statprof: with Python 3.12, lineno is (more) often None

test-profile.t failed with errors like:
  TypeError: %d format: a real number is required, not NoneType

statprof.py already handled None values as -1 in some cases. Do the same in
more cases.

mercurial/statprof.py

@@ -1,1090 +1,1094 b''
 ## statprof.py
 ## Copyright (C) 2012 Bryan O'Sullivan <[e-mail]>
 ## Copyright (C) 2011 Alex Fraser <alex at phatcore dot com>
 ## Copyright (C) 2004,2005 Andy Wingo <wingo at pobox dot com>
 ## Copyright (C) 2001 Rob Browning <rlb at defaultvalue dot org>
 
 ## This library is free software; you can redistribute it and/or
 ## modify it under the terms of the GNU Lesser General Public
 ## License as published by the Free Software Foundation; either
 ## version 2.1 of the License, or (at your option) any later version.
 ##
 ## This library is distributed in the hope that it will be useful,
 ## but WITHOUT ANY WARRANTY; without even the implied warranty of
 ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 ## Lesser General Public License for more details.
 ##
 ## You should have received a copy of the GNU Lesser General Public
 ## License along with this program; if not, contact:
 ##
 ## Free Software Foundation           Voice:  [phone]
 ## 59 Temple Place - Suite 330        Fax:    [phone]
 ## Boston, MA  02111-1307,  USA       [e-mail]
 
 """
 statprof is intended to be a fairly simple statistical profiler for
 python. It was ported directly from a statistical profiler for guile,
 also named statprof, available from guile-lib [0].
 
 [0] http://wingolog.org/software/guile-lib/statprof/
 
 To start profiling, call statprof.start():
 >>> start()
 
 Then run whatever it is that you want to profile, for example:
 >>> import test.pystone; test.pystone.pystones()
 
 Then stop the profiling and print out the results:
 >>> stop()
 >>> display()
   %   cumulative      self
  time    seconds   seconds  name
  26.72      1.40      0.37  pystone.py:79:Proc0
  13.79      0.56      0.19  pystone.py:133:Proc1
  13.79      0.19      0.19  pystone.py:208:Proc8
  10.34      0.16      0.14  pystone.py:229:Func2
   6.90      0.10      0.10  pystone.py:45:__init__
   4.31      0.16      0.06  pystone.py:53:copy
     ...
 
 All of the numerical data is statistically approximate. In the
 following column descriptions, and in all of statprof, "time" refers
 to execution time (both user and system), not wall clock time.
 
 % time
     The percent of the time spent inside the procedure itself (not
     counting children).
 
 cumulative seconds
     The total number of seconds spent in the procedure, including
     children.
 
 self seconds
     The total number of seconds spent in the procedure itself (not
     counting children).
 
 name
     The name of the procedure.
 
 By default statprof keeps the data collected from previous runs. If you
 want to clear the collected data, call reset():
 >>> reset()
 
 reset() can also be used to change the sampling frequency from the
 default of 1000 Hz. For example, to tell statprof to sample 50 times a
 second:
 >>> reset(50)
 
 This means that statprof will sample the call stack after every 1/50 of
 a second of user + system time spent running on behalf of the python
 process. When your process is idle (for example, blocking in a read(),
 as is the case at the listener), the clock does not advance. For this
 reason statprof is not currently not suitable for profiling io-bound
 operations.
 
 The profiler uses the hash of the code object itself to identify the
 procedures, so it won't confuse different procedures with the same name.
 They will show up as two different rows in the output.
 
