# Basic properties -------------------------------------------------------- test_that("mutating joins preserve row and column order of x", { df1 <- data.frame(a = 1:3) df2 <- data.frame(b = 1, c = 2, a = 4:1) out <- duckplyr_inner_join(df1, df2, by = "a") expect_named(out, c("a", "b", "c")) expect_equal(out$a, 1:3) out <- duckplyr_left_join(df1, df2, by = "a") expect_named(out, c("a", "b", "c")) expect_equal(out$a, 1:3) out <- duckplyr_right_join(df1, df2, by = "a") expect_named(out, c("a", "b", "c")) expect_equal(out$a, 1:4) out <- duckplyr_full_join(df1, df2, by = "a") expect_named(out, c("a", "b", "c")) expect_equal(out$a, 1:4) }) test_that("even when column names change", { df1 <- data.frame(x = c(1, 1, 2, 3), z = 1:4, a = 1) df2 <- data.frame(z = 1:3, b = 1, x = c(1, 2, 4)) out <- duckplyr_inner_join(df1, df2, by = "x") expect_named(out, c("x", "z.x", "a", "z.y", "b")) }) test_that("filtering joins preserve row and column order of x (#2964)", { df1 <- data.frame(a = 4:1, b = 1) df2 <- data.frame(b = 1, c = 2, a = 2:3) out <- duckplyr_semi_join(df1, df2, by = "a") expect_named(out, c("a", "b")) expect_equal(out$a, 3:2) out <- duckplyr_anti_join(df1, df2, by = "a") expect_named(out, c("a", "b")) expect_equal(out$a, c(4L, 1L)) }) test_that("keys are coerced to symmetric type", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") foo <- tibble(id = 1:2, var1 = "foo") bar <- tibble(id = as.numeric(1:2), var2 = "bar") expect_type(duckplyr_inner_join(foo, bar, by = "id")$id, "double") expect_type(duckplyr_inner_join(bar, foo, by = "id")$id, "double") foo <- tibble(id = factor(c("a", "b")), var1 = "foo") bar <- tibble(id = c("a", "b"), var2 = "bar") expect_type(duckplyr_inner_join(foo, bar, by = "id")$id, "character") expect_type(duckplyr_inner_join(bar, foo, by = "id")$id, "character") }) test_that("factor keys are coerced to the union factor type", { df1 <- tibble(x = 1, y = factor("a")) df2 <- tibble(x = 2, y = factor("b")) out <- duckplyr_full_join(df1, df2, by = c("x", "y")) expect_equal(out$y, factor(c("a", "b"))) }) test_that("keys of non-equi conditions are not coerced if `keep = NULL`", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") foo <- tibble(id = factor(c("a", "b")), col1 = c(1, 2), var1 = "foo") bar <- tibble(id = c("a", "b"), col2 = c(1L, 2L), var2 = "bar") out <- duckplyr_inner_join(foo, bar, by = join_by(id, col1 >= col2)) expect_type(out$id, "character") expect_type(out$col1, "double") expect_type(out$col2, "integer") out <- duckplyr_inner_join(bar, foo, by = join_by(id, col2 <= col1)) expect_type(out$id, "character") expect_type(out$col1, "double") expect_type(out$col2, "integer") }) test_that("when keep = TRUE, duckplyr_left_join() preserves both sets of keys", { # when keys have different names df1 <- tibble(a = c(2, 3), b = c(1, 2)) df2 <- tibble(x = c(3, 4), y = c(3, 4)) out <- duckplyr_left_join(df1, df2, by = c("a" = "x"), keep = TRUE) expect_equal(out$a, c(2, 3)) expect_equal(out$x, c(NA, 3)) # when keys have same name df1 <- tibble(a = c(2, 3), b = c(1, 2)) df2 <- tibble(a = c(3, 4), y = c(3, 4)) out <- duckplyr_left_join(df1, df2, by = c("a"), keep = TRUE) expect_equal(out$a.x, c(2, 3)) expect_equal(out$a.y, c(NA, 3)) }) test_that("when keep = TRUE, duckplyr_right_join() preserves both sets of keys", { # when keys have different names df1 <- tibble(a = c(2, 3), b = c(1, 2)) df2 <- tibble(x = c(3, 4), y = c(3, 4)) out <- duckplyr_right_join(df1, df2, by = c("a" = "x"), keep = TRUE) expect_equal(out$a, c(3, NA)) expect_equal(out$x, c(3, 