After building a dataset, it's beneficial (if not
a requirement) to run tests on that dataset to ensure
that it behaves as expected. blueprintr gives authors
a framework to run these tests automatically, both for
individual variables and general dataset checks.
blueprintr provides three functions as models for developing
these kinds of functions: one to check that all expected variables
are present, one to check the variable types, and a generic
function that checks if variable values are contained within
a known set.
all_variables_present(df, meta, blueprint)
all_types_match(df, meta)