 Right now the profiler is quite simplistic.  I cannot provide
 call-graphs or other higher level information.  What you see in the
 table is pretty much all there is. Patches are welcome :-)
 
 
 Threading
 ---------
 
 Because signals only get delivered to the main thread in Python,
 statprof only profiles the main thread. However because the time
 reporting function uses per-process timers, the results can be
 significantly off if other threads' work patterns are not similar to the
 main thread's work patterns.
 """
 # no-check-code
 
 import collections
 import contextlib
 import getopt
 import inspect
 import json
 import os
 import signal
 import sys
 import threading
 import time
 
 from .pycompat import open
 from . import (
     encoding,
     pycompat,
 )
 
 defaultdict = collections.defaultdict
 contextmanager = contextlib.contextmanager
 
 __all__ = [b'start', b'stop', b'reset', b'display', b'profile']
 
 skips = {
     "util.py:check",
     "extensions.py:closure",
     "color.py:colorcmd",
     "dispatch.py:checkargs",
     "dispatch.py:<lambda>",
     "dispatch.py:_runcatch",
     "dispatch.py:_dispatch",
     "dispatch.py:_runcommand",
     "pager.py:pagecmd",
     "dispatch.py:run",
     "dispatch.py:dispatch",
     "dispatch.py:runcommand",
     "hg.py:<module>",
     "evolve.py:warnobserrors",
 }
 
 ###########################################################################
 ## Utils
 
 
 def clock():
     times = os.times()
     return (times[0] + times[1], times[4])
 
 
 ###########################################################################
 ## Collection data structures
 
 
 class ProfileState:
     def __init__(self, frequency=None):
         self.reset(frequency)
         self.track = b'cpu'
 
     def reset(self, frequency=None):
         # total so far
         self.accumulated_time = (0.0, 0.0)
         # start_time when timer is active
         self.last_start_time = None
         # a float
         if frequency:
             self.sample_interval = 1.0 / frequency
         elif not pycompat.hasattr(self, 'sample_interval'):
             # default to 1000 Hz
             self.sample_interval = 1.0 / 1000.0
         else:
             # leave the frequency as it was
             pass
         self.remaining_prof_time = None
         # for user start/stop nesting
         self.profile_level = 0
 
         self.samples = []
 
     def accumulate_time(self, stop_time):
         increment = (
             stop_time[0] - self.last_start_time[0],
             stop_time[1] - self.last_start_time[1],
         )
         self.accumulated_time = (
             self.accumulated_time[0] + increment[0],
             self.accumulated_time[1] + increment[1],
         )
 
     def seconds_per_sample(self):
         return self.accumulated_time[self.timeidx] / len(self.samples)
 
     @property
     def timeidx(self):
         if self.track == b'real':
             return 1
         return 0
 
 
 state = ProfileState()
 
 
 class CodeSite:
     cache = {}
 
     __slots__ = ('path', 'lineno', 'function', 'source')
 
     def __init__(self, path, lineno, function):
         assert isinstance(path, bytes)
         self.path = path
         self.lineno = lineno
         assert isinstance(function, bytes)
         self.function = function
         self.source = None
 
     def __eq__(self, other):
         try:
             return self.lineno == other.lineno and self.path == other.path
         except:
             return False
 
     def __hash__(self):
         return hash((self.lineno, self.path))
 
     @classmethod
     def get(cls, path, lineno, function):
         k = (path, lineno)
         try:
             return cls.cache[k]
         except KeyError:
             v = cls(path, lineno, function)
             cls.cache[k] = v
             return v
 
     def getsource(self, length):
         if self.source is None:
             try:
                 lineno = self.lineno - 1  # lineno can be None
                 with open(self.path, b'rb') as fp:
                     for i, line in enumerate(fp):
                         if i == lineno:
                             self.source = line.strip()
                             break
             except:
                 pass
             if self.source is None:
                 self.source = b''
 
         source = self.source
         if len(source) > length:
             source = source[: (length - 3)] + b"..."
         return source
 
     def filename(self):
         return os.path.basename(self.path)
 
     def skipname(self):
         return '%s:%s' % (self.filename(), self.function)
 
 
 class Sample:
     __slots__ = ('stack', 'time')
 
     def __init__(self, stack, time):
         self.stack = stack
         self.time = time
 