4)) # when keys have same name df1 <- tibble(a = c(2, 3), b = c(1, 2)) df2 <- tibble(a = c(3, 4), y = c(3, 4)) out <- duckplyr_right_join(df1, df2, by = c("a"), keep = TRUE) expect_equal(out$a.x, c(3, NA)) expect_equal(out$a.y, c(3, 4)) }) test_that("when keep = TRUE, duckplyr_full_join() preserves both sets of keys", { # when keys have different names df1 <- tibble(a = c(2, 3), b = c(1, 2)) df2 <- tibble(x = c(3, 4), y = c(3, 4)) out <- duckplyr_full_join(df1, df2, by = c("a" = "x"), keep = TRUE) expect_equal(out$a, c(2, 3, NA)) expect_equal(out$x, c(NA, 3, 4)) # when keys have same name df1 <- tibble(a = c(2, 3), b = c(1, 2)) df2 <- tibble(a = c(3, 4), y = c(3, 4)) out <- duckplyr_full_join(df1, df2, by = c("a"), keep = TRUE) expect_equal(out$a.x, c(2, 3, NA)) expect_equal(out$a.y, c(NA, 3, 4)) }) test_that("when keep = TRUE, duckplyr_inner_join() preserves both sets of keys (#5581)", { # when keys have different names df1 <- tibble(a = c(2, 3), b = c(1, 2)) df2 <- tibble(x = c(3, 4), y = c(3, 4)) out <- duckplyr_inner_join(df1, df2, by = c("a" = "x"), keep = TRUE) expect_equal(out$a, c(3)) expect_equal(out$x, c(3)) # when keys have same name df1 <- tibble(a = c(2, 3), b = c(1, 2)) df2 <- tibble(a = c(3, 4), y = c(3, 4)) out <- duckplyr_inner_join(df1, df2, by = c("a"), keep = TRUE) expect_equal(out$a.x, c(3)) expect_equal(out$a.y, c(3)) }) test_that("can't use `keep = FALSE` with non-equi conditions (#6499)", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(xl = c(1, 3), xu = c(4, 7)) df2 <- tibble(yl = c(2, 5, 8), yu = c(6, 8, 9)) expect_snapshot(error = TRUE, { duckplyr_left_join(df1, df2, join_by(overlaps(xl, xu, yl, yu)), keep = FALSE) }) # Would never make sense here. # Based on how the binary conditions are generated we'd merge: # - `yu` into `xl` # - `yl` into `xu` # Which results in `xl` and `xu` columns that don't maintain `xl <= xu`. expect_snapshot(error = TRUE, { duckplyr_full_join(df1, df2, join_by(overlaps(xl, xu, yl, yu)), keep = FALSE) }) }) test_that("joins matches NAs by default (#892, #2033)", { df1 <- tibble(x = c(NA_character_, 1)) df2 <- tibble(x = c(NA_character_, 2)) expect_equal(nrow(duckplyr_inner_join(df1, df2, by = "x")), 1) expect_equal(nrow(duckplyr_semi_join(df1, df2, by = "x")), 1) }) test_that("joins don't match NA when na_matches = 'never' (#2033)", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(a = c(1, NA)) df2 <- tibble(a = c(1, NA), b = 1:2) out <- duckplyr_left_join(df1, df2, by = "a", na_matches = "never") expect_equal(out, tibble(a = c(1, NA), b = c(1, NA))) out <- duckplyr_inner_join(df1, df2, by = "a", na_matches = "never") expect_equal(out, tibble(a = 1, b = 1)) out <- duckplyr_semi_join(df1, df2, by = "a", na_matches = "never") expect_equal(out, tibble(a = 1)) out <- duckplyr_anti_join(df1, df2, by = "a", na_matches = "never") expect_equal(out, tibble(a = NA_integer_)) out <- duckplyr_nest_join(df1, df2, by = "a", na_matches = "never") expect <- tibble(a = c(1, NA), df2 = list(tibble(b = 1L), tibble(b = integer()))) expect_equal(out, expect) dat1 <- tibble( name = c("a", "c"), var1 = c(1, 2) ) dat3 <- tibble( name = c("a", NA_character_), var3 = c(5, 6) ) expect_equal( duckplyr_full_join(dat1, dat3, by = "name", na_matches = "never"), tibble(name = c("a", "c", NA), var1 = c(1, 2, NA), var3 = c(5, NA, 6)) ) }) test_that("`duckplyr_left_join(by = join_by(closest(...)))