Current File : //usr/lib64/python3.6/tracemalloc.py
from collections import Sequence, Iterable
from functools import total_ordering
import fnmatch
import linecache
import os.path
import pickle

# Import types and functions implemented in C
from _tracemalloc import *
from _tracemalloc import _get_object_traceback, _get_traces


def _format_size(size, sign):
    for unit in ('B', 'KiB', 'MiB', 'GiB', 'TiB'):
        if abs(size) < 100 and unit != 'B':
            # 3 digits (xx.x UNIT)
            if sign:
                return "%+.1f %s" % (size, unit)
            else:
                return "%.1f %s" % (size, unit)
        if abs(size) < 10 * 1024 or unit == 'TiB':
            # 4 or 5 digits (xxxx UNIT)
            if sign:
                return "%+.0f %s" % (size, unit)
            else:
                return "%.0f %s" % (size, unit)
        size /= 1024


class Statistic:
    """
    Statistic difference on memory allocations between two Snapshot instance.
    """

    __slots__ = ('traceback', 'size', 'count')

    def __init__(self, traceback, size, count):
        self.traceback = traceback
        self.size = size
        self.count = count

    def __hash__(self):
        return hash((self.traceback, self.size, self.count))

    def __eq__(self, other):
        return (self.traceback == other.traceback
                and self.size == other.size
                and self.count == other.count)

    def __str__(self):
        text = ("%s: size=%s, count=%i"
                 % (self.traceback,
                    _format_size(self.size, False),
                    self.count))
        if self.count:
            average = self.size / self.count
            text += ", average=%s" % _format_size(average, False)
        return text

    def __repr__(self):
        return ('<Statistic traceback=%r size=%i count=%i>'
                % (self.traceback, self.size, self.count))

    def _sort_key(self):
        return (self.size, self.count, self.traceback)


class StatisticDiff:
    """
    Statistic difference on memory allocations between an old and a new
    Snapshot instance.
    """
    __slots__ = ('traceback', 'size', 'size_diff', 'count', 'count_diff')

    def __init__(self, traceback, size, size_diff, count, count_diff):
        self.traceback = traceback
        self.size = size
        self.size_diff = size_diff
        self.count = count
        self.count_diff = count_diff

    def __hash__(self):
        return hash((self.traceback, self.size, self.size_diff,
                     self.count, self.count_diff))

    def __eq__(self, other):
        return (self.traceback == other.traceback
                and self.size == other.size
                and self.size_diff == other.size_diff
                and self.count == other.count
                and self.count_diff == other.count_diff)

    def __str__(self):
        text = ("%s: size=%s (%s), count=%i (%+i)"
                % (self.traceback,
                   _format_size(self.size, False),
                   _format_size(self.size_diff, True),
                   self.count,
                   self.count_diff))
        if self.count:
            average = self.size / self.count
            text += ", average=%s" % _format_size(average, False)
        return text

    def __repr__(self):
        return ('<StatisticDiff traceback=%r size=%i (%+i) count=%i (%+i)>'
                % (self.traceback, self.size, self.size_diff,
                   self.count, self.count_diff))

    def _sort_key(self):
        return (abs(self.size_diff), self.size,
                abs(self.count_diff), self.count,
                self.traceback)


def _compare_grouped_stats(old_group, new_group):
    statistics = []
    for traceback, stat in new_group.items():
        previous = old_group.pop(traceback, None)
        if previous is not None:
            stat = StatisticDiff(traceback,
                                 stat.size, stat.size - previous.size,
                                 stat.count, stat.count - previous.count)
        else:
            stat = StatisticDiff(traceback,
                                 stat.size, stat.size,
                                 stat.count, stat.count)
        statistics.append(stat)

    for traceback, stat in old_group.items():
        stat = StatisticDiff(traceback, 0, -stat.size, 0, -stat.count)
        statistics.append(stat)
    return statistics