     @classmethod
     def from_frame(cls, frame, time):
         stack = []
 
         while frame:
             stack.append(
                 CodeSite.get(
                     pycompat.sysbytes(frame.f_code.co_filename),
                     frame.f_lineno,
                     pycompat.sysbytes(frame.f_code.co_name),
                 )
             )
             frame = frame.f_back
 
         return Sample(stack, time)
 
 
 ###########################################################################
 ## SIGPROF handler
 
 
 def profile_signal_handler(signum, frame):
     if state.profile_level > 0:
         now = clock()
         state.accumulate_time(now)
 
         timestamp = state.accumulated_time[state.timeidx]
         state.samples.append(Sample.from_frame(frame, timestamp))
 
         signal.setitimer(signal.ITIMER_PROF, state.sample_interval, 0.0)
         state.last_start_time = now
 
 
 stopthread = threading.Event()
 
 
 def samplerthread(tid):
     while not stopthread.is_set():
         now = clock()
         state.accumulate_time(now)
 
         frame = sys._current_frames()[tid]
 
         timestamp = state.accumulated_time[state.timeidx]
         state.samples.append(Sample.from_frame(frame, timestamp))
 
         state.last_start_time = now
         time.sleep(state.sample_interval)
 
     stopthread.clear()
 
 
 ###########################################################################
 ## Profiling API
 
 
 def is_active():
     return state.profile_level > 0
 
 
 lastmechanism = None
 
 
 def start(mechanism=b'thread', track=b'cpu'):
     '''Install the profiling signal handler, and start profiling.'''
     state.track = track  # note: nesting different mode won't work
     state.profile_level += 1
     if state.profile_level == 1:
         state.last_start_time = clock()
         rpt = state.remaining_prof_time
         state.remaining_prof_time = None
 
         global lastmechanism
         lastmechanism = mechanism
 
         if mechanism == b'signal':
             signal.signal(signal.SIGPROF, profile_signal_handler)
             signal.setitimer(
                 signal.ITIMER_PROF, rpt or state.sample_interval, 0.0
             )
         elif mechanism == b'thread':
             frame = inspect.currentframe()
             tid = [k for k, f in sys._current_frames().items() if f == frame][0]
             state.thread = threading.Thread(
                 target=samplerthread, args=(tid,), name="samplerthread"
             )
             state.thread.start()
 
 
 def stop():
     '''Stop profiling, and uninstall the profiling signal handler.'''
     state.profile_level -= 1
     if state.profile_level == 0:
         if lastmechanism == b'signal':
             rpt = signal.setitimer(signal.ITIMER_PROF, 0.0, 0.0)
             signal.signal(signal.SIGPROF, signal.SIG_IGN)
             state.remaining_prof_time = rpt[0]
         elif lastmechanism == b'thread':
             stopthread.set()
             state.thread.join()
 
         state.accumulate_time(clock())
         state.last_start_time = None
         statprofpath = encoding.environ.get(b'STATPROF_DEST')
         if statprofpath:
             save_data(statprofpath)
 
     return state
 
 
 def save_data(path):
     with open(path, b'w+') as file:
         file.write(b"%f %f\n" % state.accumulated_time)
         for sample in state.samples:
             time = sample.time
             stack = sample.stack
             sites = [
                 b'\1'.join([s.path, b'%d' % s.lineno, s.function])
                 for s in stack
             ]
             file.write(b"%d\0%s\n" % (time, b'\0'.join(sites)))
 
 
 def load_data(path):
     lines = open(path, b'rb').read().splitlines()
 
     state.accumulated_time = [float(value) for value in lines[0].split()]
     state.samples = []
     for line in lines[1:]:
         parts = line.split(b'\0')
         time = float(parts[0])
         rawsites = parts[1:]
         sites = []
         for rawsite in rawsites:
             siteparts = rawsite.split(b'\1')
             sites.append(
                 CodeSite.get(siteparts[0], int(siteparts[1]), siteparts[2])
             )
 
         state.samples.append(Sample(sites, time))
 
 
 def reset(frequency=None):
     """Clear out the state of the profiler.  Do not call while the
     profiler is running.
 
