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Profile.jl
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Profile.jl
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# This file is a part of Julia. License is MIT: https://julialang.org/license
"""
Profiling support, main entry point is the [`@profile`](@ref) macro.
"""
module Profile
import Base.StackTraces: lookup, UNKNOWN, show_spec_linfo, StackFrame
# deprecated functions: use `getdict` instead
lookup(ip::UInt) = lookup(convert(Ptr{Cvoid}, ip))
export @profile
"""
@profile
`@profile <expression>` runs your expression while taking periodic backtraces. These are
appended to an internal buffer of backtraces.
"""
macro profile(ex)
return quote
try
status = start_timer()
if status < 0
error(error_codes[status])
end
$(esc(ex))
finally
stop_timer()
end
end
end
####
#### User-level functions
####
"""
init(; n::Integer, delay::Real))
Configure the `delay` between backtraces (measured in seconds), and the number `n` of
instruction pointers that may be stored. Each instruction pointer corresponds to a single
line of code; backtraces generally consist of a long list of instruction pointers. Current
settings can be obtained by calling this function with no arguments, and each can be set
independently using keywords or in the order `(n, delay)`.
"""
function init(; n::Union{Nothing,Integer} = nothing, delay::Union{Nothing,Real} = nothing)
n_cur = ccall(:jl_profile_maxlen_data, Csize_t, ())
delay_cur = ccall(:jl_profile_delay_nsec, UInt64, ())/10^9
if n === nothing && delay === nothing
return Int(n_cur), delay_cur
end
nnew = (n === nothing) ? n_cur : n
delaynew = (delay === nothing) ? delay_cur : delay
init(nnew, delaynew)
end
function init(n::Integer, delay::Real)
status = ccall(:jl_profile_init, Cint, (Csize_t, UInt64), n, round(UInt64,10^9*delay))
if status == -1
error("could not allocate space for ", n, " instruction pointers")
end
end
# init with default values
# Use a max size of 1M profile samples, and fire timer every 1ms
if Sys.iswindows()
__init__() = init(1_000_000, 0.01)
else
__init__() = init(1_000_000, 0.001)
end
"""
clear()
Clear any existing backtraces from the internal buffer.
"""
clear() = ccall(:jl_profile_clear_data, Cvoid, ())
const LineInfoDict = Dict{UInt64, Vector{StackFrame}}
const LineInfoFlatDict = Dict{UInt64, StackFrame}
struct ProfileFormat
maxdepth::Int
mincount::Int
noisefloor::Float64
sortedby::Symbol
combine::Bool
C::Bool
recur::Symbol
function ProfileFormat(;
C = false,
combine = true,
maxdepth::Int = typemax(Int),
mincount::Int = 0,
noisefloor = 0,
sortedby::Symbol = :filefuncline,
recur::Symbol = :off)
return new(maxdepth, mincount, noisefloor, sortedby, combine, C, recur)
end
end
"""
print([io::IO = stdout,] [data::Vector]; kwargs...)
Prints profiling results to `io` (by default, `stdout`). If you do not
supply a `data` vector, the internal buffer of accumulated backtraces
will be used.
The keyword arguments can be any combination of:
- `format` -- Determines whether backtraces are printed with (default, `:tree`) or without (`:flat`)
indentation indicating tree structure.
- `C` -- If `true`, backtraces from C and Fortran code are shown (normally they are excluded).
- `combine` -- If `true` (default), instruction pointers are merged that correspond to the same line of code.
- `maxdepth` -- Limits the depth higher than `maxdepth` in the `:tree` format.
- `sortedby` -- Controls the order in `:flat` format. `:filefuncline` (default) sorts by the source
line, `:count` sorts in order of number of collected samples, and `:overhead` sorts by the number of samples
incurred by each function by itself.
- `noisefloor` -- Limits frames that exceed the heuristic noise floor of the sample (only applies to format `:tree`).
A suggested value to try for this is 2.0 (the default is 0). This parameter hides samples for which `n <= noisefloor * √N`,
where `n` is the number of samples on this line, and `N` is the number of samples for the callee.
- `mincount` -- Limits the printout to only those lines with at least `mincount` occurrences.