` works as expected", { df1 <- tibble(x = 1:5) df2 <- tibble(y = c(1, 2, 4)) out <- duckplyr_left_join(df1, df2, by = join_by(closest(x <= y))) expect_identical(out$x, 1:5) expect_identical(out$y, c(1, 2, 4, 4, NA)) out <- duckplyr_left_join(df1, df2, by = join_by(closest(x < y))) expect_identical(out$x, 1:5) expect_identical(out$y, c(2, 4, 4, NA, NA)) out <- duckplyr_left_join(df1, df2, by = join_by(closest(x >= y))) expect_identical(out$x, 1:5) expect_identical(out$y, c(1, 2, 2, 4, 4)) out <- duckplyr_left_join(df1, df2, by = join_by(closest(x > y))) expect_identical(out$x, 1:5) expect_identical(out$y, c(NA, 1, 2, 2, 4)) }) test_that("`duckplyr_full_join(by = join_by(closest(...)))` works as expected", { df1 <- tibble(x = 1:5) df2 <- tibble(y = c(1, 2, 4)) out <- duckplyr_full_join(df1, df2, by = join_by(closest(x <= y))) expect_identical(out$x, 1:5) expect_identical(out$y, c(1, 2, 4, 4, NA)) out <- duckplyr_full_join(df1, df2, by = join_by(closest(x < y))) expect_identical(out$x, c(1:5, NA)) expect_identical(out$y, c(2, 4, 4, NA, NA, 1)) out <- duckplyr_full_join(df1, df2, by = join_by(closest(x >= y))) expect_identical(out$x, 1:5) expect_identical(out$y, c(1, 2, 2, 4, 4)) out <- duckplyr_full_join(df1, df2, by = join_by(closest(x > y))) expect_identical(out$x, 1:5) expect_identical(out$y, c(NA, 1, 2, 2, 4)) }) test_that("`duckplyr_right_join(by = join_by(closest(...)))` works as expected", { df1 <- tibble(x = 1:5) df2 <- tibble(y = c(1, 2, 4)) out <- duckplyr_right_join(df1, df2, by = join_by(closest(x <= y))) expect_identical(out$x, 1:4) expect_identical(out$y, c(1, 2, 4, 4)) out <- duckplyr_right_join(df1, df2, by = join_by(closest(x < y))) expect_identical(out$x, c(1:3, NA)) expect_identical(out$y, c(2, 4, 4, 1)) out <- duckplyr_right_join(df1, df2, by = join_by(closest(x >= y))) expect_identical(out$x, 1:5) expect_identical(out$y, c(1, 2, 2, 4, 4)) out <- duckplyr_right_join(df1, df2, by = join_by(closest(x > y))) expect_identical(out$x, 2:5) expect_identical(out$y, c(1, 2, 2, 4)) }) test_that("`duckplyr_inner_join(by = join_by(closest(...)))` works as expected", { df1 <- tibble(x = 1:5) df2 <- tibble(y = c(1, 2, 4)) out <- duckplyr_inner_join(df1, df2, by = join_by(closest(x <= y))) expect_identical(out$x, 1:4) expect_identical(out$y, c(1, 2, 4, 4)) out <- duckplyr_inner_join(df1, df2, by = join_by(closest(x < y))) expect_identical(out$x, 1:3) expect_identical(out$y, c(2, 4, 4)) out <- duckplyr_inner_join(df1, df2, by = join_by(closest(x >= y))) expect_identical(out$x, 1:5) expect_identical(out$y, c(1, 2, 2, 4, 4)) out <- duckplyr_inner_join(df1, df2, by = join_by(closest(x > y))) expect_identical(out$x, 2:5) expect_identical(out$y, c(1, 2, 2, 4)) }) test_that("joins using `between(bounds =)` work as expected (#6488)", { df1 <- tibble(x = 1:5) df2 <- tibble(lower = 2, upper = 4) out <- duckplyr_full_join(df1, df2, by = join_by(between(x, lower, upper, bounds = "[]"))) expect_identical(out$lower, c(NA, 2, 2, 2, NA)) expect_identical(out$upper, c(NA, 4, 4, 4, NA)) out <- duckplyr_full_join(df1, df2, by = join_by(between(x, lower, upper, bounds = "[)"))) expect_identical(out$lower, c(NA, 2, 2, NA, NA)) expect_identical(out$upper, c(NA, 4, 4, NA, NA)) out <- duckplyr_full_join(df1, df2, by = join_by(between(x, lower, upper, bounds = "(]"))) expect_identical(out$lower, c(NA, NA, 2, 2, NA)) expect_identical(out$upper, c(NA, NA, 4, 4, NA)) out <- duckplyr_full_join(df1, df2, by = join_by(between(x, lower, upper, bounds = "()"))) expect_identical(out$lower, c(NA, NA, 2, NA, NA)) expect_identical(out$upper, c(NA, NA, 4, NA, NA)) }) test_that("joins using `overlaps(bounds =)` work as expected (#6488)", { df1 <- tibble(x_lower = c(1, 1, 3, 4), x_upper = c(2, 3, 4, 5)) df2 <- tibble(y_lower = 2, y_upper = 4) expect_closed <- vec_cbind(df1, vec_c(df2, df2, df2, df2)) out <- duckplyr_full_join(df1, df2, by = join_by(overlaps(x_lower, x_upper, y_lower, y_upper, bounds = "[]"))) expect_identical(out, expect_closed) # `[)`, `(]`, and `()` all generate the same binary conditions but are useful # for consistency with `between(bounds =)` expect_open <- vec_cbind(df1, vec_c(NA, df2, df2, NA)) out <- duckplyr_full_join(df1, df2, by = join_by(overlaps(x_lower, x_upper, y_lower, y_upper, bounds = "[)"))) expect_identical(out, expect_open) out <- duckplyr_full_join(df1, df2, by = join_by(overlaps(x_lower, x_upper, y_lower, y_upper, bounds = "(]"))) expect_identical(out, expect_open) out <- duckplyr_full_join(df1, df2, by = join_by(overlaps(x_lower, x_upper, y_lower, y_upper, bounds = "()"))) expect_identical(out, expect_open) }) test_that("join_mutate() validates arguments", { df <- tibble(x = 1) # Mutating joins expect_snapshot(error = TRUE, { join_mutate(df, df, by = 1, type = "left") join_mutate(df, df, by = "x", type = "left", suffix = 1) join_mutate(df, df, by = "x", type = "left", na_matches = "foo") join_mutate(df, df, by = "x", type = "left", keep = 1) }) }) test_that("join_filter() validates arguments", { df <- tibble(x = 1) # Filtering joins expect_snapshot(error = TRUE, { join_filter(df, df, by = 1, type = "semi") join_filter(df, df, by = "x", type = "semi", na_matches = "foo") }) }) test_that("mutating joins trigger many-to-many warning", { skip("TODO duckdb") df <- tibble(x = c(1, 1)) expect_snapshot(out <- duckplyr_left_join(df, df, join_by(x))) }) test_that("mutating joins don't trigger many-to-many warning when called indirectly", { skip("TODO duckdb") df <- tibble(x = c(1, 1)) fn <- function(df1, df2, relationship = NULL) { duckplyr_left_join(df1, df2, join_by(x), relationship = relationship) } # Directly calling `duckplyr_left_join()` from a function you control results in a warning expect_warning(fn(df, df), class = "dplyr_warning_join_relationship_many_to_many") # Now mimic calling an "rlang function" which you don't control that calls `duckplyr_left_join()` fn_env(fn) <- ns_env("rlang") # Indirectly calling `duckplyr_left_join()` through a function you don't control # doesn't warn expect_no_warning(fn(df, df), class = "dplyr_warning_join_relationship_many_to_many") }) test_that("mutating joins compute common columns", { df1 <- tibble(x = c(1, 2), y = c(2, 3)) df2 <- tibble(x = c(1, 3), z = c(2, 3)) expect_snapshot(out <- duckplyr_left_join(df1, df2)) }) test_that("filtering joins compute common columns", { df1 <- tibble(x = c(1, 2), y = c(2, 3)) df2 <- tibble(x = c(1, 3), z = c(2, 3)) expect_snapshot(out <- duckplyr_semi_join(df1, df2)) }) test_that("mutating joins finalize unspecified columns (#6804)", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(x = NA) df2 <- tibble(x = NA) expect_identical( duckplyr_inner_join(df1, df2, by = join_by(x)), tibble(x = NA) ) expect_identical( duckplyr_inner_join(df1, df2, by = join_by(x), na_matches = "never"), tibble(x = logical()) ) # Pre-existing `unspecified()` vectors get finalized, because they are # considered internal types and we took a "common type" between the keys df1 <- tibble(x = unspecified()) df2 <- tibble(x = unspecified()) expect_identical( duckplyr_inner_join(df1, df2, by = join_by(x)), tibble(x = logical()) ) }) test_that("filtering joins finalize unspecified columns (#6804)", { df1 <- tibble(x = NA) df2 <- tibble(x = NA) expect_identical( duckplyr_semi_join(df1, df2, by = join_by(x)), tibble(x = NA) ) expect_identical( duckplyr_semi_join(df1, df2, by = join_by(x), na_matches = "never"), tibble(x = logical()) ) # Pre-existing `unspecified()` vectors aren't finalized, # because we don't take the common type of the keys. # We retain the exact type of `x`. df1 <- tibble(x = unspecified()) df2 <- tibble(x = NA) expect_identical( duckplyr_semi_join(df1, df2, by = join_by(x)), tibble(x = unspecified()) ) }) test_that("mutating joins reference original column in `y` when there are type errors (#6465)", { x <- tibble(a = 1) y <- tibble(b = "1") expect_snapshot({ (expect_error(duckplyr_left_join(x, y, by = join_by(a == b)))) }) }) test_that("filtering joins reference original column in `y` when there are type errors (#6465)", { x <- tibble(a = 1) y <- tibble(b = "1") expect_snapshot({ (expect_error(duckplyr_semi_join(x, y, by = join_by(a == b)))) }) }) test_that("error if passed additional arguments", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- data.frame(a = 1:3) df2 <- data.frame(a = 1) expect_snapshot(error = TRUE, { duckplyr_inner_join(df1, df2, on = "a") duckplyr_left_join(df1, df2, on = "a") duckplyr_right_join(df1, df2, on = "a") duckplyr_full_join(df1, df2, on = "a") duckplyr_nest_join(df1, df2, on = "a") duckplyr_anti_join(df1, df2, on = "a") duckplyr_semi_join(df1, df2, on = "a") }) }) # nest_join --------------------------------------------------------------- test_that("nest_join returns list of tibbles (#3570)",{ skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(x = c(1, 2), y = c(2, 3)) df2 <- tibble(x = c(1, 1), z = c(2, 3)) out <- duckplyr_nest_join(df1, df2, by = "x") expect_named(out, c("x", "y", "df2")) expect_type(out$df2, "list") expect_s3_class(out$df2[[1]], "tbl_df") }) test_that("nest_join respects types of y (#6295)",{ df1 <- tibble(x = c(1, 2), y = c(2, 3)) df2 <- duckplyr_rowwise(tibble(x = c(1, 1), z = c(2, 3))) out <- duckplyr_nest_join(df1, df2, by = "x") expect_s3_class(out$df2[[1]], "rowwise_df") }) test_that("nest_join preserves data frame attributes on `x` and `y` (#6295)", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- data.frame(x = c(1, 2), y = c(3, 4)) attr(df1, "foo") <- 1 df2 <- data.frame(x = c(1, 2), z = c(3, 4)) attr(df2, "foo") <- 2 out <- duckplyr_nest_join(df1, df2, by = "x") expect_identical(attr(out, "foo"), 1) expect_identical(attr(out$df2[[1]], "foo"), 2) }) test_that("nest_join computes common columns", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(x = c(1, 2), y = c(2, 3)) df2 <- tibble(x = c(1, 3), z = c(2, 3)) expect_snapshot(out <- duckplyr_nest_join(df1, df2)) }) test_that("nest_join finalizes unspecified columns (#6804)", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(x = NA) df2 <- tibble(x = NA) expect_identical( duckplyr_nest_join(df1, df2, by = join_by(x)), tibble(x = NA, df2 = list(tibble(.rows = 1L))) ) expect_identical( duckplyr_nest_join(df1, df2, by = join_by(x), keep = TRUE), tibble(x = NA, df2 = list(tibble(x = NA))) ) expect_identical( duckplyr_nest_join(df1, df2, by = join_by(x), na_matches = "never"), tibble(x = NA, df2 = list(tibble())) ) # Pre-existing `unspecified()` vectors get finalized, because they are # considered internal types and we took a "common type" between the keys df1 <- tibble(x = unspecified()) df2 <- tibble(x = unspecified()) expect_identical( duckplyr_nest_join(df1, df2, by = join_by(x)), tibble(x = logical(), df2 = list()) ) }) test_that("nest_join