     The optional frequency argument specifies the number of samples to
     collect per second."""
     assert state.profile_level == 0, b"Can't reset() while statprof is running"
     CodeSite.cache.clear()
     state.reset(frequency)
 
 
 @contextmanager
 def profile():
     start()
     try:
         yield
     finally:
         stop()
         display()
 
 
 ###########################################################################
 ## Reporting API
 
 
 class SiteStats:
     def __init__(self, site):
         self.site = site
         self.selfcount = 0
         self.totalcount = 0
 
     def addself(self):
         self.selfcount += 1
 
     def addtotal(self):
         self.totalcount += 1
 
     def selfpercent(self):
         return self.selfcount / len(state.samples) * 100
 
     def totalpercent(self):
         return self.totalcount / len(state.samples) * 100
 
     def selfseconds(self):
         return self.selfcount * state.seconds_per_sample()
 
     def totalseconds(self):
         return self.totalcount * state.seconds_per_sample()
 
     @classmethod
     def buildstats(cls, samples):
         stats = {}
 
         for sample in samples:
             for i, site in enumerate(sample.stack):
                 sitestat = stats.get(site)
                 if not sitestat:
                     sitestat = SiteStats(site)
                     stats[site] = sitestat
 
                 sitestat.addtotal()
 
                 if i == 0:
                     sitestat.addself()
 
         return [s for s in stats.values()]
 
 
 class DisplayFormats:
     ByLine = 0
     ByMethod = 1
     AboutMethod = 2
     Hotpath = 3
     FlameGraph = 4
     Json = 5
     Chrome = 6
 
 
 def display(fp=None, format=3, data=None, **kwargs):
     '''Print statistics, either to stdout or the given file object.'''
     if data is None:
         data = state
 
     if fp is None:
         from .utils import procutil
 
         fp = procutil.stdout
     if len(data.samples) == 0:
         fp.write(b'No samples recorded.\n')
         return
 
     if format == DisplayFormats.ByLine:
         display_by_line(data, fp)
     elif format == DisplayFormats.ByMethod:
         display_by_method(data, fp)
     elif format == DisplayFormats.AboutMethod:
         display_about_method(data, fp, **kwargs)
     elif format == DisplayFormats.Hotpath:
         display_hotpath(data, fp, **kwargs)
     elif format == DisplayFormats.FlameGraph:
         write_to_flame(data, fp, **kwargs)
     elif format == DisplayFormats.Json:
         write_to_json(data, fp)
     elif format == DisplayFormats.Chrome:
         write_to_chrome(data, fp, **kwargs)
     else:
         raise Exception("Invalid display format")
 
     if format not in (DisplayFormats.Json, DisplayFormats.Chrome):
         fp.write(b'---\n')
         fp.write(b'Sample count: %d\n' % len(data.samples))
         fp.write(b'Total time: %f seconds (%f wall)\n' % data.accumulated_time)
 
 
 def display_by_line(data, fp):
     """Print the profiler data with each sample line represented
     as one row in a table.  Sorted by self-time per line."""
     stats = SiteStats.buildstats(data.samples)
     stats.sort(reverse=True, key=lambda x: x.selfseconds())
 
     fp.write(
         b'%5.5s %10.10s   %7.7s  %-8.8s\n'
         % (b'%  ', b'cumulative', b'self', b'')
     )
     fp.write(
         b'%5.5s  %9.9s  %8.8s  %-8.8s\n'
         % (b"time", b"seconds", b"seconds", b"name")
     )
 
     for stat in stats:
         site = stat.site
-        sitelabel = b'%s:%d:%s' % (site.filename(), site.lineno, site.function)
+        sitelabel = b'%s:%d:%s' % (
+            site.filename(),
+            site.lineno or -1,
+            site.function,
+        )
         fp.write(
             b'%6.2f %9.2f %9.2f  %s\n'
             % (
                 stat.selfpercent(),
                 stat.totalseconds(),
                 stat.selfseconds(),
                 sitelabel,
             )
         )
 
