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  #   ˆl–Ãa¾”d*j"TÚzã@¸Ø”Å£Áƒq–›À¿Ã É    #! /usr/bin/python3.9

"""Python interface for the 'lsprof' profiler.
   Compatible with the 'profile' module.
"""

__all__ = ["run", "runctx", "Profile"]

import _lsprof
import io
import profile as _pyprofile

# ____________________________________________________________
# Simple interface

def run(statement, filename=None, sort=-1):
    return _pyprofile._Utils(Profile).run(statement, filename, sort)

def runctx(statement, globals, locals, filename=None, sort=-1):
    return _pyprofile._Utils(Profile).runctx(statement, globals, locals,
                                             filename, sort)

run.__doc__ = _pyprofile.run.__doc__
runctx.__doc__ = _pyprofile.runctx.__doc__

# ____________________________________________________________

class Profile(_lsprof.Profiler):
    """Profile(timer=None, timeunit=None, subcalls=True, builtins=True)

    Builds a profiler object using the specified timer function.
    The default timer is a fast built-in one based on real time.
    For custom timer functions returning integers, timeunit can
    be a float specifying a scale (i.e. how long each integer unit
    is, in seconds).
    """

    # Most of the functionality is in the base class.
    # This subclass only adds convenient and backward-compatible methods.

    def print_stats(self, sort=-1):
        import pstats
        pstats.Stats(self).strip_dirs().sort_stats(sort).print_stats()

    def dump_stats(self, file):
        import marshal
        with open(file, 'wb') as f:
            self.create_stats()
            marshal.dump(self.stats, f)

    def create_stats(self):
        self.disable()
        self.snapshot_stats()

    def snapshot_stats(self):
        entries = self.getstats()
        self.stats = {}
        callersdicts = {}
        # call information
        for entry in entries:
            func = label(entry.code)
            nc = entry.callcount         # ncalls column of pstats (before '/')
            cc = nc - entry.reccallcount # ncalls column of pstats (after '/')
            tt = entry.inlinetime        # tottime column of pstats
            ct = entry.totaltime         # cumtime column of pstats
            callers = {}
            callersdicts[id(entry.code)] = callers
            self.stats[func] = cc, nc, tt, ct, callers
        # subcall information
        for entry in entries:
            if entry.calls:
                func = label(entry.code)
                for subentry in entry.calls:
                    try:
                        callers = callersdicts[id(subentry.code)]
                    except KeyError:
                        continue
                    nc = subentry.callcount
                    cc = nc - subentry.reccallcount
                    tt = subentry.inlinetime
                    ct = subentry.totaltime
                    if func in callers:
                        prev = callers[func]
                        nc += prev[0]
                        cc += prev[1]
                        tt += prev[2]
                        ct += prev[3]
                    callers[func] = nc, cc, tt, ct

    # The following two methods can be called by clients to use
    # a profiler to profile a statement, given as a string.

    def run(self, cmd):
        import __main__
        dict = __main__.__dict__
        return self.runctx(cmd, dict, dict)

    def runctx(self, cmd, globals, locals):
        self.enable()
        try:
            exec(cmd, globals, locals)
        finally:
            self.disable()
        return self

    # This method is more useful to profile a single function call.
    def runcall(self, func, /, *args, **kw):
        self.enable()
        try:
            return func(*args, **kw)
        finally:
            self.disable()

    def __enter__(self):
        self.enable()
        return self

    def __exit__(self, *exc_info):
        self.disable()

# ____________________________________________________________

def label(code):
    if isinstance(code, str):
        return ('~', 0, code)    # b