tests/testthat/_snaps/rows.md

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

duckplyr_rows_insert() doesn't allow insertion of matched keys by default

Code
  (expect_error(duckplyr_rows_insert(x, y, by = "a")))
Output
  <error/rlang_error>
  Error in `rows_insert()`:
  ! `y` can't contain keys that already exist in `x`.
  i The following rows in `y` have keys that already exist in `x`: `c(1)`.
  i Use `conflict = "ignore"` if you want to ignore these `y` rows.

Code
  (expect_error(duckplyr_rows_insert(x, y, by = "a")))
Output
  <error/rlang_error>
  Error in `rows_insert()`:
  ! `y` can't contain keys that already exist in `x`.
  i The following rows in `y` have keys that already exist in `x`: `c(1, 2, 3)`.
  i Use `conflict = "ignore"` if you want to ignore these `y` rows.

duckplyr_rows_insert() casts keys to the type of x

Code
  (expect_error(duckplyr_rows_insert(x, y, "key")))
Output
  <error/vctrs_error_cast_lossy>
  Error in `rows_insert()`:
  ! Can't convert from `y$key` <double> to `x$key` <integer> due to loss of precision.
  * Locations: 1

duckplyr_rows_insert() casts values to the type of x

Code
  (expect_error(duckplyr_rows_insert(x, y, "key")))
Output
  <error/vctrs_error_cast_lossy>
  Error in `rows_insert()`:
  ! Can't convert from `y$value` <double> to `x$value` <integer> due to loss of precision.
  * Locations: 1

duckplyr_rows_insert() checks that x and y contain by (#6652)

Code
  (expect_error(duckplyr_rows_insert(x, y, by = "c")))
Output
  <error/rlang_error>
  Error in `rows_insert()`:
  ! All columns specified through `by` must exist in `x` and `y`.
  i The following columns are missing from `x`: `c`.

Code
  (expect_error(duckplyr_rows_insert(x, y, by = c("a", "b"))))
Output
  <error/rlang_error>
  Error in `rows_insert()`:
  ! All columns specified through `by` must exist in `x` and `y`.
  i The following columns are missing from `y`: `b`.

conflict is validated

Code
  (expect_error(duckplyr_rows_insert(x, y, by = "a", conflict = "foo")))
Output
  <error/rlang_error>
  Error in `rows_insert()`:
  ! `conflict` must be one of "error" or "ignore", not "foo".
Code
  (expect_error(duckplyr_rows_insert(x, y, by = "a", conflict = 1)))
Output
  <error/rlang_error>
  Error in `rows_insert()`:
  ! `conflict` must be a string or character vector.

duckplyr_rows_append() casts to the type of x

Code
  (expect_error(duckplyr_rows_append(x, y)))
Output
  <error/vctrs_error_cast_lossy>
  Error in `rows_append()`:
  ! Can't convert from `y$key` <double> to `x$key` <integer> due to loss of precision.
  * Locations: 1

duckplyr_rows_append() requires that y columns be a subset of x

Code
  (expect_error(duckplyr_rows_append(x, y)))
Output
  <error/rlang_error>
  Error in `rows_append()`:
  ! All columns in `y` must exist in `x`.
  i The following columns only exist in `y`: `c`.

duckplyr_rows_update() requires y keys to exist in x by default

Code
  (expect_error(duckplyr_rows_update(x, y, "a")))
Output
  <error/rlang_error>
  Error in `rows_update()`:
  ! `y` must contain keys that already exist in `x`.
  i The following rows in `y` have keys that don't exist in `x`: `c(1, 3)`.
  i Use `unmatched = "ignore"` if you want to ignore these `y` rows.

duckplyr_rows_update() doesn't allow y keys to be duplicated (#5553)

Code
  (expect_error(duckplyr_rows_update(x, y, by = "a")))
Output
  <error/rlang_error>
  Error in `rows_update()`:
  ! `y` key values must be unique.
  i The following rows contain duplicate key values: `c(1, 2)`.

duckplyr_rows_update() casts keys to their common type for matching but retains x type

Code
  (expect_error(duckplyr_rows_update(x, y, "key")))
Output
  <error/vctrs_error_ptype2>
  Error in `rows_update()`:
  ! Can't combine `x$key` <integer> and `y$key` <character>.

duckplyr_rows_update() casts values to the type of x

Code
  (expect_error(duckplyr_rows_update(x, y, "key")))
Output
  <error/vctrs_error_cast_lossy>
  Error in `rows_update()`:
  ! Can't convert from `y$value` <double> to `x$value` <integer> due to loss of precision.
  * Locations: 1

unmatched is validated

Code
  (expect_error(duckplyr_rows_update(x, y, by = "a", unmatched = "foo")))
Output
  <error/rlang_error>
  Error in `rows_update()`:
  ! `unmatched` must be one of "error" or "ignore", not "foo".
Code
  (expect_error(duckplyr_rows_update(x, y, by = "a", unmatched = 1)))
Output
  <error/rlang_error>
  Error in `rows_update()`:
  ! `unmatched` must be a string or character vector.

duckplyr_rows_patch() requires y keys to exist in x by default

Code
  (expect_error(duckplyr_rows_patch(x, y, "a")))
Output
  <error/rlang_error>
  Error in `rows_patch()`:
  ! `y` must contain keys that already exist in `x`.
  i The following rows in `y` have keys that don't exist in `x`: `c(1, 3)`.
  i Use `unmatched = "ignore"` if you want to ignore these `y` rows.

duckplyr_rows_patch() doesn't allow y keys to be duplicated (#5553)

