Sticky: Persistent Attributes

CRAN_Status_Badge Downloads software impact Lifecycle: stable

In base R, objects lose attributes in many common operations such as: subset, [, [[<-, append, etc. or when inserted into or extracted from recursive (list-like) objects such as data frames or data tables. Marking objects ‘sticky’, make attributes resilient to these operations. In essence, sticky makes object behave more like objects in other languages whose attributes are preserved. There isn’t much to the package. sticky/unstickand sticky_all are the only interfaces to the package.

Key Functions


Here is an simple example of a sticky attribute in action. Under base R, attributes do not survive a slice/subset/[ operation:

x <- 1:5
attr(x, 'foo') <- 'bar'
attr(x[1:3],'foo')        # NULL -- attribute removed 

To ensure that they get preserved, simply declare the object as sticky:

x <- sticky(x)
attr(x[1:3],'foo')        # 'bar' -- attribute preserved    

sticky() works for vectors inside table-like objects ( i.e. data.frames and data.tables), preserving their attributes during table operations.

df <- data.frame( 
  sticky   = sticky( structure(1:5, foo="bar") ),
  nonstick = structure( letters[1:5], foo="baz" )
attr( df[2:3,"nonstick"], 'foo' )  # NULL
attr( df[2:3,"sticky"], 'foo' )    # bar

If all elements of a list or a data.frame need to behave in a sticky manner, use sticky_all.

df <- sticky_all(df)
attr( df[2:3,"nonstick"], 'foo' )  # Now 'baz'


Stable Version: CRAN (coming soon)


Development Version: Github


Use Cases

There are a number of things that can be done with sticky:


The issue of attribute resilience has been often asked and debated. Here are a few of the most prevalent discussions.