- `recur` -- Controls the recursion handling in `:tree` format. `:off` (default) prints the tree as normal. `:flat` instead
compresses any recursion (by ip), showing the approximate effect of converting any self-recursion into an iterator.
`:flatc` does the same but also includes collapsing of C frames (may do odd things around `jl_apply`).
"""
function print(io::IO,
data::Vector{<:Unsigned} = fetch(),
lidict::Union{LineInfoDict, LineInfoFlatDict} = getdict(data)
;
format = :tree,
C = false,
combine = true,
maxdepth::Int = typemax(Int),
mincount::Int = 0,
noisefloor = 0,
sortedby::Symbol = :filefuncline,
recur::Symbol = :off)
print(io, data, lidict, ProfileFormat(
C = C,
combine = combine,
maxdepth = maxdepth,
mincount = mincount,
noisefloor = noisefloor,
sortedby = sortedby,
recur = recur),
format)
end
function print(io::IO, data::Vector{<:Unsigned}, lidict::Union{LineInfoDict, LineInfoFlatDict}, fmt::ProfileFormat, format::Symbol)
cols::Int = Base.displaysize(io)[2]
data = convert(Vector{UInt64}, data)
fmt.recur ∈ (:off, :flat, :flatc) || throw(ArgumentError("recur value not recognized"))
if format === :tree
tree(io, data, lidict, cols, fmt)
elseif format === :flat
fmt.recur === :off || throw(ArgumentError("format flat only implements recur=:off"))
flat(io, data, lidict, cols, fmt)
else
throw(ArgumentError("output format $(repr(format)) not recognized"))
end
end
"""
print([io::IO = stdout,] data::Vector, lidict::LineInfoDict; kwargs...)
Prints profiling results to `io`. This variant is used to examine results exported by a
previous call to [`retrieve`](@ref). Supply the vector `data` of backtraces and
a dictionary `lidict` of line information.
See `Profile.print([io], data)` for an explanation of the valid keyword arguments.
"""
print(data::Vector{<:Unsigned} = fetch(), lidict::Union{LineInfoDict, LineInfoFlatDict} = getdict(data); kwargs...) =
print(stdout, data, lidict; kwargs...)
"""
retrieve() -> data, lidict
"Exports" profiling results in a portable format, returning the set of all backtraces
(`data`) and a dictionary that maps the (session-specific) instruction pointers in `data` to
`LineInfo` values that store the file name, function name, and line number. This function
allows you to save profiling results for future analysis.
"""
function retrieve()
data = fetch()
return (data, getdict(data))
end
function getdict(data::Vector{UInt})
# Lookup is expensive, so do it only once per ip.
udata = unique(data)
dict = LineInfoDict()
for ip in udata
st = lookup(convert(Ptr{Cvoid}, ip))
# To correct line numbers for moving code, put it in the form expected by
# Base.update_stackframes_callback[]
stn = map(x->(x, 1), st)
try Base.invokelatest(Base.update_stackframes_callback[], stn) catch end
dict[UInt64(ip)] = map(first, stn)
end
return dict
end
"""
flatten(btdata::Vector, lidict::LineInfoDict) -> (newdata::Vector{UInt64}, newdict::LineInfoFlatDict)
Produces "flattened" backtrace data. Individual instruction pointers
sometimes correspond to a multi-frame backtrace due to inlining; in
such cases, this function inserts fake instruction pointers for the
inlined calls, and returns a dictionary that is a 1-to-1 mapping
between instruction pointers and a single StackFrame.
