globalVariables(c("data",
"download.file",
"unzip",
"item_hash",
"item-hash",
"hash",
"hash-list",
"as_tibble",
"json",
"entry-number",
"desc",
"map_chr",
"items",
"key",
"n",
"timestamp",
"type",
"unnest",
"datatype",
"field",
".x",
":=",
".curie",
"register",
"from",
"to",
"cardinality",
"text",
"."))
#' Return column names missing from a data frame
#'
#' @param .data Data frame.
#' @param ... names of columns.
#' @return A character vector of column names that aren't in `.data`.
missing_col_names <- function(.data, ...) {
UseMethod("missing_col_names")
}
missing_col_names.data.frame <- function(.data, ...) {
col_names <- purrr::map_chr(rlang::enquos(...), rlang::quo_text)
col_names[!(col_names %in% colnames(.data))]
}
#' Construct a zero-row tibble with given column names
#'
#' @description
#' All columns will be `logical` so that they don't disturb existing columns
#' when appended with [dplyr::bind_rows()]`
#'
#' @param col_names Character vector of column names
blank_tibble <- function(col_names) {
columns <- purrr::map(col_names, ~ rlang::expr(list()))
names(columns) <- col_names
tibble::tibble(!!! columns)
}
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