R/rows_update.R

In duckplyr: A 'DuckDB'-Backed Version of 'dplyr'

# Generated by 02-duckplyr_df-methods.R
#' @export
rows_update.duckplyr_df <- function(x, y, by = NULL, ..., unmatched = c("error", "ignore"), copy = FALSE, in_place = FALSE) {
  # Our implementation
  rel_try(
    "No relational implementation for rows_update()" = TRUE,
    {
      return(out)
    }
  )

  # dplyr forward
  rows_update <- dplyr$rows_update.data.frame
  out <- rows_update(x, y, by, ..., unmatched = unmatched, copy = copy, in_place = in_place)
  return(out)

  # dplyr implementation
  check_dots_empty()
  rows_df_in_place(in_place)

  y <- auto_copy(x, y, copy = copy)

  by <- rows_check_by(by, y)

  rows_check_x_contains_y(x, y)
  rows_check_contains_by(x, by, "x")
  rows_check_contains_by(y, by, "y")

  x_key <- dplyr_col_select(x, by)
  y_key <- dplyr_col_select(y, by)

  rows_check_unique(y_key, "y")

  args <- vec_cast_common(x = x_key, y = y_key)
  x_key <- args$x
  y_key <- args$y

  values_names <- setdiff(names(y), names(y_key))

  x_values <- dplyr_col_select(x, values_names)
  y_values <- dplyr_col_select(y, values_names)
  y_values <- rows_cast_y(y_values, x_values)

  keep <- rows_check_y_unmatched(x_key, y_key, unmatched)

  if (!is.null(keep)) {
    y_key <- dplyr_row_slice(y_key, keep)
    y_values <- dplyr_row_slice(y_values, keep)
  }

  loc <- vec_match(x_key, y_key)
  match <- !is.na(loc)

  y_loc <- loc[match]
  x_loc <- which(match)

  y_values <- dplyr_row_slice(y_values, y_loc)

  x_values <- vec_assign(x_values, x_loc, y_values)
  x_values <- dplyr_new_list(x_values)

  x <- dplyr_col_modify(x, x_values)

  x
}

duckplyr_rows_update <- function(x, y, ...) {
  try_fetch(
    {
      x <- as_duckplyr_df(x)
      y <- as_duckplyr_df(y)
    },
    error = function(e) {
      testthat::skip(conditionMessage(e))
    }
  )
  out <- rows_update(x, y, ...)
  class(out) <- setdiff(class(out), "duckplyr_df")
  out
}