"""
function flatten(data::Vector, lidict::LineInfoDict)
# Makes fake instruction pointers, counting down from typemax(UInt)
newip = typemax(UInt64) - 1
taken = Set(keys(lidict)) # make sure we don't pick one that's already used
newdict = Dict{UInt64,StackFrame}()
newmap = Dict{UInt64,Vector{UInt64}}()
for (ip, trace) in lidict
if length(trace) == 1
newdict[ip] = trace[1]
else
newm = UInt64[]
for sf in trace
while newip ∈ taken && newip > 0
newip -= 1
end
newip == 0 && error("all possible instruction pointers used")
push!(newm, newip)
newdict[newip] = sf
newip -= 1
end
newmap[ip] = newm
end
end
newdata = UInt64[]
for ip::UInt64 in data
if haskey(newmap, ip)
append!(newdata, newmap[ip])
else
push!(newdata, ip)
end
end
return (newdata, newdict)
end
# Take a file-system path and try to form a concise representation of it
# based on the package ecosystem
function short_path(spath::Symbol, filenamecache::Dict{Symbol, String})
return get!(filenamecache, spath) do
path = string(spath)
if isabspath(path)
if ispath(path)
# try to replace the file-system prefix with a short "@Module" one,
# assuming that profile came from the current machine
# (or at least has the same file-system layout)
root = path
while !isempty(root)
root, base = splitdir(root)
isempty(base) && break
@assert startswith(path, root)
for proj in Base.project_names
project_file = joinpath(root, proj)
if Base.isfile_casesensitive(project_file)
pkgid = Base.project_file_name_uuid(project_file, "", Base.TOMLCache())
isempty(pkgid.name) && return path # bad Project file
# return the joined the module name prefix and path suffix
path = path[nextind(path, sizeof(root)):end]
return string("@", pkgid.name, path)
end
end
end
end
return path
elseif isfile(joinpath(Sys.BINDIR::String, Base.DATAROOTDIR, "julia", "base", path))
# do the same mechanic for Base (or Core/Compiler) files as above,
# but they start from a relative path
return joinpath("@Base", normpath(path))
else
# for non-existent relative paths (such as "REPL[1]"), just consider simplifying them
return normpath(path) # drop leading "./"
end
end
end
"""
callers(funcname, [data, lidict], [filename=<filename>], [linerange=<start:stop>]) -> Vector{Tuple{count, lineinfo}}
Given a previous profiling run, determine who called a particular function. Supplying the
filename (and optionally, range of line numbers over which the function is defined) allows
you to disambiguate an overloaded method. The returned value is a vector containing a count
of the number of calls and line information about the caller. One can optionally supply
backtrace `data` obtained from [`retrieve`](@ref); otherwise, the current internal
profile buffer is used.
"""
function callers end
function callers(funcname::String, bt::Vector, lidict::LineInfoFlatDict; filename = nothing, linerange = nothing)
if filename === nothing && linerange === nothing
return callersf(li -> String(li.func) == funcname,
bt, lidict)
end
filename === nothing && throw(ArgumentError("if supplying linerange, you must also supply the filename"))
filename = String(filename)
if linerange === nothing
return callersf(li -> String(li.func) == funcname && String(li.file) == filename,
bt, lidict)
else
return callersf(li -> String(li.func) == funcname && String(li.file) == filename && in(li.line, linerange),
bt, lidict)
end
end
callers(funcname::String, bt::Vector, lidict::LineInfoDict; kwargs...) =
callers(funcname, flatten(bt, lidict)...; kwargs...)
callers(funcname::String; kwargs...) = callers(funcname, retrieve()...; kwargs...)
callers(func::Function, bt::Vector, lidict::LineInfoFlatDict; kwargs...) =
callers(string(func), bt, lidict; kwargs...)
callers(func::Function; kwargs...) = callers(string(func), retrieve()...; kwargs...)
##
## For --track-allocation
##
# Reset the malloc log. Used to avoid counting memory allocated during
# compilation.
"""
clear_malloc_data()
Clears any stored memory allocation data when running julia with `--track-allocation`.
Execute the command(s) you want to test (to force JIT-compilation), then call
[`clear_malloc_data`](@ref). Then execute your command(s) again, quit
Julia, and examine the resulting `*.mem` files.
"""
clear_malloc_data() = ccall(:jl_clear_malloc_data, Cvoid, ())
# C wrappers
start_timer() = ccall(:jl_profile_start_timer, Cint, ())
stop_timer() = ccall(:jl_profile_stop_timer, Cvoid, ())
is_running() = ccall(:jl_profile_is_running, Cint, ())!=0
get_data_pointer() = convert(Ptr{UInt}, ccall(:jl_profile_get_data, Ptr{UInt8}, ()))
len_data() = convert(Int, ccall(:jl_profile_len_data, Csize_t, ()))
maxlen_data() = convert(Int, ccall(:jl_profile_maxlen_data, Csize_t, ()))
error_codes = Dict(
-1=>"cannot specify signal action for profiling",
-2=>"cannot create the timer for profiling",
-3=>"cannot start the timer for profiling",
-4=>"cannot unblock SIGUSR1")
"""
fetch() -> data
Returns a copy of the buffer of profile backtraces. Note that the
values in `data` have meaning only on this machine in the current session, because it
depends on the exact memory addresses used in JIT-compiling. This function is primarily for
internal use; [`retrieve`](@ref) may be a better choice for most users.