references original column in `y` when there are type errors (#6465)", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") x <- tibble(a = 1) y <- tibble(b = "1") expect_snapshot({ (expect_error(duckplyr_nest_join(x, y, by = join_by(a == b)))) }) }) test_that("nest_join handles multiple matches in x (#3642)", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(x = c(1, 1)) df2 <- tibble(x = 1, y = 1:2) out <- duckplyr_nest_join(df1, df2, by = "x") expect_equal(out$df2[[1]], out$df2[[2]]) }) test_that("nest_join forces `multiple = 'all'` internally (#6392)", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(x = 1) df2 <- tibble(x = 1, y = 1:2) expect_no_warning(out <- duckplyr_nest_join(df1, df2, by = "x")) expect_identical(nrow(out$df2[[1]]), 2L) }) test_that("y keys dropped by default for equi conditions", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(x = c(1, 2), y = c(2, 3)) df2 <- tibble(x = c(1, 3), z = c(2, 3)) out <- duckplyr_nest_join(df1, df2, by = "x") expect_named(out, c("x", "y", "df2")) expect_named(out$df2[[1]], "z") out <- duckplyr_nest_join(df1, df2, by = "x", keep = TRUE) expect_named(out$df2[[1]], c("x", "z")) }) test_that("y keys kept by default for non-equi conditions", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(x = c(1, 2), y = c(2, 3)) df2 <- tibble(x = c(1, 3), z = c(2, 3)) out <- duckplyr_nest_join(df1, df2, by = join_by(x >= x)) expect_named(out, c("x", "y", "df2")) expect_named(out$df2[[1]], c("x", "z")) }) test_that("validates inputs", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(x = c(1, 2), y = c(2, 3)) df2 <- tibble(x = c(1, 3), z = c(2, 3)) expect_snapshot(error = TRUE, { duckplyr_nest_join(df1, df2, by = 1) duckplyr_nest_join(df1, df2, keep = 1) duckplyr_nest_join(df1, df2, name = 1) duckplyr_nest_join(df1, df2, na_matches = 1) }) }) # output type --------------------------------------------------------------- test_that("joins x preserve type of x", { df1 <- data.frame(x = 1) df2 <- tibble(x = 2) expect_s3_class(duckplyr_inner_join(df1, df2, by = "x"), "data.frame", exact = TRUE) expect_s3_class(duckplyr_inner_join(df2, df1, by = "x"), "tbl_df") }) test_that("joins preserve groups", { gf1 <- tibble(a = 1:3) %>% duckplyr_group_by(a) gf2 <- tibble(a = rep(1:4, 2), b = 1) %>% duckplyr_group_by(b) i <- count_regroups(out <- duckplyr_inner_join(gf1, gf2, by = "a")) expect_equal(i, 1L) expect_equal(duckplyr_group_vars(out), "a") i <- count_regroups(out <- duckplyr_semi_join(gf1, gf2, by = "a")) expect_equal(i, 0L) expect_equal(duckplyr_group_vars(out), "a") # once for x + once for each row for y i <- count_regroups(out <- duckplyr_nest_join(gf1, gf2, by = "a")) expect_equal(i, 4L) expect_equal(duckplyr_group_vars(out), "a") expect_equal(duckplyr_group_vars(out$gf2[[1]]), "b") }) test_that("joins respect zero length groups", { df1 <- tibble(f = factor( c(1,1,2,2), levels = 1:3), x = c(1,2,1,4)) %>% duckplyr_group_by(f) df2 <- tibble(f = factor( c(2,2,3,3), levels = 1:3), y = c(1,2,3,4)) %>% duckplyr_group_by(f) expect_equal(duckplyr_group_size(duckplyr_left_join( df1, df2, by = "f", relationship = "many-to-many")), c(2,4)) expect_equal(duckplyr_group_size(duckplyr_right_join( df1, df2, by = "f", relationship = "many-to-many")), c(4,2)) expect_equal(duckplyr_group_size(duckplyr_full_join( df1, df2, by = "f", relationship = "many-to-many")), c(2,4,2)) expect_equal(duckplyr_group_size(duckplyr_anti_join( df1, df2, by = "f")), c(2)) expect_equal(duckplyr_group_size(duckplyr_inner_join( df1, df2, by = "f", relationship = "many-to-many")), c(4)) df1 <- tibble(f = factor( c(1,1,2,2), levels = 1:3), x = c(1,2,1,4)) %>% duckplyr_group_by(f, .drop = FALSE) df2 <- tibble(f = factor( c(2,2,3,3), levels = 1:3), y = c(1,2,3,4)) %>% duckplyr_group_by(f, .drop = FALSE) expect_equal(duckplyr_group_size(duckplyr_left_join( df1, df2, by = "f", relationship = "many-to-many")), c(2,4,0)) expect_equal(duckplyr_group_size(duckplyr_right_join( df1, df2, by = "f", relationship = "many-to-many")), c(0,4,2)) expect_equal(duckplyr_group_size(duckplyr_full_join( df1, df2, by = "f", relationship = "many-to-many")), c(2,4,2)) expect_equal(duckplyr_group_size(duckplyr_anti_join( df1, df2, by = "f")), c(2,0,0)) expect_equal(duckplyr_group_size(duckplyr_inner_join( df1, df2, by = "f", relationship = "many-to-many")), c(0,4,0)) }) test_that("group column names reflect renamed duplicate columns (#2330)", { df1 <- tibble(x = 1:5, y = 1:5) %>% duckplyr_group_by(x, y) df2 <- tibble(x = 1:5, y = 1:5) out <- duckplyr_inner_join(df1, df2, by = "x") expect_equal(duckplyr_group_vars(out), "x") # TODO: fix this issue: https://github.com/tidyverse/dplyr/issues/4917 # expect_equal(duckplyr_group_vars(out), c("x", "y.x")) }) test_that("rowwise group structure is updated after a join (#5227)", { df1 <- duckplyr_rowwise(tibble(x = 1:2)) df2 <- tibble(x = c(1:2, 2L)) x <- duckplyr_left_join(df1, df2, by = "x") expect_identical(group_rows(x), list_of(1L, 2L, 3L)) }) # deprecated ---------------------------------------------------------------- test_that("by = character() generates cross (#4206)", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") local_options(lifecycle_verbosity = "quiet") df1 <- tibble(x = 1:2) df2 <- tibble(y = 1:2) out <- duckplyr_left_join(df1, df2, by = character()) expect_equal(out$x, rep(1:2, each = 2)) expect_equal(out$y, rep(1:2, 2)) }) test_that("`by = character()` technically respects `unmatched`", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") local_options(lifecycle_verbosity = "quiet") df1 <- tibble() df2 <- tibble(x = 1) expect_snapshot(error = TRUE, { duckplyr_left_join(df1, df2, by = character(), unmatched = "error") }) }) test_that("`by = character()` technically respects `relationship`", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") local_options(lifecycle_verbosity = "quiet") df <- tibble(x = 1:2) expect_snapshot(error = TRUE, { duckplyr_left_join(df, df, by = character(), relationship = "many-to-one") }) }) test_that("`by = character()` for a cross join is deprecated (#6604)", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(x = 1:2) df2 <- tibble(y = 1:2) # Mutating join expect_snapshot({ out <- duckplyr_left_join(df1, df2, by = character()) }) # Filtering join expect_snapshot({ out <- duckplyr_semi_join(df1, df2, by = character()) }) # Nest join expect_snapshot({ out <- duckplyr_nest_join(df1, df2, by = character()) }) }) test_that("`by = named character()` for a cross join works", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") # Used by the sift package df1 <- tibble(x = 1:2) df2 <- tibble(y = 1:2) by <- set_names(character(), nm = character()) expect_snapshot({ out <- duckplyr_left_join(df1, df2, by = by) }) expect_identical( out, duckplyr_cross_join(df1, df2) ) }) test_that("`by = list(x = character(), y = character())` for a cross join is deprecated (#6604)", { skip_if(Sys.getenv("DUCKPLYR_FORCE") == "TRUE") df1 <- tibble(x = 1:2) df2 <- tibble(y = 1:2) expect_snapshot({ out <- duckplyr_left_join(df1, df2, by = list(x = character(), y = character())) }) })