The goal of waldo is to find and concisely describe the difference between a pair of R objects, with the primary goal of making it easier to figure out what’s gone wrong in your unit tests.

waldo::compare() is inspired by all.equal(), but takes additional care to generate actionable insights by:

  • Ordering the differences from most important to least important.
  • Displaying the values of atomic vectors that are actually different.
  • Carefully using colour to emphasise changes (while still being readable when colour isn’t available).
  • Using R code (not a text description) to show where differences arise.
  • Where possible, comparing elements by name, rather than by position.
  • Erring on the side of producing too much output, rather than too little.


You can install the released version of waldo from CRAN with:


When comparing atomic vectors, compare() produces diffs (thanks to diffobj) that highlight additions, deletions, and changes, along with a little context:

Depending on the relative size of the differences and the width of your console you’ll get one of three displays:

When comparing more complex objects, waldo creates an executable code path telling you where the differences lie:

  • Unnamed lists are compared by position:

    compare(list(factor("x")), list(1L))

  • Named lists, including data frames, are compared by name. For example, note that the following comparison reports a difference in the class and names, but not the values of the columns.

    df1 <- data.frame(x = 1:3, y = 3:1)
    df2 <- tibble::tibble(rev(df1))
    compare(df1, df2)

  • Recursion can be arbitrarily deep:

    x <- list(a = list(b = list(c = list(structure(1, e = 1)))))
    y <- list(a = list(b = list(c = list(structure(1, e = "a")))))
    compare(x, y)