 
 def display_by_method(data, fp):
     """Print the profiler data with each sample function represented
     as one row in a table.  Important lines within that function are
     output as nested rows.  Sorted by self-time per line."""
     fp.write(
         b'%5.5s %10.10s   %7.7s  %-8.8s\n'
         % (b'%  ', b'cumulative', b'self', b'')
     )
     fp.write(
         b'%5.5s  %9.9s  %8.8s  %-8.8s\n'
         % (b"time", b"seconds", b"seconds", b"name")
     )
 
     stats = SiteStats.buildstats(data.samples)
 
     grouped = defaultdict(list)
     for stat in stats:
         grouped[stat.site.filename() + b":" + stat.site.function].append(stat)
 
     # compute sums for each function
     functiondata = []
     for fname, sitestats in grouped.items():
         total_cum_sec = 0
         total_self_sec = 0
         total_percent = 0
         for stat in sitestats:
             total_cum_sec += stat.totalseconds()
             total_self_sec += stat.selfseconds()
             total_percent += stat.selfpercent()
 
         functiondata.append(
             (fname, total_cum_sec, total_self_sec, total_percent, sitestats)
         )
 
     # sort by total self sec
     functiondata.sort(reverse=True, key=lambda x: x[2])
 
     for function in functiondata:
         if function[3] < 0.05:
             continue
         fp.write(
             b'%6.2f %9.2f %9.2f  %s\n'
             % (
                 function[3],  # total percent
                 function[1],  # total cum sec
                 function[2],  # total self sec
                 function[0],
             )
         )  # file:function
 
         function[4].sort(reverse=True, key=lambda i: i.selfseconds())
         for stat in function[4]:
             # only show line numbers for significant locations (>1% time spent)
             if stat.selfpercent() > 1:
                 source = stat.site.getsource(25)
                 if not isinstance(source, bytes):
                     source = pycompat.bytestr(source)
 
                 stattuple = (
                     stat.selfpercent(),
                     stat.selfseconds(),
-                    stat.site.lineno,
+                    stat.site.lineno or -1,
                     source,
                 )
 
                 fp.write(b'%33.0f%% %6.2f   line %d: %s\n' % stattuple)
 
 
 def display_about_method(data, fp, function=None, **kwargs):
     if function is None:
         raise Exception("Invalid function")
 
     filename = None
     if b':' in function:
         filename, function = function.split(b':')
 
     relevant_samples = 0
     parents = {}
     children = {}
 
     for sample in data.samples:
         for i, site in enumerate(sample.stack):
             if site.function == function and (
                 not filename or site.filename() == filename
             ):
                 relevant_samples += 1
                 if i != len(sample.stack) - 1:
                     parent = sample.stack[i + 1]
                     if parent in parents:
                         parents[parent] = parents[parent] + 1
                     else:
                         parents[parent] = 1
 
                 if site in children:
                     children[site] = children[site] + 1
                 else:
                     children[site] = 1
 
     parents = [(parent, count) for parent, count in parents.items()]
     parents.sort(reverse=True, key=lambda x: x[1])
     for parent, count in parents:
         fp.write(
             b'%6.2f%%   %s:%s   line %s: %s\n'
             % (
                 count / relevant_samples * 100,
                 pycompat.fsencode(parent.filename()),
                 pycompat.sysbytes(parent.function),
                 parent.lineno,
                 pycompat.sysbytes(parent.getsource(50)),
             )
         )
 
     stats = SiteStats.buildstats(data.samples)
     stats = [
         s
         for s in stats
         if s.site.function == function
         and (not filename or s.site.filename() == filename)
     ]
 
     total_cum_sec = 0
     total_self_sec = 0
     total_self_percent = 0
     total_cum_percent = 0
     for stat in stats:
         total_cum_sec += stat.totalseconds()
         total_self_sec += stat.selfseconds()
         total_self_percent += stat.selfpercent()
         total_cum_percent += stat.totalpercent()
 
