# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

#' @importFrom utils object.size
.serialize_arrow_r_metadata <- function(x) {
  assert_is(x, "list")

  # drop problems attributes (most likely from readr)
  x[["attributes"]][["problems"]] <- NULL

  out <- serialize(x, NULL, ascii = TRUE)

  # if the metadata is over 100 kB, compress
  if (option_compress_metadata() && object.size(out) > 100000) {
    out_comp <- serialize(memCompress(out, type = "gzip"), NULL, ascii = TRUE)

    # but ensure that the compression+serialization is effective.
    if (object.size(out) > object.size(out_comp)) out <- out_comp
  }

  rawToChar(out)
}

.unserialize_arrow_r_metadata <- function(x) {
  tryCatch(
    expr = {
      out <- unserialize(charToRaw(x))

      # if this is still raw, try decompressing
      if (is.raw(out)) {
        out <- unserialize(memDecompress(out, type = "gzip"))
      }
      out
    },
    error = function(e) {
      warning("Invalid metadata$r", call. = FALSE)
      NULL
    }
  )
}

#' @importFrom rlang trace_back
apply_arrow_r_metadata <- function(x, r_metadata) {
  tryCatch(
    expr = {
      columns_metadata <- r_metadata$columns
      if (is.data.frame(x)) {
        if (length(names(x)) && !is.null(columns_metadata)) {
          for (name in intersect(names(columns_metadata), names(x))) {
            x[[name]] <- apply_arrow_r_metadata(x[[name]], columns_metadata[[name]])
          }
        }
      } else if (is.list(x) && !inherits(x, "POSIXlt") && !is.null(columns_metadata)) {
        # If we have a list and "columns_metadata" this applies row-level metadata
        # inside of a column in a dataframe.

        # However, if we are inside of a dplyr collection (including all datasets),
        # we cannot apply this row-level metadata, since the order of the rows is
        # not guaranteed to be the same, so don't even try, but warn what's going on
        trace <- trace_back()
        # TODO: remove `trace$calls %||% trace$call` once rlang > 0.4.11 is released
        in_dplyr_collect <- any(map_lgl(trace$calls %||% trace$call, function(x) {
          grepl("collect.arrow_dplyr_query", x, fixed = TRUE)[[1]]
        }))
        if (in_dplyr_collect) {
          warning(
            "Row-level metadata is not compatible with this operation and has ",
            "been ignored",
            call. = FALSE
          )
        } else {
          x <- map2(x, columns_metadata, function(.x, .y) {
            apply_arrow_r_metadata(.x, .y)
          })
        }
        x
      }

      if (!is.null(r_metadata$attributes)) {
        attributes(x)[names(r_metadata$attributes)] <- r_metadata$attributes
        if (inherits(x, "POSIXlt")) {
          # We store POSIXlt as a StructArray, which is translated back to R
          # as a data.frame, but while data frames have a row.names = c(NA, nrow(x))
          # attribute, POSIXlt does not, so since this is now no longer an object
          # of class data.frame, remove the extraneous attribute
          attr(x, "row.names") <- NULL
        }
        if (!is.null(attr(x, ".group_vars")) && requireNamespace("dplyr", quietly = TRUE)) {
          x <- dplyr::group_by(x, !!!syms(attr(x, ".group_vars")))
          attr(x, ".group_vars") <- NULL
        }
      }
    },
    error = function(e) {
      warning("Invalid metadata$r", call. = FALSE)
    }
  )
  x
}

remove_attributes <- function(x) {
  removed_attributes <- character()
  if (identical(class(x), c("tbl_df", "tbl", "data.frame"))) {
    removed_attributes <- c("class", "row.names", "names")
  } else if (inherits(x, "data.frame")) {
    removed_attributes <- c("row.names", "names")
  } else if (inherits(x, "factor")) {
    removed_attributes <- c("class", "levels")
  } else if (inherits(x, c("integer64", "Date", "arrow_binary", "arrow_large_binary"))) {
    removed_attributes <- c("class")
  } else if (inherits(x, "arrow_fixed_size_binary")) {
    removed_attributes <- c("class", "byte_width")
  } else if (inherits(x, "POSIXct")) {
    removed_attributes <- c("class", "tzone")
  } else if (inherits(x, "hms") || inherits(x, "difftime")) {
    removed_attributes <- c("class", "units")
  }
  removed_attributes
}

arrow_attributes <- function(x, only_top_level = FALSE) {
  if (inherits(x, "grouped_df")) {
    # Keep only the group var names, not the rest of the cached data that dplyr
    # uses, which may be large
    if (requireNamespace("dplyr", quietly = TRUE)) {
      gv <- dplyr::group_vars(x)
      x <- dplyr::ungroup(x)
      # ungroup() first, then set attribute, bc ungroup() would erase it
      attr(x, ".group_vars") <- gv
    } else {
      # Regardless, we shouldn't keep groups around
      attr(x, "groups") <- NULL
    }
  }
  att <- attributes(x)

  removed_attributes <- remove_attributes(x)

  att <- att[setdiff(names(att), removed_attributes)]
  if (isTRUE(only_top_level)) {
    return(att)
  }

  if (is.data.frame(x)) {
    columns <- map(x, arrow_attributes)
    out <- if (length(att) || !all(map_lgl(columns, is.null))) {
      list(attributes = att, columns = columns)
    }
    return(out)
  }

  columns <- NULL
  attempt_to_save_row_level <- getOption("arrow.preserve_row_level_metadata", FALSE) &&
    is.list(x) && !inherits(x, "POSIXlt")
  if (attempt_to_save_row_level) {
    # However, if we are inside of a dplyr collection (including all datasets),
    # we cannot apply this row-level metadata, since the order of the rows is
    # not guaranteed to be the same, so don't even try, but warn what's going on
    trace <- trace_back()
    # TODO: remove `trace$calls %||% trace$call` once rlang > 0.4.11 is released
    in_dataset_write <- any(map_lgl(trace$calls %||% trace$call, function(x) {
      grepl("write_dataset", x, fixed = TRUE)[[1]]
    }))
    if (in_dataset_write) {
      warning(
        "Row-level metadata is not compatible with datasets and will be discarded",
        call. = FALSE
      )
    } else {
      # for list columns, we also keep attributes of each
      # element in columns
      columns <- map(x, arrow_attributes)
    }
    if (all(map_lgl(columns, is.null))) {
      columns <- NULL
    }
  } else if (inherits(x, c("sfc", "sf"))) {
    # Check if there are any columns that look like sf columns, warn that we will
    # not be saving this data for now (but only if arrow.preserve_row_level_metadata
    # is set to FALSE)
    warning(
      "One of the columns given appears to be an `sfc` SF column. Due to their unique ",
      "nature, these columns do not convert to Arrow well. We are working on ",
      "better ways to do this, but in the interim we recommend converting any `sfc` ",
      "columns to WKB (well-known binary) columns before using them with Arrow ",
      "(for example, with `sf::st_as_binary(col)`).",
      call. = FALSE
    )
  }

  if (length(att) || !is.null(columns)) {
    list(attributes = att, columns = columns)
  } else {
    NULL
  }
}