Mercurial > hg
view mercurial/statprof.py @ 51684:20e2a20674dc
convert: drop a duplicate implementation of `dateutil.makedate()`
I noticed this because the signature generated by pytype recently changed to be
less specific. When the method was introduced back in 337d728e644f,
`util.makedate()` didn't take an optional timestamp arg. But now it does, and
the methods are the same (except the `dateutil` version validates that the
timestamp isn't a negative value). I left the old method in place in case
anyone has custom convert code that monkey patches it.
author | Matt Harbison <matt_harbison@yahoo.com> |
---|---|
date | Thu, 11 Jul 2024 14:46:00 -0400 |
parents | 933551630b0d |
children | 99632adff795 460e80488cf0 |
line wrap: on
line source
## statprof.py ## Copyright (C) 2012 Bryan O'Sullivan <bos@serpentine.com> ## 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: +1-617-542-5942 ## 59 Temple Place - Suite 330 Fax: +1-617-542-2652 ## Boston, MA 02111-1307, USA gnu@gnu.org """ 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 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 or -1, 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 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 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 or -1, 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 or -1, 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 or -1, 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 or -1, ), 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())