     fp.write(
         b'\n    %s:%s    Total: %0.2fs (%0.2f%%)    Self: %0.2fs (%0.2f%%)\n\n'
         % (
             pycompat.sysbytes(filename or b'___'),
             pycompat.sysbytes(function),
             total_cum_sec,
             total_cum_percent,
             total_self_sec,
             total_self_percent,
         )
     )
 
     children = [(child, count) for child, count in children.items()]
     children.sort(reverse=True, key=lambda x: x[1])
     for child, count in children:
         fp.write(
             b'        %6.2f%%   line %s: %s\n'
             % (
                 count / relevant_samples * 100,
                 child.lineno,
                 pycompat.sysbytes(child.getsource(50)),
             )
         )
 
 
 def display_hotpath(data, fp, limit=0.05, **kwargs):
     class HotNode:
         def __init__(self, site):
             self.site = site
             self.count = 0
             self.children = {}
 
         def add(self, stack, time):
             self.count += time
             site = stack[0]
             child = self.children.get(site)
             if not child:
                 child = HotNode(site)
                 self.children[site] = child
 
             if len(stack) > 1:
                 i = 1
                 # Skip boiler plate parts of the stack
                 while i < len(stack) and stack[i].skipname() in skips:
                     i += 1
                 if i < len(stack):
                     child.add(stack[i:], time)
             else:
                 # Normally this is done by the .add() calls
                 child.count += time
 
     root = HotNode(None)
     lasttime = data.samples[0].time
     for sample in data.samples:
         root.add(sample.stack[::-1], sample.time - lasttime)
         lasttime = sample.time
     showtime = kwargs.get('showtime', True)
 
     def _write(node, depth, multiple_siblings):
         site = node.site
         visiblechildren = [
             c for c in node.children.values() if c.count >= (limit * root.count)
         ]
         if site:
             indent = depth * 2 - 1
             filename = (site.filename() + b':').ljust(15)
             function = site.function
 
             # lots of string formatting
             listpattern = (
                 b''.ljust(indent)
                 + (b'\\' if multiple_siblings else b'|')
                 + b' %4.1f%%'
                 + (b' %5.2fs' % node.count if showtime else b'')
                 + b'  %s %s'
             )
             liststring = listpattern % (
                 node.count / root.count * 100,
                 filename,
                 function,
             )
             # 4 to account for the word 'line'
             spacing_len = max(4, 55 - len(liststring))
             prefix = b''
             if spacing_len == 4:
                 prefix = b', '
 
             codepattern = b'%s%s %d: %s%s'
             codestring = codepattern % (
                 prefix,
                 b'line'.rjust(spacing_len),
                 site.lineno if site.lineno is not None else -1,
                 b''.ljust(max(0, 4 - len(str(site.lineno)))),
                 site.getsource(30),
             )
 
             finalstring = liststring + codestring
             childrensamples = sum([c.count for c in node.children.values()])
             # Make frames that performed more than 10% of the operation red
             if node.count - childrensamples > (0.1 * root.count):
                 finalstring = b'\033[91m' + finalstring + b'\033[0m'
             # Make frames that didn't actually perform work dark grey
             elif node.count - childrensamples == 0:
                 finalstring = b'\033[90m' + finalstring + b'\033[0m'
             fp.write(finalstring + b'\n')
 
         newdepth = depth
         if len(visiblechildren) > 1 or multiple_siblings:
             newdepth += 1
 
         visiblechildren.sort(reverse=True, key=lambda x: x.count)
         for child in visiblechildren:
             _write(child, newdepth, len(visiblechildren) > 1)
 
     if root.count > 0:
         _write(root, 0, False)
 
 
 def write_to_flame(data, fp, scriptpath=None, outputfile=None, **kwargs):
     if scriptpath is None:
         scriptpath = encoding.environ[b'HOME'] + b'/flamegraph.pl'
     if not os.path.exists(scriptpath):
         fp.write(b'error: missing %s\n' % scriptpath)
         fp.write(b'get it here: https://github.com/brendangregg/FlameGraph\n')
         return
 
