thisisnic commented on code in PR #33614:
URL: https://github.com/apache/arrow/pull/33614#discussion_r1072513809
##########
r/tests/testthat/test-dataset-csv.R:
##########
@@ -476,3 +476,87 @@ test_that("CSV reading/parsing/convert options can be
passed in as lists", {
expect_equal(ds1, ds2)
})
+
+test_that("open_delim_dataset params passed through to open_dataset", {
+ ds <- open_delim_dataset(csv_dir, delim = ",", partitioning = "part")
+ expect_r6_class(ds$format, "CsvFileFormat")
+ expect_r6_class(ds$filesystem, "LocalFileSystem")
+ expect_identical(names(ds), c(names(df1), "part"))
+ expect_identical(dim(ds), c(20L, 7L))
+
+ # quote
+ df <- data.frame(a = c(1, 2), b = c("'abc'", "'def'"))
+ dst_dir <- make_temp_dir()
+ dst_file <- file.path(dst_dir, "data.csv")
+ write.table(df, sep = ",", dst_file, row.names = FALSE, quote = FALSE)
+
+ ds_quote <- open_csv_dataset(dst_dir, quote = "'") %>% collect()
+ expect_equal(ds_quote$b, c("abc", "def"))
+
+ # na
+ ds <- open_csv_dataset(csv_dir, partitioning = "part", na = c("", "NA",
"FALSE")) %>% collect()
+ expect_identical(ds$lgl, c(
+ TRUE, NA, NA, TRUE, NA, TRUE, NA, NA, TRUE, NA, TRUE, NA, NA,
+ TRUE, NA, TRUE, NA, NA, TRUE, NA
+ ))
+
+ # col_names and skip
+ ds <- open_csv_dataset(
+ csv_dir,
+ partitioning = "part",
+ col_names = paste0("col_", 1:6),
+ skip = 1
+ ) %>% collect()
+
+ expect_named(ds, c("col_1", "col_2", "col_3", "col_4", "col_5", "col_6",
"part"))
+ expect_equal(nrow(ds), 20)
+
+ # col_types
+ df <- data.frame(a = c(1, NA, 2), b = c("'abc'", NA, "'def'"))
+ dst_dir <- make_temp_dir()
+ dst_file <- file.path(dst_dir, "data.csv")
+ write.table(df, sep = ",", dst_file, row.names = FALSE, quote = FALSE)
+
+ data_schema <- schema(a = string(), b = string())
+ ds_strings <- open_csv_dataset(dst_dir, col_types = data_schema)
+ expect_equal(ds_strings$schema, schema(a = string(), b = string()))
+
+ # skip_empty_rows
+ tf <- tempfile()
+ writeLines('"x"\n"y"\nNA\nNA\n"NULL"\n\n\n', tf)
Review Comment:
When it's one column I agree, though it's trickier when it's multiple
columns. In order to make it more readable/obvious, I've swapped out
`write.table` for `write.csv` as we use that more in this file, and moved
things around so that the data frame is defined next to where it's written.
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