# 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. test_that("convert_array() errors for invalid arrays", { array <- as_nanoarrow_array(1:10) nanoarrow_array_set_schema( array, na_string(), validate = FALSE ) expect_error( convert_array(array), "Expected array with 3 buffer" ) }) test_that("convert_array() errors for unsupported ptype", { array <- as_nanoarrow_array(1:10) # an S3 unsupported type expect_error( convert_array(array, structure(list(), class = "some_class")), "Can't convert array to R vector of type some_class" ) # A non-S3 unsupported type expect_error( convert_array(array, environment()), "Can't convert array to R vector of type environment" ) # An array with a name to an unsupported type struct_array <- as_nanoarrow_array(data.frame(x = 1L)) expect_error( convert_array(struct_array$children$x, environment()), "Can't convert `x`" ) }) test_that("convert_array() errors for unsupported array", { unsupported_array <- nanoarrow_array_init(na_interval_day_time()) expect_error( convert_array(as_nanoarrow_array(unsupported_array)), "Can't infer R vector type for " ) }) test_that("convert to vector works for data.frame", { df <- data.frame(a = 1L, b = "two", c = 3, d = TRUE, stringsAsFactors = FALSE) array <- as_nanoarrow_array(df) expect_identical(convert_array(array, NULL), df) expect_identical(convert_array(array, df), df) expect_error( convert_array(array, data.frame(a = integer(), b = raw())), "Expected data.frame\\(\\) ptype with 4 column\\(s\\) but found 2 column\\(s\\)" ) bad_ptype <- data.frame(a = integer(), b = raw(), c = double(), d = integer()) expect_error( convert_array(array, bad_ptype), "Can't convert `b` to R vector of type raw" ) }) test_that("convert to vector works for partial_frame", { array <- as_nanoarrow_array( data.frame(a = 1L, b = "two", stringsAsFactors = FALSE) ) expect_identical( convert_array(array, vctrs::partial_frame()), data.frame(a = 1L, b = "two", stringsAsFactors = FALSE) ) }) test_that("convert to vector works for extension -> data.frame()", { array <- nanoarrow_extension_array( data.frame(x = c(TRUE, FALSE, NA, FALSE, TRUE)), "some_ext" ) expect_warning( expect_identical( convert_array(array, data.frame(x = logical())), data.frame(x = c(TRUE, FALSE, NA, FALSE, TRUE)) ), "Converting unknown extension" ) }) test_that("convert to vector works for dictionary -> data.frame()", { array <- as_nanoarrow_array(c(0L, 1L, 2L, 1L, 0L)) array$dictionary <- as_nanoarrow_array(data.frame(x = c(TRUE, FALSE, NA))) expect_identical( convert_array(array, data.frame(x = logical())), data.frame(x = c(TRUE, FALSE, NA, FALSE, TRUE)) ) }) test_that("convert to vector works for function()", { tibble_or_bust <- function(array, ptype) { if (is.data.frame(ptype)) { ptype <- tibble::as_tibble(ptype) ptype[] <- Map(tibble_or_bust, list(NULL), ptype) } ptype } df_nested_df <- as.data.frame( tibble::tibble(a = 1L, b = "two", c = data.frame(a = 3)) ) array_nested <- as_nanoarrow_array(df_nested_df) expect_identical( convert_array(array_nested, tibble_or_bust), tibble::tibble(a = 1L, b = "two", c = tibble::tibble(a = 3)) ) }) test_that("convert to vector works for tibble", { array <- as_nanoarrow_array( data.frame(a = 1L, b = "two", stringsAsFactors = FALSE) ) expect_identical( convert_array(array, tibble::tibble(a = integer(), b = character())), tibble::tibble(a = 1L, b = "two") ) # Check nested tibble at both levels tbl_nested_df <- tibble::tibble(a = 1L, b = "two", c = data.frame(a = 3)) array_nested <- as_nanoarrow_array(tbl_nested_df) expect_identical( convert_array(array_nested, tbl_nested_df), tbl_nested_df ) df_nested_tbl <- as.data.frame(tbl_nested_df) df_nested_tbl$c <- tibble::as_tibble(df_nested_tbl$c) expect_identical( convert_array(array_nested, df_nested_tbl), df_nested_tbl ) }) test_that("convert to vector works for struct-style vectors", { array <- as_nanoarrow_array(as.POSIXlt("2021-01-01", tz = "America/Halifax")) expect_identical( convert_array(array), as.data.frame( unclass(as.POSIXlt("2021-01-01", tz = "America/Halifax")), stringsAsFactors = FALSE ) ) array <- as_nanoarrow_array(as.POSIXlt("2021-01-01", tz = "America/Halifax")) expect_identical( convert_array(array, as.POSIXlt("2021-01-01", tz = "America/Halifax")), as.POSIXlt("2021-01-01", tz = "America/Halifax") ) }) test_that("convert to vector works for unspecified()", { array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 # implicit for null type expect_identical( convert_array(array, to = NULL), vctrs::vec_cast(rep(NA, 10), vctrs::unspecified()) ) # explicit for null type expect_identical( convert_array(array, vctrs::unspecified()), vctrs::vec_cast(rep(NA, 10), vctrs::unspecified()) ) # explicit for non-null type that is all NAs array <- as_nanoarrow_array(rep(NA_integer_, 10)) expect_identical( convert_array(array, vctrs::unspecified()), vctrs::vec_cast(rep(NA, 10), vctrs::unspecified()) ) # explicit for non-null type that is not all NAs array <- as_nanoarrow_array(c(1L, rep(NA_integer_, 9))) expect_warning( expect_identical( convert_array(array, vctrs::unspecified()), vctrs::vec_cast(rep(NA, 10), vctrs::unspecified()) ), class = "nanoarrow_warning_lossy_conversion" ) }) test_that("convert to vector works for valid logical()", { skip_if_not_installed("arrow") arrow_numeric_types <- list( int8 = arrow::int8(), uint8 = arrow::uint8(), int16 = arrow::int16(), uint16 = arrow::uint16(), int32 = arrow::int32(), uint32 = arrow::uint32(), int64 = arrow::int64(), uint64 = arrow::uint64(), float32 = arrow::float32(), float64 = arrow::float64() ) vals <- c(NA, 0:10) for (nm in names(arrow_numeric_types)) { expect_identical( convert_array( as_nanoarrow_array(vals, schema = arrow_numeric_types[[!!nm]]), logical() ), vals != 0 ) } vals_no_na <- 0:10 for (nm in names(arrow_numeric_types)) { expect_identical( convert_array( as_nanoarrow_array(vals_no_na, schema = arrow_numeric_types[[!!nm]]), logical() ), vals_no_na != 0 ) } # Boolean array to logical expect_identical( convert_array( as_nanoarrow_array(c(NA, TRUE, FALSE), schema = arrow::boolean()), logical() ), c(NA, TRUE, FALSE) ) expect_identical( convert_array( as_nanoarrow_array(c(TRUE, FALSE), schema = arrow::boolean()), logical() ), c(TRUE, FALSE) ) }) test_that("convert to vector works for null -> logical()", { array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 expect_identical( convert_array(array, logical()), rep(NA, 10) ) }) test_that("convert to vector works for extension -> logical()", { array <- nanoarrow_extension_array(c(TRUE, FALSE, NA), "some_ext") expect_warning( expect_identical( convert_array(array, logical()), c(TRUE, FALSE, NA) ), "Converting unknown extension" ) }) test_that("convert to vector works for dictionary -> logical()", { array <- as_nanoarrow_array(c(0L, 1L, 2L, 1L, 0L)) array$dictionary <- as_nanoarrow_array(c(TRUE, FALSE, NA)) expect_identical( convert_array(array, logical()), c(TRUE, FALSE, NA, FALSE, TRUE) ) }) test_that("convert to vector errors for bad array to logical()", { expect_error( convert_array(as_nanoarrow_array(letters), logical()), "Can't convert array to R vector of type logical" ) }) test_that("convert to vector works for valid integer()", { skip_if_not_installed("arrow") arrow_int_types <- list( int8 = arrow::int8(), uint8 = arrow::uint8(), int16 = arrow::int16(), uint16 = arrow::uint16(), int32 = arrow::int32(), uint32 = arrow::uint32(), int64 = arrow::int64(), uint64 = arrow::uint64(), float32 = arrow::float32(), float64 = arrow::float64() ) ints <- c(NA, 0:10) for (nm in names(arrow_int_types)) { expect_identical( convert_array( as_nanoarrow_array(ints, schema = arrow_int_types[[!!nm]]), integer() ), ints ) } ints_no_na <- 0:10 for (nm in names(arrow_int_types)) { expect_identical( convert_array( as_nanoarrow_array(ints_no_na, schema = arrow_int_types[[!!nm]]), integer() ), ints_no_na ) } # Boolean array to integer expect_identical( convert_array( as_nanoarrow_array(c(NA, TRUE, FALSE), schema = arrow::boolean()), integer() ), c(NA, 1L, 0L) ) expect_identical( convert_array( as_nanoarrow_array(c(TRUE, FALSE), schema = arrow::boolean()), integer() ), c(1L, 0L) ) }) test_that("convert to vector works for null -> logical()", { array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 expect_identical( convert_array(array, integer()), rep(NA_integer_, 10) ) }) test_that("convert to vector works for extension -> integer()", { array <- nanoarrow_extension_array(c(0L, 1L, NA_integer_), "some_ext") expect_warning( expect_identical( convert_array(array, integer()), c(0L, 1L, NA_integer_) ), "Converting unknown extension" ) }) test_that("convert to vector warns for invalid integer()", { array <- as_nanoarrow_array(.Machine$integer.max + 1) expect_warning( expect_identical(convert_array(array, integer()), NA_integer_), class = "nanoarrow_warning_lossy_conversion" ) array <- as_nanoarrow_array(c(NA, .Machine$integer.max + 1)) expect_warning( expect_identical(convert_array(array, integer()), c(NA_integer_, NA_integer_)), class = "nanoarrow_warning_lossy_conversion" ) }) test_that("convert to vector errors for bad array to integer()", { expect_error( convert_array(as_nanoarrow_array(letters), integer()), "Can't convert array to R vector of type integer" ) }) test_that("convert to vector works for valid double()", { skip_if_not_installed("arrow") arrow_numeric_types <- list( int8 = arrow::int8(), uint8 = arrow::uint8(), int16 = arrow::int16(), uint16 = arrow::uint16(), int32 = arrow::int32(), uint32 = arrow::uint32(), int64 = arrow::int64(), uint64 = arrow::uint64(), float32 = arrow::float32(), float64 = arrow::float64() ) vals <- as.double(c(NA, 0:10)) for (nm in names(arrow_numeric_types)) { expect_identical( convert_array( as_nanoarrow_array(vals, schema = arrow_numeric_types[[!!nm]]), double() ), vals ) } vals_no_na <- as.double(0:10) for (nm in names(arrow_numeric_types)) { expect_identical( convert_array( as_nanoarrow_array(vals_no_na, schema = arrow_numeric_types[[!!nm]]), double() ), vals_no_na ) } # Boolean array to double expect_identical( convert_array( as_nanoarrow_array(c(NA, TRUE, FALSE), schema = arrow::boolean()), double() ), as.double(c(NA, 1L, 0L)) ) expect_identical( convert_array( as_nanoarrow_array(c(TRUE, FALSE), schema = arrow::boolean()), double() ), as.double(c(1L, 0L)) ) }) test_that("convert to vector works for decimal128 -> double()", { skip_if_not_installed("arrow") array <- as_nanoarrow_array(arrow::Array$create(1:10)$cast(arrow::decimal128(20, 10))) # Check via S3 dispatch expect_equal( convert_array(array, double()), as.double(1:10) ) # ...and via C -> S3 dispatch expect_equal( convert_array.default(array, double()), as.double(1:10) ) }) test_that("convert to vector works for null -> double()", { array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 expect_identical( convert_array(array, double()), rep(NA_real_, 10) ) }) test_that("convert to vector works for extension -> double()", { array <- nanoarrow_extension_array(c(0, 1, NA_real_), "some_ext") expect_warning( expect_identical( convert_array(array, double()), c(0, 1, NA_real_) ), "Converting unknown extension" ) }) test_that("convert to vector works for dictionary -> double()", { array <- as_nanoarrow_array(c(0L, 1L, 2L, 1L, 0L)) array$dictionary <- as_nanoarrow_array(c(123, 0, NA_real_)) expect_identical( convert_array(array, double()), c(123, 0, NA_real_, 0, 123) ) }) test_that("convert to vector warns for possibly invalid double()", { array <- as_nanoarrow_array(2^54, schema = na_int64()) expect_warning( convert_array(array, double()), class = "nanoarrow_warning_lossy_conversion" ) }) test_that("convert to vector errors for bad array to double()", { expect_error( convert_array(as_nanoarrow_array(letters), double()), "Can't convert array to R vector of type numeric" ) }) test_that("convert to vector works for valid integer64()", { skip_if_not_installed("bit64") skip_if_not_installed("arrow") arrow_numeric_types <- list( int8 = arrow::int8(), uint8 = arrow::uint8(), int16 = arrow::int16(), uint16 = arrow::uint16(), int32 = arrow::int32(), uint32 = arrow::uint32(), int64 = arrow::int64(), uint64 = arrow::uint64(), float32 = arrow::float32(), float64 = arrow::float64() ) vals <- bit64::as.integer64(c(NA, 0:10)) for (nm in names(arrow_numeric_types)) { expect_identical( convert_array( as_nanoarrow_array(vals, schema = arrow_numeric_types[[!!nm]]), bit64::integer64() ), vals ) } vals_no_na <- bit64::as.integer64(0:10) for (nm in names(arrow_numeric_types)) { expect_identical( convert_array( as_nanoarrow_array(vals_no_na, schema = arrow_numeric_types[[!!nm]]), bit64::integer64() ), vals_no_na ) } # Boolean array to double expect_identical( convert_array( as_nanoarrow_array(c(NA, TRUE, FALSE), schema = arrow::boolean()), bit64::integer64() ), bit64::as.integer64(c(NA, 1L, 0L)) ) expect_identical( convert_array( as_nanoarrow_array(c(TRUE, FALSE), schema = arrow::boolean()), bit64::integer64() ), bit64::as.integer64(c(1L, 0L)) ) }) test_that("convert to vector works for null -> integer64()", { skip_if_not_installed("bit64") array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 expect_identical( convert_array(array, bit64::integer64()), rep(bit64::NA_integer64_, 10) ) }) test_that("convert to vector works for extension -> integer64()", { skip_if_not_installed("bit64") vec <- bit64::as.integer64(c(0, 1, NA)) array <- nanoarrow_extension_array(vec, "some_ext") expect_warning( expect_identical( convert_array(array, bit64::integer64()), vec ), "Converting unknown extension" ) }) test_that("convert to vector errors for bad array to integer64()", { skip_if_not_installed("bit64") expect_error( convert_array(as_nanoarrow_array(letters), bit64::integer64()), "Can't convert array to R vector of type integer64" ) }) test_that("convert to vector works for character()", { array <- as_nanoarrow_array(letters) expect_identical( convert_array(array, character()), letters ) # make sure we get altrep here expect_true(is_nanoarrow_altrep(convert_array(array, character()))) # check an array that we can't convert expect_error( convert_array(as_nanoarrow_array(1:5), character()), "Can't convert array to R vector of type character" ) }) test_that("convert to vector works for null -> character()", { array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 all_nulls <- convert_array(array, character()) nanoarrow_altrep_force_materialize(all_nulls) expect_identical( all_nulls, rep(NA_character_, 10) ) }) test_that("convert to vector works for extension -> character()", { array <- nanoarrow_extension_array(c("a", "b", NA_character_), "some_ext") expect_warning( expect_identical( convert_array(array, character()), c("a", "b", NA_character_) ), "Converting unknown extension" ) }) test_that("convert to vector works for dictionary -> character()", { array <- as_nanoarrow_array(factor(letters[5:1])) # Via S3 dispatch expect_identical( convert_array(array, character()), c("e", "d", "c", "b", "a") ) # Via C -> S3 dispatch expect_identical( convert_array.default(array, character()), c("e", "d", "c", "b", "a") ) }) test_that("convert to vector works for dictionary -> factor()", { array <- as_nanoarrow_array(factor(letters[5:1])) # With empty levels expect_identical( convert_array(array, factor()), factor(letters[5:1]) ) # With identical levels expect_identical( convert_array(array, factor(levels = c("a", "b", "c", "d", "e"))), factor(letters[5:1]) ) # With mismatched levels expect_identical( convert_array(array, factor(levels = c("b", "a", "c", "e", "d"))), factor(letters[5:1], levels = c("b", "a", "c", "e", "d")) ) expect_error( convert_array(array, factor(levels = letters[-4])), "some levels in data do not exist" ) }) test_that("batched convert to vector works for dictionary -> factor()", { # A slightly different path: convert_array.factor() called from C multiple # times with different dictionaries each