     lines = {}
     for sample in data.samples:
         sites = [s.function for s in sample.stack]
         sites.reverse()
         line = b';'.join(sites)
         if line in lines:
             lines[line] = lines[line] + 1
         else:
             lines[line] = 1
 
     fd, path = pycompat.mkstemp()
 
     with open(path, b"w+") as file:
         for line, count in lines.items():
             file.write(b"%s %d\n" % (line, count))
 
     if outputfile is None:
         outputfile = b'~/flamegraph.svg'
 
     os.system(b"perl ~/flamegraph.pl %s > %s" % (path, outputfile))
     fp.write(b'Written to %s\n' % outputfile)
 
 
 _pathcache = {}
 
 
 def simplifypath(path):
     """Attempt to make the path to a Python module easier to read by
     removing whatever part of the Python search path it was found
     on."""
 
     if path in _pathcache:
         return _pathcache[path]
     hgpath = encoding.__file__.rsplit(os.sep, 2)[0]
     for p in [hgpath] + sys.path:
         prefix = p + os.sep
         if path.startswith(prefix):
             path = path[len(prefix) :]
             break
     _pathcache[path] = path
     return path
 
 
 def write_to_json(data, fp):
     samples = []
 
     for sample in data.samples:
         stack = []
 
         for frame in sample.stack:
             stack.append(
                 (
                     pycompat.sysstr(frame.path),
                     frame.lineno,
                     pycompat.sysstr(frame.function),
                 )
             )
 
         samples.append((sample.time, stack))
 
     data = json.dumps(samples)
     if not isinstance(data, bytes):
         data = data.encode('utf-8')
 
     fp.write(data)
 
 
 def write_to_chrome(data, fp, minthreshold=0.005, maxthreshold=0.999):
     samples = []
     laststack = collections.deque()
     lastseen = collections.deque()
 
     # The Chrome tracing format allows us to use a compact stack
     # representation to save space. It's fiddly but worth it.
     # We maintain a bijection between stack and ID.
     stack2id = {}
     id2stack = []  # will eventually be rendered
 
     def stackid(stack):
         if not stack:
             return
         if stack in stack2id:
             return stack2id[stack]
         parent = stackid(stack[1:])
         myid = len(stack2id)
         stack2id[stack] = myid
         id2stack.append(dict(category=stack[0][0], name='%s %s' % stack[0]))
         if parent is not None:
             id2stack[-1].update(parent=parent)
         return myid
 
     # The sampling profiler can sample multiple times without
     # advancing the clock, potentially causing the Chrome trace viewer
     # to render single-pixel columns that we cannot zoom in on.  We
     # work around this by pretending that zero-duration samples are a
     # millisecond in length.
 
     clamp = 0.001
 
     # We provide knobs that by default attempt to filter out stack
     # frames that are too noisy:
     #
     # * A few take almost all execution time. These are usually boring
     #   setup functions, giving a stack that is deep but uninformative.
     #
     # * Numerous samples take almost no time, but introduce lots of
     #   noisy, oft-deep "spines" into a rendered profile.
 
     blacklist = set()
     totaltime = data.samples[-1].time - data.samples[0].time
     minthreshold = totaltime * minthreshold
     maxthreshold = max(totaltime * maxthreshold, clamp)
 
     def poplast():
         oldsid = stackid(tuple(laststack))
         oldcat, oldfunc = laststack.popleft()
         oldtime, oldidx = lastseen.popleft()
         duration = sample.time - oldtime
         if minthreshold <= duration <= maxthreshold:
             # ensure no zero-duration events
             sampletime = max(oldtime + clamp, sample.time)
             samples.append(
                 dict(
                     ph='E',
                     name=oldfunc,
                     cat=oldcat,
                     sf=oldsid,
                     ts=sampletime * 1e6,
                     pid=0,
                 )
             )
         else:
             blacklist.add(oldidx)
 
