# vctrs 0.2.0.9000 Unreleased

• New vec_split_id() for locating unique groups in a vector. This helps power vec_split() by returning the unique values and their locations in the original vector (#514).

• Equality and ordering methods are now implemented for raw and complex vectors (@romainfrancois).

# vctrs 0.2.0 2019-07-05

With the 0.2.0 release, many vctrs functions have been rewritten with native C code to improve performance. Functions like vec_c() and vec_rbind() should now be fast enough to be used in packages. This is an ongoing effort, for instance the handling of factors and dates has not been rewritten yet. These classes still slow down vctrs primitives.

The API in 0.2.0 has been updated, please see a list of breaking changes below. vctrs has now graduated from experimental to a maturing package (see the lifecycle of tidyverse packages). Please note that API changes are still planned for future releases, for instance vec_ptype2() and vec_cast() might need to return a sentinel instead of failing with an error when there is no common type or possible cast.

## Breaking changes

• Lossy casts now throw errors of type vctrs_error_cast_lossy. Previously these were warnings. You can suppress these errors selectively with allow_lossy_cast() to get the partial cast results. To implement your own lossy cast operation, call the new exported function maybe_lossy_cast().

• vec_c() now fails when an input is supplied with a name but has internal names or is length > 1:

vec_c(foo = c(a = 1))
#> Error: Can't merge the outer name foo with a named vector.
#> Please supply a .name_spec specification.

vec_c(foo = 1:3)
#> Error: Can't merge the outer name foo with a vector of length > 1.
#> Please supply a .name_spec specification.

You can supply a name specification that describes how to combine the external name of the input with its internal names or positions:

# Name spec as glue string:
vec_c(foo = c(a = 1), .name_spec = "{outer}_{inner}")

# Name spec as a function:
vec_c(foo = c(a = 1), .name_spec = function(outer, inner) paste(outer, inner, sep = "_"))
vec_c(foo = c(a = 1), .name_spec = ~ paste(.x, .y, sep = "_"))
• vec_empty() has been renamed to vec_is_empty().

• vec_dim() and vec_dims() are no longer exported.

• vec_na() has been renamed to vec_init(), as the primary use case is to initialize an output container.

• vec_slice<- is now type stable (#140). It always returns the same type as the LHS. If needed, the RHS is cast to the correct type, but only if both inputs are coercible. See examples in ?vec_slice.

• We have renamed the type particle to ptype:

• vec_type() => vec_ptype()
• vec_type2() => vec_ptype2()
• vec_type_common() => vec_ptype_common()

Consequently, vec_ptype() was renamed to vec_ptype_show().

## New features

• New vec_proxy() generic. This is the main customisation point in vctrs along with vec_restore(). You should only implement it when your type is designed around a non-vector class (atomic vectors, bare lists, data frames). In this case, vec_proxy() should return such a vector class. The vctrs operations will be applied on the proxy and vec_restore() is called to restore the original representation of your type.

The most common case where you need to implement vec_proxy() is for S3 lists. In vctrs, S3 lists are treated as scalars by default. This way we don’t treat objects like model fits as vectors. To prevent vctrs from treating your S3 list as a scalar, unclass it from the vec_proxy() method. For instance here is the definition for list_of:

#' @export
vec_proxy.vctrs_list_of <- function(x) {
unclass(x)
}

If you inherit from vctrs_vctr or vctrs_rcrd you don’t need to implement vec_proxy().

• vec_c(), vec_rbind(), and vec_cbind() gain a .name_repair argument (#227, #229).

• vec_c(), vec_rbind(), vec_cbind(), and all functions relying on vec_ptype_common() now have more informative error messages when some of the inputs have nested data frames that are not convergent:

df1 <- tibble(foo = tibble(bar = tibble(x = 1:3, y = letters[1:3])))
df2 <- tibble(foo = tibble(bar = tibble(x = 1:3, y = 4:6)))

vec_rbind(df1, df2)
#> Error: No common type for ..1$foo$bar$y <character> and ..2$foo$bar$y <integer>.
• vec_cbind() now turns named data frames to packed columns.

data <- tibble::tibble(x = 1:3, y = letters[1:3])
data <- vec_cbind(data, packed = data)
data
# A tibble: 3 x 3
x y     packed$x$y
<int> <chr>    <int> <chr>
1     1 a            1 a
2     2 b            2 b
3     3 c            3 c

Packed data frames are nested in a single column. This makes it possible to access it through a single name:

data\$packed
# A tibble: 3 x 2
x y
<int> <chr>
1     1 a
2     2 b
3     3 c

We are planning to use this syntax more widely in the tidyverse.

• New vec_is() function to check whether a vector conforms to a prototype and/or a size. Unlike vec_assert(), it doesn’t throw errors but returns TRUE or FALSE (#79).

Called without a specific type or size, vec_assert() tests whether an object is a data vector or a scalar. S3 lists are treated as scalars by default. Implement a vec_is_vector() for your class to override this property (or derive from vctrs_vctr).

• New vec_order() and vec_sort() for ordering and sorting generalised vectors.

• New .names_to parameter for vec_rbind(). If supplied, this should be the name of a column where the names of the inputs are copied. This is similar to the .id parameter of dplyr::bind_rows().

• New vec_seq_along() and vec_init_along() create useful sequences (#189).

• vec_slice() now preserves character row names, if present.

• New vec_split(x, by) is a generalisation of split() that can divide a vector into groups formed by the unique values of another vector. Returns a two-column data frame containing unique values of by aligned with matching x values (#196).

## Other features and bug fixes

• Using classed errors of class "vctrs_error_assert" for failed assertions, and of class "vctrs_error_incompatible" (with subclasses _type, _cast and _op) for errors on incompatible types (#184).

• Character indexing is now only supported for named objects, an error is raised for unnamed objects (#171).

• Predicate generics now consistently return logical vectors when passed a vctrs_vctr class. They used to restore the output to their input type (#251).

• list_of() now has an as.character() method. It uses vec_ptype_abbr() to collapse complex objects into their type representation (tidyverse/tidyr#654).

• New stop_incompatible_size() to signal a failure due to mismatched sizes.

• New validate_list_of() (#193).

• vec_arith() is consistent with base R when combining difftime and date, with a warning if casts are lossy (#192).

• vec_c() and vec_rbind() now handle data.frame columns properly (@yutannihilation, #182).

• vec_cast(x, data.frame()) preserves the number of rows in x.

• vec_equal() now handles missing values symmetrically (#204).

• vec_equal_na() now returns TRUE for data frames and records when every component is missing, not when any component is missing (#201).

• vec_init() checks input is a vector.

• vec_proxy_compare() gains an experimental relax argument, which allows data frames to be orderable even if all their columns are not (#210).

• vec_size() now works with positive short row names. This fixes issues with data frames created with jsonlite (#220).

• vec_slice<- now has a vec_assign() alias. Use vec_assign() when you don’t want to modify the original input.

• vec_slice() now calls vec_restore() automatically. Unlike the default [ method from base R, attributes are preserved by default.

• vec_slice() can correct slice 0-row data frames (#179).

• New vec_repeat() for repeating each element of a vector the same number of times.

• vec_type2(x, data.frame()) ensures that the returned object has names that are a length-0 character vector.