• Fixed a C level protection issue in %>% (#256).
  • New eager pipe %!>% for sequential evaluation (#247). Consider using force() in your functions instead to make them strict, if sequentiality is required. See the examples in ?"pipe-eager".

  • Fixed an issue that could cause pipe invocations to fail in versions of R built with --enable-strict-barrier. (#239, @kevinushey)

  • Fixed issue caused by objects with certain names being present in the calling environment (#233).

  • Fixed regression in freduce() with long lists (kcf-jackson/sketch#5).

Fast and lean implementation of the pipe

The pipe has been rewritten in C with the following goals in mind:

  • Minimal performance cost.
  • Minimal impact on backtraces.
  • No impact on reference counts.

As part of this rewrite we have changed the behaviour of the pipe to make it closer to the implementation that will likely be included in a future version of R. The pipe now evaluates piped expressions lazily (#120). The main consequence of this change is that warnings and errors can now be handled by trailing pipe calls:


stop("foo") %>% try()
warning("bar") %>% suppressWarnings()

Breaking changes

The pipe rewrite should generally not affect your code. We have checked magrittr on 2800 CRAN packages and found only a dozen of failures. The development version of magrittr has been advertised on social media for a 3 months trial period, and no major issues were reported. However, there are some corner cases that might require updating your code. Below is a report of the backward incompatibilities we found in real code to help you transition, should you find an issue in your code.

Behaviour of return() in a pipeline

In previous versions of magrittr, the behaviour of return() within pipe expressions was undefined. Should it return from the current pipe expression, from the whole pipeline, or from the enclosing function? The behaviour that makes the most sense is to return from the enclosing function. However, we can’t make this work easily with the new implementation, and so calling return() is now an error.


my_function <- function(x) {
  x %>% {
    if (.) return("true")
    "false"
  }
}

my_function(TRUE)
#> Error: no function to return from, jumping to top level

In magrittr 1.5, return() used to return from the current pipe expression. You can rewrite this to the equivalent:


my_function <- function(x) {
  x %>% {
    if (.) {
      "true"
    } else {
      "false"
    }
  }
}

my_function(TRUE)
#> [1] "true"

For backward-compatibility we have special-cased trailing return() calls as this is a common occurrence in packages:

Note however that this only returns from the pipeline, not the enclosing function (which is the historical behaviour):


my_function <- function() {
  "value" %>% identity() %>% return()
  "wrong value"
}

my_function()
#> [1] "wrong value"

It is generally best to avoid using return() in a pipeline, even if trailing.

Failures caused by laziness

With the new lazy model for the evaluation of pipe expressions, earlier parts of a pipeline are not yet evaluated when the last pipe expression is called. They only get evaluated when the last function actually uses the piped arguments:


ignore <- function(x) "return value"
stop("never called") %>% ignore()
#> [1] "return value"

This should generally not cause problems. However we found some functions with special behaviour, written under the assumption that earlier parts of the pipeline were already evaluated and had already produced side effects. This is generally incorrect behaviour because that means that these functions do not work properly when called with the nested form, e.g. f(g(1)) instead of 1 %>% g() %>% f().

The solution to fix this is to call force() on the inputs to force evaluation, and only then check for side effects:


my_function <- function(data) {
  force(data)
  peek_side_effect()
}

Another issue caused by laziness is that if any function in a pipeline returns invisibly, than the whole pipeline returns invisibly as well.

This is consistent with the equivalent nested code. This behaviour can be worked around in two ways. You can force visibility by wrapping the pipeline in parentheses:


my_function <- function(x) {
  (x %>% invisible() %>% identity())
}

Or by assigning the result to a variable and return it:


my_function <- function(x) {
  out <- x %>% invisible() %>% identity()
  out
}

Incorrect call stack introspection

The magrittr expressions are no longer evaluated in frames that can be inspected by sys.frames() or sys.parent(). Using these functions for implementing actual functionality (as opposed as debugging tools) is likely to produce bugs. Instead, you should generally use parent.frame() which works even when R code is called from non-inspectable frames. This happens with e.g. do.call() and the new C implementation of magrittr.

Incorrect assumptions about magrittr internals

Some packages were depending on how magrittr was internally structured. Robust code should only use the documented and exported API of other packages.

Bug fixes

  • Can now use the placeholder . with the splicing operator !!! from rlang (#191).

  • Piped arguments are now persistent. They can be evaluated after the pipeline has returned, which fixes subtle issues with function factories (#159, #195).

New features

Functional sequences.

A pipeline, or a “functional sequence”, need not be applied to a left-hand side value instantly. Instead it can serve as a function definition. A pipeline where the left-most left-hand side is the magrittr placeholder (the dot .) will thus create a function, which applies each right-hand side in sequence to its argument, e.g. f <- . %>% abs %>% mean(na.rm = TRUE).

New operators

Three new operators are introduced for some special cases

  • Assignment pipe: %<>%
  • Tee pipe: %T>%
  • Exposition pipe: %$%

For more information see the documentation, e.g. ?%T>%.

Lambdas

Lambdas can now be made by enclosing several statements in curly braces, and is a unary function of the dot argument.

For more information and examples, see the updated vignette, and help files.