Extract the data underlying an S3 vector object, i.e. the underlying (named) atomic vector or list.

  • vec_data() returns unstructured data. The only attributes preserved are names, dims, and dimnames.

    Currently, due to the underlying memory architecture of R, this creates a full copy of the data.

  • vec_proxy() may return structured data. This generic is the main customisation point in vctrs, along with vec_restore(). See the section below to learn when you should implement vec_proxy().

    Methods must return a vector type. Records and data frames will be processed rowwise.





A vector or object implementing vec_proxy().


The data underlying x, free from any attributes except the names.

When should you proxy your type

You should only implement vec_proxy() when your type is designed around a non-vector class. I.e. anything that is not either:

  • An atomic vector

  • A bare list

  • A data frame

In this case, implement vec_proxy() to return such a vector class. The vctrs operations such as vec_slice() are 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 in the vec_proxy() method. For instance, here is the definition for list_of:

vec_proxy.vctrs_list_of <- function(x) {

Another case where you need to implement a proxy is record types. Record types should return a data frame, as in the POSIXlt method:

vec_proxy.POSIXlt <- function(x) {

Note that you don't need to implement vec_proxy() when your class inherits from vctrs_vctr or vctrs_rcrd.

See also

See vec_restore() for the inverse operation: it restores attributes given a bare vector and a prototype; vec_restore(vec_data(x), x) will always yield x.