictionary to preserve as much information as possible.
+
+```{r}
+dd_ls <- mtcars |>
+  dplyr::mutate(record_id = seq_len(dplyr::n())) |>
+  dplyr::select(record_id, dplyr::everything()) |>
+  ds2dd_detailed()
+dd_ls |> str()
+```
+
+Additional specifications to the DataDictionary can be made manually, or it can be uploaded and modified manually in the graphical user interface on the web page.
+
+## Step 3 - Meta data upload
+
+Now the DataDictionary can be exported as a spreadsheet and uploaded or it can be uploaded using the `REDCapR` package (only projects with "Development" status).
+
+Use one of the two approaches below:
+
+### Manual upload
+
+```{r eval=FALSE}
+write.csv(dd_ls$meta, "datadictionary.csv")
+```
+
+### Upload with `REDCapR`
+
+```{r eval=FALSE}
+REDCapR::redcap_metadata_write(
+  dd_ls$meta,
+  redcap_uri = keyring::key_get("DB_URI"),
+  token = keyring::key_get("DB_TOKEN")
+)
+```
+
+In the ["REDCap R Handbook"](https://agdamsbo.github.io/redcap-r-handbook/) more is written on interfacing with REDCap in R using the `library(keyring)`to store credentials in [chapter 1.1](https://agdamsbo.github.io/redcap-r-handbook/access.html#sec-getting-access).
+
+## Step 4 - Data upload
+
+The same two options are available for data upload as meta data upload: manual or through `REDCapR`.
+
+Only the latter is shown here.
+
+```{r eval=FALSE}
+REDCapR::redcap_write(
+  dd_ls$data,
+  redcap_uri = keyring::key_get("DB_URI"),
+  token = keyring::key_get("DB_TOKEN")
+)
+```

vignettes/Shiny casting.Rmd

@@ -0,0 +1,30 @@
+---
+title: "Introduction"
+output: rmarkdown::html_vignette
+vignette: >
+  %\VignetteIndexEntry{Introduction}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+---
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>"
+)
+```
+
+```{r setup}
+library(REDCapCAST)
+```
+
+To make the easiest possible transistion from spreadsheet/dataset to REDCap, I have created a small Shiny app, which adds a graphical interface to the casting of a data dictionary and data upload. Install the package and run the app as follows:
+
+```{r}
+require(REDCapCAST)
+shiny_cast()
+```
+
+The app will launch in a new window and the interface should be fairly self-explanatory.
+The app only provides the most basic functionality, but might be extended in the future.
+