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199 lines
6.4 KiB
Python
199 lines
6.4 KiB
Python
#! /usr/bin/env python
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"""Python interface for the 'lsprof' profiler.
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Compatible with the 'profile' module.
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"""
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__all__ = ["run", "runctx", "help", "Profile"]
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import _lsprof
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# ____________________________________________________________
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# Simple interface
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def run(statement, filename=None, sort=-1):
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"""Run statement under profiler optionally saving results in filename
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This function takes a single argument that can be passed to the
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"exec" statement, and an optional file name. In all cases this
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routine attempts to "exec" its first argument and gather profiling
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statistics from the execution. If no file name is present, then this
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function automatically prints a simple profiling report, sorted by the
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standard name string (file/line/function-name) that is presented in
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each line.
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"""
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prof = Profile()
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result = None
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try:
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try:
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prof = prof.run(statement)
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except SystemExit:
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pass
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finally:
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if filename is not None:
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prof.dump_stats(filename)
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else:
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result = prof.print_stats(sort)
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return result
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def runctx(statement, globals, locals, filename=None, sort=-1):
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"""Run statement under profiler, supplying your own globals and locals,
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optionally saving results in filename.
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statement and filename have the same semantics as profile.run
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"""
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prof = Profile()
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result = None
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try:
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try:
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prof = prof.runctx(statement, globals, locals)
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except SystemExit:
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pass
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finally:
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if filename is not None:
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prof.dump_stats(filename)
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else:
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result = prof.print_stats(sort)
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return result
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# Backwards compatibility.
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def help():
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print "Documentation for the profile/cProfile modules can be found "
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print "in the Python Library Reference, section 'The Python Profiler'."
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# ____________________________________________________________
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class Profile(_lsprof.Profiler):
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"""Profile(custom_timer=None, time_unit=None, subcalls=True, builtins=True)
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Builds a profiler object using the specified timer function.
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The default timer is a fast built-in one based on real time.
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For custom timer functions returning integers, time_unit can
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be a float specifying a scale (i.e. how long each integer unit
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is, in seconds).
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"""
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# Most of the functionality is in the base class.
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# This subclass only adds convenient and backward-compatible methods.
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def print_stats(self, sort=-1):
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import pstats
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pstats.Stats(self).strip_dirs().sort_stats(sort).print_stats()
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def dump_stats(self, file):
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import marshal
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f = open(file, 'wb')
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self.create_stats()
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marshal.dump(self.stats, f)
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f.close()
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def create_stats(self):
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self.disable()
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self.snapshot_stats()
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def snapshot_stats(self):
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entries = self.getstats()
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self.stats = {}
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callersdicts = {}
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# call information
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for entry in entries:
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func = label(entry.code)
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nc = entry.callcount # ncalls column of pstats (before '/')
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cc = nc - entry.reccallcount # ncalls column of pstats (after '/')
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tt = entry.inlinetime # tottime column of pstats
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ct = entry.totaltime # cumtime column of pstats
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callers = {}
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callersdicts[id(entry.code)] = callers
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self.stats[func] = cc, nc, tt, ct, callers
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# subcall information
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for entry in entries:
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if entry.calls:
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func = label(entry.code)
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for subentry in entry.calls:
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try:
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callers = callersdicts[id(subentry.code)]
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except KeyError:
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continue
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nc = subentry.callcount
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cc = nc - subentry.reccallcount
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tt = subentry.inlinetime
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ct = subentry.totaltime
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if func in callers:
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prev = callers[func]
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nc += prev[0]
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cc += prev[1]
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tt += prev[2]
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ct += prev[3]
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callers[func] = nc, cc, tt, ct
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# The following two methods can be called by clients to use
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# a profiler to profile a statement, given as a string.
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def run(self, cmd):
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import __main__
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dict = __main__.__dict__
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return self.runctx(cmd, dict, dict)
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def runctx(self, cmd, globals, locals):
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self.enable()
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try:
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exec cmd in globals, locals
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finally:
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self.disable()
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return self
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# This method is more useful to profile a single function call.
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def runcall(self, func, *args, **kw):
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self.enable()
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try:
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return func(*args, **kw)
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finally:
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self.disable()
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# ____________________________________________________________
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def label(code):
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if isinstance(code, str):
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return ('~', 0, code) # built-in functions ('~' sorts at the end)
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else:
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return (code.co_filename, code.co_firstlineno, code.co_name)
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# ____________________________________________________________
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def main():
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import os, sys
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from optparse import OptionParser
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usage = "cProfile.py [-o output_file_path] [-s sort] scriptfile [arg] ..."
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parser = OptionParser(usage=usage)
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parser.allow_interspersed_args = False
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parser.add_option('-o', '--outfile', dest="outfile",
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help="Save stats to <outfile>", default=None)
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parser.add_option('-s', '--sort', dest="sort",
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help="Sort order when printing to stdout, based on pstats.Stats class",
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default=-1)
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if not sys.argv[1:]:
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parser.print_usage()
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sys.exit(2)
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(options, args) = parser.parse_args()
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sys.argv[:] = args
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if len(args) > 0:
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progname = args[0]
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sys.path.insert(0, os.path.dirname(progname))
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with open(progname, 'rb') as fp:
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code = compile(fp.read(), progname, 'exec')
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globs = {
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'__file__': progname,
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'__name__': '__main__',
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'__package__': None,
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}
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runctx(code, globs, None, options.outfile, options.sort)
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else:
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parser.print_usage()
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return parser
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# When invoked as main program, invoke the profiler on a script
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if __name__ == '__main__':
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main()
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