"""
function fetch()
maxlen = maxlen_data()
len = len_data()
if (len == maxlen)
@warn """The profile data buffer is full; profiling probably terminated
before your program finished. To profile for longer runs, call
`Profile.init()` with a larger buffer and/or larger delay."""
end
data = Vector{UInt}(undef, len)
GC.@preserve data unsafe_copyto!(pointer(data), get_data_pointer(), len)
return data
end
## Print as a flat list
# Counts the number of times each line appears, at any nesting level and at the topmost level
# Merging multiple equivalent entries and recursive calls
function parse_flat(::Type{T}, data::Vector{UInt64}, lidict::Union{LineInfoDict, LineInfoFlatDict}, C::Bool) where {T}
lilist = StackFrame[]
n = Int[]
m = Int[]
lilist_idx = Dict{T, Int}()
recursive = Set{T}()
first = true
totalshots = 0
for ip in data
if ip == 0
totalshots += 1
empty!(recursive)
first = true
continue
end
frames = lidict[ip]
nframes = (frames isa Vector ? length(frames) : 1)
for i = 1:nframes
frame = (frames isa Vector ? frames[i] : frames)
!C && frame.from_c && continue
key = (T === UInt64 ? ip : frame)
idx = get!(lilist_idx, key, length(lilist) + 1)
if idx > length(lilist)
push!(recursive, key)
push!(lilist, frame)
push!(n, 1)
push!(m, 0)
elseif !(key in recursive)
push!(recursive, key)
n[idx] += 1
end
if first
m[idx] += 1
first = false
end
end
end
@assert length(lilist) == length(n) == length(m) == length(lilist_idx)
return (lilist, n, m, totalshots)
end
function flat(io::IO, data::Vector{UInt64}, lidict::Union{LineInfoDict, LineInfoFlatDict}, cols::Int, fmt::ProfileFormat)
lilist, n, m, totalshots = parse_flat(fmt.combine ? StackFrame : UInt64, data, lidict, fmt.C)
if isempty(lilist)
warning_empty()
return
end
if false # optional: drop the "non-interpretable" ones
keep = map(frame -> frame != UNKNOWN && frame.line != 0, lilist)
lilist = lilist[keep]
n = n[keep]
m = m[keep]
end
filenamemap = Dict{Symbol,String}()
print_flat(io, lilist, n, m, cols, filenamemap, fmt)
Base.println(io, "Total snapshots: ", totalshots)
nothing
end
function print_flat(io::IO, lilist::Vector{StackFrame},
n::Vector{Int}, m::Vector{Int},
cols::Int, filenamemap::Dict{Symbol,String},
fmt::ProfileFormat)
if fmt.sortedby === :count
p = sortperm(n)
elseif fmt.sortedby === :overhead
p = sortperm(m)
else
p = liperm(lilist)
end
lilist = lilist[p]
n = n[p]
m = m[p]
filenames = String[short_path(li.file, filenamemap) for li in lilist]
funcnames = String[string(li.func) for li in lilist]
wcounts = max(6, ndigits(maximum(n)))
wself = max(9, ndigits(maximum(m)))
maxline = 1
maxfile = 6
maxfunc = 10
for i in 1:length(lilist)
li = lilist[i]
maxline = max(maxline, li.line)
maxfunc = max(maxfunc, length(funcnames[i]))
maxfile = max(maxfile, length(filenames[i]))
end
wline = max(5, ndigits(maxline))
ntext = max(20, cols - wcounts - wself - wline - 3)
maxfunc += 25 # for type signatures
if maxfile + maxfunc <= ntext
wfile = maxfile
wfunc = ntext - maxfunc # take the full width (for type sig)
else
wfile = 2*ntext÷5
wfunc = 3*ntext÷5
end
println(io, lpad("Count", wcounts, " "), " ", lpad("Overhead", wself, " "), " ",
rpad("File", wfile, " "), " ", lpad("Line", wline, " "), " Function")
println(io, lpad("=====", wcounts, " "), " ", lpad("========", wself, " "), " ",
rpad("====", wfile, " "), " ", lpad("====", wline, " "), " ========")
for i = 1:length(n)
n[i] < fmt.mincount && continue
li = lilist[i]
Base.print(io, lpad(string(n[i]), wcounts, " "), " ")