time. array1 <- as_nanoarrow_array(factor(letters[1:5])) array2 <- as_nanoarrow_array(factor(letters[6:10])) array3 <- as_nanoarrow_array(factor(letters[11:15])) stream <- basic_array_stream(list(array1, array2, array3)) expect_identical( convert_array_stream(stream, factor(levels = letters)), factor(letters[1:15], levels = letters) ) }) test_that("batched convert to vector errors for dictionary -> factor()", { # We can't currently handle a preallocate + fill style conversion where the # result is partial_factor(). array1 <- as_nanoarrow_array(factor(letters[1:5])) array2 <- as_nanoarrow_array(factor(letters[6:10])) array3 <- as_nanoarrow_array(factor(letters[11:15])) stream <- basic_array_stream(list(array1, array2, array3)) expect_error( convert_array_stream(stream, factor()), "Can't allocate ptype of class 'factor'" ) }) test_that("convert to vector works for blob::blob()", { skip_if_not_installed("blob") array <- as_nanoarrow_array(list(as.raw(1:5)), schema = na_binary()) expect_identical( convert_array(array), blob::blob(as.raw(1:5)) ) expect_identical( convert_array(array, blob::blob()), blob::blob(as.raw(1:5)) ) }) test_that("convert to vector works for null -> blob::blob()", { array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 expect_identical( convert_array(array, blob::blob()), blob::new_blob(rep(list(NULL), 10)) ) }) test_that("convert to vector works for list -> vctrs::list_of", { skip_if_not_installed("arrow") array_list <- as_nanoarrow_array( arrow::Array$create( list(1:5, 6:10, NULL), type = arrow::list_of(arrow::int32()) ) ) # Default conversion expect_identical( convert_array(array_list), vctrs::list_of(1:5, 6:10, NULL, .ptype = integer()) ) # With explicit ptype expect_identical( convert_array(array_list, vctrs::list_of(.ptype = double())), vctrs::list_of(as.double(1:5), as.double(6:10), NULL, .ptype = double()) ) # With bad ptype expect_error( convert_array(array_list, vctrs::list_of(.ptype = character())), "Can't convert `item`" ) # With malformed ptype ptype <- vctrs::list_of(.ptype = character()) attr(ptype, "ptype") <- NULL expect_error( convert_array(array_list, ptype), "Expected attribute 'ptype'" ) }) test_that("convert to vector works for large_list -> vctrs::list_of", { skip_if_not_installed("arrow") array_list <- as_nanoarrow_array( arrow::Array$create( list(1:5, 6:10, NULL), type = arrow::large_list_of(arrow::int32()) ) ) # Default conversion expect_identical( convert_array(array_list), vctrs::list_of(1:5, 6:10, NULL, .ptype = integer()) ) # With explicit ptype expect_identical( convert_array(array_list, vctrs::list_of(.ptype = double())), vctrs::list_of(as.double(1:5), as.double(6:10), NULL, .ptype = double()) ) # With bad ptype expect_error( convert_array(array_list, vctrs::list_of(.ptype = character())), "Can't convert `item`" ) }) test_that("convert to vector works for fixed_size_list -> vctrs::list_of", { skip_if_not_installed("arrow") array_list <- as_nanoarrow_array( arrow::Array$create( list(1:5, 6:10, NULL), type = arrow::fixed_size_list_of(arrow::int32(), 5) ) ) # Default conversion expect_identical( convert_array(array_list), vctrs::list_of(1:5, 6:10, NULL, .ptype = integer()) ) # With explicit ptype expect_identical( convert_array(array_list, vctrs::list_of(.ptype = double())), vctrs::list_of(as.double(1:5), as.double(6:10), NULL, .ptype = double()) ) # With bad ptype expect_error( convert_array(array_list, vctrs::list_of(.ptype = character())), "Can't convert `item`" ) }) test_that("convert to vector works for null -> vctrs::list_of()", { array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 expect_identical( convert_array(array, vctrs::list_of(.ptype = integer())), vctrs::new_list_of(rep(list(NULL), 10), ptype = integer()) ) }) test_that("convert to vector works for Date", { array_date <- as_nanoarrow_array(as.Date(c(NA, "2000-01-01"))) expect_identical( convert_array(array_date), as.Date(c(NA, "2000-01-01")) ) array_date <- as_nanoarrow_array( as.Date(c(NA, "2000-01-01")), schema = na_date64() ) expect_identical( convert_array(array_date), as.POSIXct(c(NA, "2000-01-01"), tz = "UTC") ) }) test_that("convert to vector works for null -> Date", { array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 expect_identical( convert_array(array, as.Date(character())), as.Date(rep(NA_character_, 10)) ) }) test_that("convert to vector works for hms", { array_time <- as_nanoarrow_array(hms::parse_hm("12:34")) expect_identical( convert_array(array_time), hms::parse_hm("12:34") ) }) test_that("convert to vector works for null -> hms", { array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 expect_identical( convert_array(array, hms::hms()), hms::parse_hms(rep(NA_character_, 10)) ) }) test_that("convert to vector works for POSIXct", { array_timestamp <- as_nanoarrow_array( as.POSIXct("2000-01-01 12:33", tz = "America/Halifax") ) expect_identical( convert_array(array_timestamp), as.POSIXct("2000-01-01 12:33", tz = "America/Halifax") ) }) test_that("convert to vector works for null -> POSIXct", { array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 expect_identical( convert_array(array, as.POSIXct(character(), tz = "America/Halifax")), as.POSIXct(rep(NA_character_, 10), tz = "America/Halifax") ) }) test_that("convert to vector works for difftime", { x <- as.difftime(123, units = "secs") array_duration <- as_nanoarrow_array(x) # default expect_identical(convert_array(array_duration), x) # explicit expect_identical(convert_array(array_duration, x), x) # explicit with other difftime units units(x) <- "mins" expect_identical(convert_array(array_duration, x), x) units(x) <- "hours" expect_identical(convert_array(array_duration, x), x) units(x) <- "days" expect_identical(convert_array(array_duration, x), x) units(x) <- "weeks" expect_equal(convert_array(array_duration, x), x) # with all Arrow units x <- as.difftime(123, units = "secs") array_duration <- as_nanoarrow_array(x, na_duration("s")) expect_identical(convert_array(array_duration), x) array_duration <- as_nanoarrow_array(x, na_duration("ms")) expect_identical(convert_array(array_duration), x) array_duration <- as_nanoarrow_array(x, na_duration("us")) expect_identical(convert_array(array_duration), x) array_duration <- as_nanoarrow_array(x, na_duration("ns")) expect_equal(convert_array(array_duration), x) # bad ptype values attr(x, "units") <- NULL expect_error( convert_array(array_duration, x), "Expected difftime 'units' attribute of type" ) attr(x, "units") <- character() expect_error( convert_array(array_duration, x), "Expected difftime 'units' attribute of type" ) attr(x, "units") <- integer(1) expect_error( convert_array(array_duration, x), "Expected difftime 'units' attribute of type" ) attr(x, "units") <- "gazornenplat" expect_error( convert_array(array_duration, x), "Unexpected value for difftime 'units' attribute" ) attr(x, "units") <- NA_character_ expect_error( convert_array(array_duration, x), "Unexpected value for difftime 'units' attribute" ) }) test_that("convert to vector works for null -> difftime", { array <- nanoarrow_array_init(na_na()) array$length <- 10 array$null_count <- 10 expect_identical( convert_array(array, as.difftime(numeric(), units = "secs")), as.difftime(rep(NA_real_, 10), units = "secs") ) }) test_that("convert to vector works for data frames nested inside lists", { skip_if_not_installed("arrow") df_in_list <- vctrs::list_of( data.frame(x = 1:5), data.frame(x = 6:10), data.frame(x = 11:15) ) nested_array <- as_nanoarrow_array(df_in_list) expect_identical( convert_array(nested_array), df_in_list ) }) test_that("convert to vector works for lists nested in data frames", { skip_if_not_installed("arrow") df_in_list_in_df <- data.frame( x = vctrs::list_of( data.frame(x = 1:5), data.frame(x = 6:10), data.frame(x = 11:15) ) ) nested_array <- as_nanoarrow_array(df_in_list_in_df) expect_identical( convert_array(nested_array), df_in_list_in_df ) })