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Design tradeoffs

Hadley Wickham

Lionel Henry

There are many different ways that magrittr could implement the pipe. The goal of this document is to elucidate the variations, and the various pros and cons of each approach. This document is primarily aimed at the magrittr developers (so we don’t forget about important considerations), but will be of interest to anyone who wants to understand pipes better, or to create their own pipe that makes different tradeoffs

Code transformation

There are three main options for how we might transform a pipeline in base R expressions. Here they are illustrated with x %>% foo() %>% bar():

We’ll first explore the desired properties we might want a pipe to possess and then see how each of the three variants does.

Desired properties

These are the properties that we might want a pipe to possess, roughly ordered from most important to least important.

It is possible to have proper visibility and a neutral impact on refcounts with all implementations by being a bit careful, so we’ll only consider the other properties:

Nested Eager
(mask)
Eager
(mask-num)
Eager
(lexical)
Lazy
(mask)
Lazy
(mask-num)
Lazy
(lexical-num)
Multiple placeholders
Lazy evaluation
Persistence
Eager unbinding
Progressive stack
Lexical effects
Continuous stack

Implications of design decisions

Some properties are a direct reflection of the high level design decisions.

Placeholder binding

The nested pipe does not assign piped expressions to a placeholder. All the other variants perform this assignment. This means that with a nested rewrite approach, it isn’t possible to have multiple placeholders unless the piped expression is pasted multiple times. This would cause multiple evaluations with deleterious effects:

sample(10) %>% list(., .)

# Becomes
list(sample(10), sample(10))

Assigning to the placeholder within an argument would preserve the nestedness and lazyness. However that wouldn’t work properly because there’s no guarantee that the first argument will be evaluated before the second argument.

sample(10) %>% foo(., .)
foo(. <- sample(10), .)

For these reasons, the nested pipe does not support multiple placeholders. By contrast, all the other variants assign the result of pipe expressions to the placeholder. There are variations in how the placeholder binding is created (lazily or eagerly, in a mask or in the current environment, with numbered symbols or with a unique symbol) but all these variants allow multiple placeholders.

Masking environment

Because the local variants of the pipe evaluate in a mask, they do not have lexical effects or a continuous stack. This is unlike the lexical variants that evaluate in the current environment.

Laziness

Unlike the lazy variants, all eager versions implementing the pipe with iterated evaluation do not pass the lazy evaluation criterion.

Secondly, no lazy variant passes the progressive stack criterion. By construction, lazy evaluation requires pushing all the pipe expressions on the stack before evaluation starts. Conversely, all eager variants have a progressive stack.

Numbered placeholders

None of the variants that use numbered placeholders can unbind piped values eagerly. This is how they achieve persistence of these bindings.

Three implementations

The GNU R team is considering implementing the nested approach in base R with a parse-time code transformation (just like -> is transformed to <- by the parser).

We have implemented three approaches in magrittr:

These approaches have complementary strengths and weaknesses.

Nested pipe

`%|>%` <- magrittr::pipe_nested

Multiple placeholders ❌

The nested pipe does not bind expressions to a placeholder and so can’t support multiple placeholders.

"foo" %|>% list(., .)
#> Error: Can't use multiple placeholders.

Lazy evaluation ✅

Because it relies on the usual rules of argument application, the nested pipe is lazy.

{
  stop("oh no") %|>% try(silent = TRUE)
  "success"
}
#> [1] "success"

Persistence and eager unbinding ✅

The pipe expressions are binded as promises within the execution environment of each function. This environment persists as long as a promise holds onto it. Evaluating the promise discards the reference to the environment which becomes available for garbage collection.

For instance, here is a function factory that creates a function. The constructed function returns the value supplied at the time of creation:

factory <- function(x) function() x
fn <- factory(TRUE)
fn()
#> [1] TRUE

This does not cause any issue with the nested pipe:

fn <- TRUE %|>% factory()
fn()

Progressive stack ❌

Because the piped expressions are lazily evaluated, the whole pipeline is pushed on the stack before execution starts. This results in a more complex backtrace than necessary:

faulty <- function() stop("tilt")
f <- function(x) x + 1
g <- function(x) x + 2
h <- function(x) x + 3

faulty() %|>% f() %|>% g() %|>% h()
#> Error in faulty() : tilt

traceback()
#> 7: stop("tilt")
#> 6: faulty()
#> 5: f(faulty())
#> 4: g(f(faulty()))
#> 3: h(g(f(faulty())))
#> 2: .External2(magrittr_pipe) at pipe.R#181
#> 1: faulty() %|>% f() %|>% g() %|>% h()

Also note how the expressions in the backtrace look different from the actual code. This is because of the nested rewrite of the pipeline.

Lexical effects ✅

This is a benefit of using the normal R rules of evaluation. Side effects occur in the correct environment:

foo <- FALSE
TRUE %|>% assign("foo", .)
foo
#> [1] TRUE

Control flow has the correct behaviour:

fn <- function() {
  TRUE %|>% return()
  FALSE
}
fn()
#> [1] TRUE

Continuous stack ✅

Because evaluation occurs in the current environment, the stack is continuous. Let’s instrument errors with a structured backtrace to see what that means:

options(error = rlang::entrace)

The tree representation of the backtrace correctly represents the hierarchy of execution frames:

foobar <- function(x) x %|>% quux()
quux <- function(x) x %|>% stop()

"tilt" %|>% foobar()
#> Error in x %|>% stop() : tilt

rlang::last_trace()
#> <error/rlang_error>
#> tilt
#> Backtrace:
#>     █
#>  1. ├─"tilt" %|>% foobar()
#>  2. └─global::foobar("tilt")
#>  3.   ├─x %|>% quux()
#>  4.   └─global::quux(x)
#>  5.     └─x %|>% stop()

Eager lexical pipe

`%!>%` <- magrittr::pipe_eager_lexical

Multiple placeholders ✅

Pipe expressions are eagerly assigned to the placeholder. This makes it possible to use the placeholder multiple times without causing multiple evaluations.