Base.print(io, lpad(string(m[i]), wself, " "), " ")
if li == UNKNOWN
if !fmt.combine && li.pointer != 0
Base.print(io, "@0x", string(li.pointer, base=16))
else
Base.print(io, "[any unknown stackframes]")
end
else
file = filenames[i]
isempty(file) && (file = "[unknown file]")
Base.print(io, rpad(rtruncto(file, wfile), wfile, " "), " ")
Base.print(io, lpad(li.line > 0 ? string(li.line) : "?", wline, " "), " ")
fname = funcnames[i]
if !li.from_c && li.linfo !== nothing
fname = sprint(show_spec_linfo, li)
end
isempty(fname) && (fname = "[unknown function]")
Base.print(io, ltruncto(fname, wfunc))
end
println(io)
end
nothing
end
## A tree representation
# Representation of a prefix trie of backtrace counts
mutable struct StackFrameTree{T} # where T <: Union{UInt64, StackFrame}
# content fields:
frame::StackFrame
count::Int # number of frames this appeared in
overhead::Int # number frames where this was the code being executed
flat_count::Int # number of times this frame was in the flattened representation (unlike count, this'll sum to 100% of parent)
max_recur::Int # maximum number of times this frame was the *top* of the recursion in the stack
count_recur::Int # sum of the number of times this frame was the *top* of the recursion in a stack (divide by count to get an average)
down::Dict{T, StackFrameTree{T}}
# construction workers:
recur::Int
builder_key::Vector{UInt64}
builder_value::Vector{StackFrameTree{T}}
up::StackFrameTree{T}
StackFrameTree{T}() where {T} = new(UNKNOWN, 0, 0, 0, 0, 0, Dict{T, StackFrameTree{T}}(), 0, UInt64[], StackFrameTree{T}[])
end
const indent_s = " ╎"^10
const indent_z = collect(eachindex(indent_s))
function indent(depth::Int)
depth < 1 && return ""
depth <= length(indent_z) && return indent_s[1:indent_z[depth]]
div, rem = divrem(depth, length(indent_z))
indent = indent_s^div
rem != 0 && (indent *= SubString(indent_s, 1, indent_z[rem]))
return indent
end
function tree_format(frames::Vector{<:StackFrameTree}, level::Int, cols::Int, maxes, filenamemap::Dict{Symbol,String}, showpointer::Bool)
nindent = min(cols>>1, level)
ndigoverhead = ndigits(maxes.overhead)
ndigcounts = ndigits(maxes.count)
ndigline = ndigits(maximum(frame.frame.line for frame in frames)) + 6
ntext = max(30, cols - ndigoverhead - nindent - ndigcounts - ndigline - 6)
widthfile = 2*ntext÷5 # min 12
widthfunc = 3*ntext÷5 # min 18
strs = Vector{String}(undef, length(frames))
showextra = false
if level > nindent
nextra = level - nindent
nindent -= ndigits(nextra) + 2
showextra = true
end
for i = 1:length(frames)
frame = frames[i]
li = frame.frame
stroverhead = lpad(frame.overhead > 0 ? string(frame.overhead) : "", ndigoverhead, " ")
base = nindent == 0 ? "" : indent(nindent - 1) * " "
if showextra
base = string(base, "+", nextra, " ")
end
strcount = rpad(string(frame.count), ndigcounts, " ")
if li != UNKNOWN
if li.line == li.pointer
strs[i] = string(stroverhead, "╎", base, strcount, " ",
"[unknown function] (pointer: 0x",
string(li.pointer, base = 16, pad = 2*sizeof(Ptr{Cvoid})),
")")
else
if !li.from_c && li.linfo !== nothing
fname = sprint(show_spec_linfo, li)
else
fname = string(li.func)
end
filename = short_path(li.file, filenamemap)
if showpointer
fname = string(
"0x",
string(li.pointer, base = 16, pad = 2*sizeof(Ptr{Cvoid})),
" ",
fname)
end
strs[i] = string(stroverhead, "╎", base, strcount, " ",
rtruncto(filename, widthfile),
":",
li.line == -1 ? "?" : string(li.line),
"; ",
ltruncto(fname, widthfunc))
end
else