Code
  (expect_error(duckplyr_rows_patch(x, y, by = "a")))
Output
  <error/rlang_error>
  Error in `rows_patch()`:
  ! `y` key values must be unique.
  i The following rows contain duplicate key values: `c(1, 2)`.

duckplyr_rows_patch() casts keys to their common type for matching but retains x type

Code
  (expect_error(duckplyr_rows_patch(x, y, "key")))
Output
  <error/vctrs_error_ptype2>
  Error in `rows_patch()`:
  ! Can't combine `x$key` <integer> and `y$key` <character>.

duckplyr_rows_patch() casts values to the type of x

Code
  (expect_error(duckplyr_rows_patch(x, y, "key")))
Output
  <error/vctrs_error_cast_lossy>
  Error in `rows_patch()`:
  ! Can't convert from `y$value` <double> to `x$value` <integer> due to loss of precision.
  * Locations: 1

duckplyr_rows_upsert() doesn't allow y keys to be duplicated (#5553)

Code
  (expect_error(duckplyr_rows_upsert(x, y, by = "a")))
Output
  <error/rlang_error>
  Error in `rows_upsert()`:
  ! `y` key values must be unique.
  i The following rows contain duplicate key values: `c(1, 2)`.

duckplyr_rows_upsert() casts keys to their common type for matching but retains x type

Code
  (expect_error(duckplyr_rows_upsert(x, y, "key")))
Output
  <error/vctrs_error_ptype2>
  Error in `rows_upsert()`:
  ! Can't combine `x$key` <integer> and `y$key` <character>.

duckplyr_rows_upsert() casts keys to the type of x

Code
  (expect_error(duckplyr_rows_upsert(x, y, "key")))
Output
  <error/vctrs_error_cast_lossy>
  Error in `rows_upsert()`:
  ! Can't convert from `y$key` <double> to `x$key` <integer> due to loss of precision.
  * Locations: 1

duckplyr_rows_upsert() casts values to the type of x

Code
  (expect_error(duckplyr_rows_upsert(x, y, "key")))
Output
  <error/vctrs_error_cast_lossy>
  Error in `rows_upsert()`:
  ! Can't convert from `y$value` <double> to `x$value` <integer> due to loss of precision.
  * Locations: 1

duckplyr_rows_delete() ignores extra y columns, with a message

Code
  out <- duckplyr_rows_delete(x, y)
Message
  Matching, by = "a"
  Ignoring extra `y` columns: b

Code
  out <- duckplyr_rows_delete(x, y, by = "a")
Message
  Ignoring extra `y` columns: b

duckplyr_rows_delete() requires y keys to exist in x by default

Code
  (expect_error(duckplyr_rows_delete(x, y, "a")))
Output
  <error/rlang_error>
  Error in `rows_delete()`:
  ! `y` must contain keys that already exist in `x`.
  i The following rows in `y` have keys that don't exist in `x`: `c(1, 3)`.
  i Use `unmatched = "ignore"` if you want to ignore these `y` rows.

duckplyr_rows_delete() casts keys to their common type for matching but retains x type

Code
  (expect_error(duckplyr_rows_delete(x, y, "key")))
Output
  <error/vctrs_error_ptype2>
  Error in `rows_delete()`:
  ! Can't combine `x$key` <integer> and `y$key` <character>.

rows_check_x_contains_y() checks that y columns are in x

Code
  (expect_error(rows_check_x_contains_y(x, y)))
Output
  <error/rlang_error>
  Error:
  ! All columns in `y` must exist in `x`.
  i The following columns only exist in `y`: `b`.

rows_check_by() checks that y has at least 1 column before using it (#6061)

Code
  (expect_error(rows_check_by(by = NULL, y = y)))
Output
  <error/rlang_error>
  Error:
  ! `y` must have at least one column.

rows_check_by() uses the first column from y by default, with a message

Code
  by <- rows_check_by(by = NULL, y = y)
Message
  Matching, by = "a"

rows_check_by() validates by

Code
  (expect_error(rows_check_by(by = 1, y = y)))
Output
  <error/rlang_error>
  Error:
  ! `by` must be a character vector.
Code
  (expect_error(rows_check_by(by = character(), y = y)))
Output
  <error/rlang_error>
  Error:
  ! `by` must specify at least 1 column.
Code
  (expect_error(rows_check_by(by = c(x = "y"), y = y)))
Output
  <error/rlang_error>
  Error:
  ! `by` must be unnamed.

rows_check_contains_by() checks that all by columns are in x

Code
  (expect_error(rows_check_contains_by(x, "y", arg = "x")))
Output
  <error/rlang_error>
  Error:
  ! All columns specified through `by` must exist in `x` and `y`.
  i The following columns are missing from `x`: `y`.
Code
  (expect_error(rows_check_contains_by(x, c("y", "x", "z"), arg = "y")))
Output
  <error/rlang_error>
  Error:
  ! All columns specified through `by` must exist in `x` and `y`.
  i The following columns are missing from `y`: `y` and `z`.

rows_check_unique() requires uniqueness

Code
  (expect_error(rows_check_unique(x["x"], "x")))
Output
  <error/rlang_error>
  Error:
  ! `x` key values must be unique.
  i The following rows contain duplicate key values: `c(1, 2, 3)`.
Code
  (expect_error(rows_check_unique(x[c("x", "y")], "y")))
Output
  <error/rlang_error>
  Error:
  ! `y` key values must be unique.
  i The following rows contain duplicate key values: `c(1, 3)`.

duckdblabs/duckplyr documentation built on Nov. 6, 2024, 10 p.m.