R: Profile an R expression and visualize profiling data

profvis {profvis}

R Documentation

Profile an R expression and visualize profiling data

Description

This function will run an R expression with profiling, and then return an htmlwidget for interactively exploring the profiling data.

Usage

profvis(
  expr = NULL,
  interval = 0.01,
  prof_output = NULL,
  prof_input = NULL,
  width = NULL,
  height = NULL,
  split = c("h", "v"),
  torture = 0,
  simplify = TRUE,
  rerun = FALSE
)

Arguments

`expr`	Expression to profile. Not compatible with `prof_input`. The expression is repeatedly evaluated until 'Rprof()' produces an output. It can _be_ a quosure injected with [rlang::inject()] but it cannot _contain_ injected quosures.
`interval`	Interval for profiling samples, in seconds. Values less than 0.005 (5 ms) will probably not result in accurate timings
`prof_output`	Name of an Rprof output file or directory in which to save profiling data. If `NULL` (the default), a temporary file will be used and automatically removed when the function exits. For a directory, a random filename is used.
`prof_input`	The path to an `Rprof` data file. Not compatible with `expr` or `prof_output`.
`width`	Width of the htmlwidget.
`height`	Height of the htmlwidget
`split`	Direction of split. Either `"v"` (the default) for vertical, or `"h"` for horizontal. This is the orientation of the split bar.
`torture`	Triggers garbage collection after every `torture` memory allocation call. Note that memory allocation is only approximate due to the nature of the sampling profiler and garbage collection: when garbage collection triggers, memory allocations will be attributed to different lines of code. Using `torture = steps` helps prevent this, by making R trigger garbage collection after every `torture` memory allocation step.
`simplify`	Whether to simplify the profiles by removing intervening frames caused by lazy evaluation. This only has an effect on R 4.0. See the `filter.callframes` argument of `Rprof()`.
`rerun`	If 'TRUE', 'Rprof()' is run again with 'expr' until a profile is actually produced. This is useful for the cases where 'expr' returns too quickly, before R had time to sample a profile. Can also be a string containing a regexp to match profiles. In this case, 'profvis()' reruns 'expr' until the regexp matches the modal value of the profile stacks.

Details

An alternate way to use profvis is to separately capture the profiling data to a file using Rprof(), and then pass the path to the corresponding data file as the prof_input argument to profvis().

Examples

# Only run these examples in interactive R sessions
if (interactive()) {

# Profile some code
profvis({
  dat <- data.frame(
    x = rnorm(5e4),
    y = rnorm(5e4)
  )

  plot(x ~ y, data = dat)
  m <- lm(x ~ y, data = dat)
  abline(m, col = "red")
})


# Save a profile to an HTML file
p <- profvis({
  dat <- data.frame(
    x = rnorm(5e4),
    y = rnorm(5e4)
  )

  plot(x ~ y, data = dat)
  m <- lm(x ~ y, data = dat)
  abline(m, col = "red")
})
htmlwidgets::saveWidget(p, "profile.html")

# Can open in browser from R
browseURL("profile.html")

}