strs[i] = string(stroverhead, "╎", base, strcount, " [unknown stackframe]")
end
end
return strs
end
# turn a list of backtraces into a tree (implicitly separated by NULL markers)
function tree!(root::StackFrameTree{T}, all::Vector{UInt64}, lidict::Union{LineInfoFlatDict, LineInfoDict}, C::Bool, recur::Symbol) where {T}
parent = root
tops = Vector{StackFrameTree{T}}()
build = Vector{StackFrameTree{T}}()
startframe = length(all)
for i in startframe:-1:1
ip = all[i]
if ip == 0
# sentinel value indicates the start of a new backtrace
empty!(build)
root.recur = 0
if recur !== :off
# We mark all visited nodes to so we'll only count those branches
# once for each backtrace. Reset that now for the next backtrace.
push!(tops, parent)
for top in tops
while top.recur != 0
top.max_recur < top.recur && (top.max_recur = top.recur)
top.recur = 0
top = top.up
end
end
empty!(tops)
end
let this = parent
while this !== root
this.flat_count += 1
this = this.up
end
end
parent.overhead += 1
parent = root
root.count += 1
startframe = i
else
pushfirst!(build, parent)
if recur === :flat || recur === :flatc
# Rewind the `parent` tree back, if this exact ip was already present *higher* in the current tree
found = false
for j in 1:(startframe - i)
if ip == all[i + j]
if recur === :flat # if not flattening C frames, check that now
frames = lidict[ip]
frame = (frames isa Vector ? frames[1] : frames)
frame.from_c && break # not flattening this frame
end
push!(tops, parent)
parent = build[j]
parent.recur += 1
parent.count_recur += 1
found = true
break
end
end
found && continue
end
builder_key = parent.builder_key
builder_value = parent.builder_value
fastkey = searchsortedfirst(builder_key, ip)
if fastkey < length(builder_key) && builder_key[fastkey] === ip
# jump forward to the end of the inlining chain
# avoiding an extra (slow) lookup of `ip` in `lidict`
# and an extra chain of them in `down`
# note that we may even have this === parent (if we're ignoring this frame ip)
this = builder_value[fastkey]
let this = this
while this !== parent && (recur === :off || this.recur == 0)
this.count += 1
this.recur = 1
this = this.up
end
end
parent = this
continue
end
frames = lidict[ip]
nframes = (frames isa Vector ? length(frames) : 1)
this = parent
# add all the inlining frames
for i = nframes:-1:1
frame = (frames isa Vector ? frames[i] : frames)
!C && frame.from_c && continue
key = (T === UInt64 ? ip : frame)
this = get!(StackFrameTree{T}, parent.down, key)
if recur === :off || this.recur == 0
this.frame = frame
this.up = parent
this.count += 1
this.recur = 1
end
parent = this
end
# record where the end of this chain is for this ip
insert!(builder_key, fastkey, ip)
insert!(builder_value, fastkey, this)
end
end
function cleanup!(node::StackFrameTree)
stack = [node]
while !isempty(stack)
node = pop!(stack)
node.recur = 0
empty!(node.builder_key)
empty!(node.builder_value)
append!(stack, values(node.down))
end
nothing
end
cleanup!(root)
return root
end
function maxstats(root::StackFrameTree)
maxcount = Ref(0)
maxflatcount = Ref(0)
maxoverhead = Ref(0)
maxmaxrecur = Ref(0)
stack = [root]
while !isempty(stack)
node = pop!(stack)
maxcount[] = max(maxcount[], node.count)
maxoverhead[] = max(maxoverhead[], node.overhead)
maxflatcount[] = max(maxflatcount[], node.flat_count)
maxmaxrecur[] = max(maxmaxrecur[], node.max_recur)
append!(stack, values(node.down))
end
return (count=maxcount[], count_flat=maxflatcount[], overhead=maxoverhead[], max_recur=maxmaxrecur[])