"foo" %!>% list(., .)
#> [[1]]
#> [1] "foo"
#> 
#> [[2]]
#> [1] "foo"

Lazy evaluation ❌

Assignment forces eager evaluation of each step.

{
  stop("oh no") %!>% try(silent = TRUE)
  "success"
}
#> Error in stop("oh no") %!>% try(silent = TRUE): oh no

Persistence: ❌

Because we’re updating the value of . at each step, the piped expressions are not persistent. This has subtle effects when the piped expressions are not evaluated right away.

With the eager pipe we get rather confusing results with the factory function if we try to call the constructed function in the middle of the pipeline. In the following snippet the placeholder . is binded to the constructed function itself rather than the initial value TRUE, by the time the function is called:

fn <- TRUE %!>% factory() %!>% { .() }
fn()
#> function() x
#> <bytecode: 0x11d1b6758>
#> <environment: 0x11da6d628>

Also, since we’re binding . in the current environment, we need to clean it up once the pipeline has returned. At that point, the placeholder no longer exists:

fn <- TRUE %!>% factory()
fn()
#> Error in fn(): object '.' not found

Or it has been reset to its previous value, if any:

. <- "wrong"
fn <- TRUE %!>% factory()
fn()
#> [1] "wrong"

Eager unbinding: ✅

This is the flip side of updating the value of the placeholder at each step. The previous intermediary values can be collected right away.

Progressive stack: ✅

Since pipe expressions are evaluated one by one as they come, only the relevant part of the pipeline is on the stack when an error is thrown:

faulty <- function() stop("tilt")
f <- function(x) x + 1
g <- function(x) x + 2
h <- function(x) x + 3

faulty() %!>% f() %!>% g() %!>% h()
#> Error in faulty() : tilt

traceback()
#> 4: stop("tilt")
#> 3: faulty()
#> 2: .External2(magrittr_pipe) at pipe.R#163
#> 1: faulty() %!>% f() %!>% g() %!>% h()

Lexical effects and continuous stack: ✅

Evaluating in the current environment rather than in a mask produces the correct side effects:

foo <- FALSE
NA %!>% { foo <- TRUE; . }
#> [1] NA

foo
#> [1] TRUE
fn <- function() {
  TRUE %!>% return()

  FALSE
}
fn()
#> [1] TRUE

Lazy masking pipe

`%?>%` <- magrittr::pipe_lazy_masking

Multiple placeholders ✅

Pipe expressions are lazily assigned to the placeholder. This makes it possible to use the placeholder multiple times without causing multiple evaluations.

"foo" %?>% list(., .)
#> [[1]]
#> [1] "foo"
#> 
#> [[2]]
#> [1] "foo"

Lazy evaluation ✅

Arguments are assigned with delayedAssign() and lazily evaluated:

{
  stop("oh no") %?>% try(silent = TRUE)
  "success"
}
#> [1] "success"

Persistence: ✅

The lazy masking pipe uses one masking environment per pipe expression. This allows persistence of the intermediary values and out of order evaluation. The factory function works as expected for instance:

fn <- TRUE %?>% factory()
fn()
#> [1] TRUE

Eager unbinding: ✅

Because we use one mask environment per pipe expression, the intermediary values can be collected as soon as they are no longer needed.

Progressive stack: ❌

With a lazy pipe the whole pipeline is pushed onto the stack before evaluation.

faulty <- function() stop("tilt")
f <- function(x) x + 1
g <- function(x) x + 2
h <- function(x) x + 3

faulty() %?>% f() %?>% g() %?>% h()
#> Error in faulty() : tilt

traceback()
#> 7: stop("tilt")
#> 6: faulty()
#> 5: f(.)
#> 4: g(.)
#> 3: h(.)
#> 2: .External2(magrittr_pipe) at pipe.R#174
#> 1: faulty() %?>% f() %?>% g() %?>% h()

Note however how the backtrace is less cluttered than with the nested pipe approach, thanks to the placeholder.

Lexical effects ❌

The lazy pipe evaluates in a mask. This causes lexical side effects to occur in the incorrect environment.

foo <- FALSE
TRUE %?>% assign("foo", .)
foo
#> [1] FALSE

Stack-sensitive functions like return() function cannot find the proper frame environment:

fn <- function() {
  TRUE %?>% return()
  FALSE
}
fn()
#> [1] FALSE

Continuous stack ❌

The masking environment causes a discontinuous stack tree:

foobar <- function(x) x %?>% quux()
quux <- function(x) x %?>% stop()

"tilt" %?>% foobar()
#> Error in x %?>% stop() : tilt

rlang::last_trace()
#> <error/rlang_error>
#> tilt
#> Backtrace:
#>     █
#>  1. ├─"tilt" %?>% foobar()
#>  2. ├─global::foobar(.)
#>  3. │ └─x %?>% quux()
#>  4. └─global::quux(.)
#>  5.   └─x %?>% stop()

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