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https://github.com/agdamsbo/REDCapCAST.git
synced 2024-11-22 05:20:23 +01:00
Fixed bug introduced in previous commit, added test to check for bug
Also started working on issue #10
This commit is contained in:
Paul W. Egeler, M.S., GStat
parent
76420b527c
commit
e7be5c1808
@ -10,8 +10,11 @@
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#' @param metadata Project metadata (the data dictionary). May be a
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#' \code{data.frame}, \code{response}, or \code{character} vector containing
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#' JSON from an API call.
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#' @param primary_table_label Name of the label given to the list element for
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#' the primary output table (as described in *README.md*).
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#' @param primary_table_name Name given to the list element for the primary
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#' output table (as described in \emph{README.md}). Ignored if
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#' \code{forms = 'all'}.
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#' @param forms Indicate whether to create separate tables for repeating
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#' instruments only or for all forms.
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#' @author Paul W. Egeler, M.S., GStat
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#' @examples
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#' \dontrun{
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@ -66,13 +69,20 @@
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#' # Split the tables
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#' REDCapRITS::REDCap_split(data, metadata)
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#' }
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#' @return A list of \code{"data.frame"}s: one base table and zero or more
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#' tables for each repeating instrument.
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#' @return A list of \code{"data.frame"}s. The number of tables will differ
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#' depending on the \code{forms} option selected.
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#' \itemize{
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#' \item \code{'repeating'}: one base table and one or more
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#' tables for each repeating instrument.
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#' \item \code{'all'}: a data.frame for each instrument, regardless of
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#' whether it is a repeating instrument or not.
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#' }
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#' @include process_user_input.r utils.r
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#' @export
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REDCap_split <- function(records,
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metadata,
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primary_table_label = ""
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primary_table_name = "",
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forms = c("repeating", "all")
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) {
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# Process user input
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@ -82,8 +92,11 @@ REDCap_split <- function(records,
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# Get the variable names in the dataset
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vars_in_data <- names(records)
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# Match arg for forms
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forms <- match.arg(forms)
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# Check to see if there were any repeating instruments
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if (!"redcap_repeat_instrument" %in% vars_in_data) {
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if (forms == "repeating" && !"redcap_repeat_instrument" %in% vars_in_data) {
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stop("There are no repeating instruments in this dataset.")
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}
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@ -107,56 +120,55 @@ REDCap_split <- function(records,
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)
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)
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# Variables to be at the beginning of each repeating instrument
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repeat_instrument_fields <- grep(
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"^redcap_repeat.*",
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vars_in_data,
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value = TRUE
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)
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# Identify the subtables in the data
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subtables <- unique(records$redcap_repeat_instrument)
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subtables <- subtables[subtables != ""]
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# Split the table based on instrument
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out <- split.data.frame(records, records$redcap_repeat_instrument)
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if (primary_table_label %in% subtables) {
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warning(
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"The label given to the primary table is already used by a repeating instrument.\n",
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"The primary table label will be left blank."
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if ("redcap_repeat_instrument" %in% vars_in_data) {
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# Variables to be at the beginning of each repeating instrument
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repeat_instrument_fields <- grep(
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"^redcap_repeat.*",
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vars_in_data,
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value = TRUE
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)
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} else if (primary_table_label > "") {
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names(out)[[which(names(out) == "")]] <- primary_table_label
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}
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# Delete the variables that are not relevant
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for (i in names(out)) {
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# Identify the subtables in the data
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subtables <- unique(records$redcap_repeat_instrument)
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subtables <- subtables[subtables != ""]
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if (i == primary_table_label) {
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out_fields <- which(
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vars_in_data %in% c(
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universal_fields,
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fields[!fields[,2] %in% subtables, 1]
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)
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)
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out[[which(names(out) == primary_table_label)]] <- out[[which(names(out) == primary_table_label)]][out_fields]
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} else {
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out_fields <- which(
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vars_in_data %in% c(
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universal_fields,
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repeat_instrument_fields,
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fields[fields[,2] == i, 1]
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)
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)
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out[[i]] <- out[[i]][out_fields]
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# Split the table based on instrument
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out <- split.data.frame(records, records$redcap_repeat_instrument)
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if (forms == "repeating" && primary_table_name %in% subtables) {
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warning("The label given to the primary table is already used by a repeating instrument. The primary table label will be left blank.")
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primary_table_name <- ""
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} else if (primary_table_name > "") {
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names(out)[[which(names(out) == "")]] <- primary_table_name
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}
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# Delete the variables that are not relevant
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for (i in names(out)) {
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if (i == primary_table_name) {
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out_fields <- which(
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vars_in_data %in% c(
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universal_fields,
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fields[!fields[,2] %in% subtables, 1]
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)
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)
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out[[which(names(out) == primary_table_name)]] <- out[[which(names(out) == primary_table_name)]][out_fields]
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} else {
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out_fields <- which(
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vars_in_data %in% c(
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universal_fields,
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repeat_instrument_fields,
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fields[fields[,2] == i, 1]
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)
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)
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out[[i]] <- out[[i]][out_fields]
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}
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}
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}
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out
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@ -4,7 +4,8 @@
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\alias{REDCap_split}
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\title{Split REDCap repeating instruments table into multiple tables}
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\usage{
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REDCap_split(records, metadata, primary_table_label = "")
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REDCap_split(records, metadata, primary_table_name = "",
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forms = c("repeating", "all"))
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}
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\arguments{
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\item{records}{Exported project records. May be a \code{data.frame},
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@ -15,12 +16,22 @@ call.}
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\code{data.frame}, \code{response}, or \code{character} vector containing
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JSON from an API call.}
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\item{primary_table_label}{Name of the label given to the list element for
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the primary output table (as described in *README.md*).}
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\item{primary_table_name}{Name given to the list element for the primary
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output table (as described in \emph{README.md}). Ignored if
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\code{forms = 'all'}.}
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\item{forms}{Indicate whether to create separate tables for repeating
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instruments only or for all forms.}
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}
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\value{
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A list of \code{"data.frame"}s: one base table and zero or more
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tables for each repeating instrument.
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A list of \code{"data.frame"}s. The number of tables will differ
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depending on the \code{forms} option selected.
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\itemize{
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\item \code{'repeating'}: one base table and one or more
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tables for each repeating instrument.
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\item \code{'all'}: a data.frame for each instrument, regardless of
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whether it is a repeating instrument or not.
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}
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}
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\description{
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This will take output from a REDCap export and split it into a base table
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38
R/tests/testthat/test-primary-table-name.R
Normal file
38
R/tests/testthat/test-primary-table-name.R
Normal file
@ -0,0 +1,38 @@
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context("Primary table name processing")
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# Global variables -------------------------------------------------------
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metadata <- jsonlite::fromJSON(
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get_data_location(
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"ExampleProject_metadata.json"
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)
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)
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records <- jsonlite::fromJSON(
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get_data_location(
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"ExampleProject_records.json"
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)
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)
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ref_hash <- "2c8b6531597182af1248f92124161e0c"
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# Tests -------------------------------------------------------------------
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test_that("Will not use a repeating instrument name for primary table", {
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redcap_output_json1 <- expect_warning(
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REDCap_split(records, metadata, "sale"),
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"primary table"
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)
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expect_known_hash(redcap_output_json1, ref_hash)
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})
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test_that("Names are set correctly and output is identical", {
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redcap_output_json2 <- REDCap_split(records, metadata, "main")
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expect_identical(names(redcap_output_json2), c("main", "sale"))
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expect_known_hash(setNames(redcap_output_json2, c("", "sale")), ref_hash)
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})
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