end
# Print the stack frame tree starting at a particular root. Uses a worklist to
# avoid stack overflows.
function print_tree(io::IO, bt::StackFrameTree{T}, cols::Int, fmt::ProfileFormat) where T
maxes = maxstats(bt)
filenamemap = Dict{Symbol,String}()
worklist = [(bt, 0, 0, "")]
println(io, "Overhead ╎ [+additional indent] Count File:Line; Function")
println(io, "=========================================================")
while !isempty(worklist)
(bt, level, noisefloor, str) = popfirst!(worklist)
isempty(str) || println(io, str)
level > fmt.maxdepth && continue
isempty(bt.down) && continue
# Order the line information
nexts = collect(values(bt.down))
# Generate the string for each line
strs = tree_format(nexts, level, cols, maxes, filenamemap, T === UInt64)
# Recurse to the next level
if fmt.sortedby === :count
counts = collect(frame.count for frame in nexts)
p = sortperm(counts)
elseif fmt.sortedby === :overhead
m = collect(frame.overhead for frame in nexts)
p = sortperm(m)
elseif fmt.sortedby === :flat_count
m = collect(frame.flat_count for frame in nexts)
p = sortperm(m)
else
lilist = collect(frame.frame for frame in nexts)
p = liperm(lilist)
end
for i in reverse(p)
down = nexts[i]
count = down.count
count < fmt.mincount && continue
count < noisefloor && continue
str = strs[i]
noisefloor_down = fmt.noisefloor > 0 ? floor(Int, fmt.noisefloor * sqrt(count)) : 0
pushfirst!(worklist, (down, level + 1, noisefloor_down, str))
end
end
end
function tree(io::IO, data::Vector{UInt64}, lidict::Union{LineInfoFlatDict, LineInfoDict}, cols::Int, fmt::ProfileFormat)
if fmt.combine
root = tree!(StackFrameTree{StackFrame}(), data, lidict, fmt.C, fmt.recur)
else
root = tree!(StackFrameTree{UInt64}(), data, lidict, fmt.C, fmt.recur)
end
if isempty(root.down)
warning_empty()
return
end
print_tree(io, root, cols, fmt)
Base.println(io, "Total snapshots: ", root.count)
nothing
end
function callersf(matchfunc::Function, bt::Vector, lidict::LineInfoFlatDict)
counts = Dict{StackFrame, Int}()
lastmatched = false
for id in bt
if id == 0
lastmatched = false
continue
end
li = lidict[id]
if lastmatched
if haskey(counts, li)
counts[li] += 1
else
counts[li] = 1
end
end
lastmatched = matchfunc(li)
end
k = collect(keys(counts))
v = collect(values(counts))
p = sortperm(v, rev=true)
return [(v[i], k[i]) for i in p]
end
# Utilities
function rtruncto(str::String, w::Int)
if length(str) <= w
return str
else
return string("...", str[prevind(str, end, w-4):end])
end
end
function ltruncto(str::String, w::Int)
if length(str) <= w
return str
else
return string(str[1:nextind(str, 1, w-4)], "...")
end
end
truncto(str::Symbol, w::Int) = truncto(string(str), w)
# Order alphabetically (file, function) and then by line number
function liperm(lilist::Vector{StackFrame})
function lt(a::StackFrame, b::StackFrame)
a == UNKNOWN && return false
b == UNKNOWN && return true
fcmp = cmp(a.file, b.file)
fcmp < 0 && return true
fcmp > 0 && return false
fcmp = cmp(a.func, b.func)
fcmp < 0 && return true
fcmp > 0 && return false
fcmp = cmp(a.line, b.line)
fcmp < 0 && return true
return false
end
return sortperm(lilist, lt = lt)
end
warning_empty() = @warn """
There were no samples collected. Run your program longer (perhaps by
running it multiple times), or adjust the delay between samples with
`Profile.init()`."""
end # module