Initial CRAN release 0.1.1

tidyselect is the new home for the legacy functions
dplyr::select_vars(), dplyr::rename_vars() and
dplyr::select_var().

API changes

We took this opportunity to make a few changes to the API:

• select_vars() and rename_vars() are now vars_select() and
  vars_rename(). This follows the tidyverse convention that a prefix
  corresponds to the input type while suffixes indicate the output
  type. Similarly, select_var() is now vars_pull().

• The arguments are now prefixed with dots to limit argument matching
  issues. While the dots help, it is still a good idea to splice a
  list of captured quosures to make sure dotted arguments are never
  matched to vars_select()'s named arguments:

  vars_select(vars, !!! quos(...))
  

• Error messages can now be customised. For consistency with dplyr,
  error messages refer to "columns" by default. This assumes that the
  variables being selected come from a data frame. If this is not
  appropriate for your DSL, you can now add an attribute vars_type
  to the .vars vector to specify alternative names. This must be a
  character vector of length 2 whose first component is the singular
  form and the second is the plural. For example, c("variable", "variables").

Establishing a variable context

tidyselect provides a few more ways of establishing a variable
context:

• scoped_vars() sets up a variable context along with an an exit
  hook that automatically restores the previous variables. It is the
  preferred way of changing the variable context.

  with_vars() takes variables and an expression and evaluates the
  latter in the context of the former.

• poke_vars() establishes a new variable context. It returns the
  previous context invisibly and it is your responsibility to restore
  it after you are done. This is for expert use only.

  current_vars() has been renamed to peek_vars(). This naming is a
  reference to peek and poke
  from legacy languages.

New evaluation semantics

The evaluation semantics for selecting verbs have changed. Symbols are
now evaluated in a data-only context that is isolated from the calling
environment. This means that you can no longer refer to local variables
unless you are explicitly unquoting these variables with !!, which
is mostly for expert use.

Note that since dplyr 0.7, helper calls (like starts_with()) obey
the opposite behaviour and are evaluated in the calling context
isolated from the data context. To sum up, symbols can only refer to
data frame objects, while helpers can only refer to contextual
objects. This differs from usual R evaluation semantics where both
the data and the calling environment are in scope (with the former
prevailing over the latter).