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Comprehensive profiling data

Source: R/debrief.R
pv_debrief.Rd

Returns all profiling analysis in a single list for programmatic access. This is the primary function for AI agents and scripts that need comprehensive profiling data without printed output.

Usage

pv_debrief(x, n = 10)

Arguments

x

A profvis object from profvis::profvis().

n

Maximum number of items to include in each category (default 10).

Value

A list containing:

  • total_time_ms: Total profiling time in milliseconds

  • total_samples: Number of profiling samples

  • interval_ms: Sampling interval in milliseconds

  • has_source: Whether source references are available

  • self_time: Data frame of functions by self-time

  • total_time: Data frame of functions by total time

  • hot_lines: Data frame of hot source lines (or NULL if no source refs)

  • hot_paths: Data frame of hot call paths

  • suggestions: Data frame of optimization suggestions

  • gc_pressure: Data frame of GC pressure analysis

  • memory: Data frame of memory allocation by function

  • memory_lines: Data frame of memory allocation by line (or NULL)

Examples

p <- pv_example()
d <- pv_debrief(p)
names(d)
#>  [1] "total_time_ms" "total_samples" "interval_ms"   "has_source"   
#>  [5] "self_time"     "total_time"    "hot_lines"     "hot_paths"    
#>  [9] "suggestions"   "gc_pressure"   "memory"        "memory_lines" 
d$self_time
#>                              label samples time_ms  pct
#> 1                            rnorm       6      30 42.9
#> 2                 x[i] <- rnorm(1)       4      20 28.6
#> 3                    generate_data       3      15 21.4
#> 4 result[i] <- sqrt(abs(x[i])) * 2       1       5  7.1