     # Much fiddling to synthesize correctly(ish) nested begin/end
     # events given only stack snapshots.
 
     for sample in data.samples:
         stack = tuple(
             (
                 (
                     '%s:%d'
                     % (simplifypath(pycompat.sysstr(frame.path)), frame.lineno),
                     pycompat.sysstr(frame.function),
                 )
                 for frame in sample.stack
             )
         )
         qstack = collections.deque(stack)
         if laststack == qstack:
             continue
         while laststack and qstack and laststack[-1] == qstack[-1]:
             laststack.pop()
             qstack.pop()
         while laststack:
             poplast()
         for f in reversed(qstack):
             lastseen.appendleft((sample.time, len(samples)))
             laststack.appendleft(f)
             path, name = f
             sid = stackid(tuple(laststack))
             samples.append(
                 dict(
                     ph='B',
                     name=name,
                     cat=path,
                     ts=sample.time * 1e6,
                     sf=sid,
                     pid=0,
                 )
             )
         laststack = collections.deque(stack)
     while laststack:
         poplast()
     events = [
         sample for idx, sample in enumerate(samples) if idx not in blacklist
     ]
     frames = collections.OrderedDict(
         (str(k), v) for (k, v) in enumerate(id2stack)
     )
     data = json.dumps(dict(traceEvents=events, stackFrames=frames), indent=1)
     if not isinstance(data, bytes):
         data = data.encode('utf-8')
     fp.write(data)
     fp.write(b'\n')
 
 
 def printusage():
     print(
         r"""
 The statprof command line allows you to inspect the last profile's results in
 the following forms:
 
 usage:
     hotpath [-l --limit percent]
         Shows a graph of calls with the percent of time each takes.
         Red calls take over 10%% of the total time themselves.
     lines
         Shows the actual sampled lines.
     functions
         Shows the samples grouped by function.
     function [filename:]functionname
         Shows the callers and callees of a particular function.
     flame [-s --script-path] [-o --output-file path]
         Writes out a flamegraph to output-file (defaults to ~/flamegraph.svg)
         Requires that ~/flamegraph.pl exist.
         (Specify alternate script path with --script-path.)"""
     )
 
 
 def main(argv=None):
     if argv is None:
         argv = sys.argv
 
     if len(argv) == 1:
         printusage()
         return 0
 
     displayargs = {}
 
     optstart = 2
     displayargs[b'function'] = None
     if argv[1] == 'hotpath':
         displayargs[b'format'] = DisplayFormats.Hotpath
     elif argv[1] == 'lines':
         displayargs[b'format'] = DisplayFormats.ByLine
     elif argv[1] == 'functions':
         displayargs[b'format'] = DisplayFormats.ByMethod
     elif argv[1] == 'function':
         displayargs[b'format'] = DisplayFormats.AboutMethod
         displayargs[b'function'] = argv[2]
         optstart = 3
     elif argv[1] == 'flame':
         displayargs[b'format'] = DisplayFormats.FlameGraph
     else:
         printusage()
         return 0
 
     # process options
     try:
         opts, args = pycompat.getoptb(
             pycompat.sysargv[optstart:],
             b"hl:f:o:p:",
             [b"help", b"limit=", b"file=", b"output-file=", b"script-path="],
         )
     except getopt.error as msg:
         print(msg)
         printusage()
         return 2
 
     displayargs[b'limit'] = 0.05
     path = None
     for o, value in opts:
         if o in ("-l", "--limit"):
             displayargs[b'limit'] = float(value)
         elif o in ("-f", "--file"):
             path = value
         elif o in ("-o", "--output-file"):
             displayargs[b'outputfile'] = value
         elif o in ("-p", "--script-path"):
             displayargs[b'scriptpath'] = value
         elif o in ("-h", "help"):
             printusage()
             return 0
         else:
             assert False, "unhandled option %s" % o
 
     if not path:
         print('must specify --file to load')
         return 1
 
     load_data(path=path)
 
     display(**pycompat.strkwargs(displayargs))
 
     return 0
 
 
 if __name__ == "__main__":
     sys.exit(main())