@total_ordering
class Frame:
    """
    Frame of a traceback.
    """
    __slots__ = ("_frame",)

    def __init__(self, frame):
        # frame is a tuple: (filename: str, lineno: int)
        self._frame = frame

    @property
    def filename(self):
        return self._frame[0]

    @property
    def lineno(self):
        return self._frame[1]

    def __eq__(self, other):
        return (self._frame == other._frame)

    def __lt__(self, other):
        return (self._frame < other._frame)

    def __hash__(self):
        return hash(self._frame)

    def __str__(self):
        return "%s:%s" % (self.filename, self.lineno)

    def __repr__(self):
        return "<Frame filename=%r lineno=%r>" % (self.filename, self.lineno)


@total_ordering
class Traceback(Sequence):
    """
    Sequence of Frame instances sorted from the most recent frame
    to the oldest frame.
    """
    __slots__ = ("_frames",)

    def __init__(self, frames):
        Sequence.__init__(self)
        # frames is a tuple of frame tuples: see Frame constructor for the
        # format of a frame tuple
        self._frames = frames

    def __len__(self):
        return len(self._frames)

    def __getitem__(self, index):
        if isinstance(index, slice):
            return tuple(Frame(trace) for trace in self._frames[index])
        else:
            return Frame(self._frames[index])

    def __contains__(self, frame):
        return frame._frame in self._frames

    def __hash__(self):
        return hash(self._frames)

    def __eq__(self, other):
        return (self._frames == other._frames)

    def __lt__(self, other):
        return (self._frames < other._frames)

    def __str__(self):
        return str(self[0])

    def __repr__(self):
        return "<Traceback %r>" % (tuple(self),)

    def format(self, limit=None):
        lines = []
        if limit is not None and limit < 0:
            return lines
        for frame in self[:limit]:
            lines.append('  File "%s", line %s'
                         % (frame.filename, frame.lineno))
            line = linecache.getline(frame.filename, frame.lineno).strip()
            if line:
                lines.append('    %s' % line)
        return lines


def get_object_traceback(obj):
    """
    Get the traceback where the Python object *obj* was allocated.
    Return a Traceback instance.

    Return None if the tracemalloc module is not tracing memory allocations or
    did not trace the allocation of the object.
    """
    frames = _get_object_traceback(obj)
    if frames is not None:
        return Traceback(frames)
    else:
        return None


class Trace:
    """
    Trace of a memory block.
    """
    __slots__ = ("_trace",)

    def __init__(self, trace):
        # trace is a tuple: (domain: int, size: int, traceback: tuple).
        # See Traceback constructor for the format of the traceback tuple.
        self._trace = trace

    @property
    def domain(self):
        return self._trace[0]

    @property
    def size(self):
        return self._trace[1]

    @property
    def traceback(self):
        return Traceback(self._trace[2])

    def __eq__(self, other):
        return (self._trace == other._trace)

    def __hash__(self):
        return hash(self._trace)

    def __str__(self):
        return "%s: %s" % (self.traceback, _format_size(self.size, False))

    def __repr__(self):
        return ("<Trace domain=%s size=%s, traceback=%r>"
                % (self.domain, _format_size(self.size, False), self.traceback))


class _Traces(Sequence):
    def __init__(self, traces):
        Sequence.__init__(self)
        # traces is a tuple of trace tuples: see Trace constructor
        self._traces = traces

    def __len__(self):
        return len(self._traces)

    def __getitem__(self, index):
        if isinstance(index, slice):
            return tuple(Trace(trace) for trace in self._traces[index])
        else:
            return Trace(self._traces[index])

    def __contains__(self, trace):
        return trace._trace in self._traces

    def __eq__(self, other):
        return (self._traces == other._traces)

    def __repr__(self):
        return "<Traces len=%s>" % len(self)


def _normalize_filename(filename):
    filename = os.path.normcase(filename)
    if filename.endswith('.pyc'):
        filename = filename[:-1]
    return filename


class BaseFilter:
    def __init__(self, inclusive):
        self.inclusive = inclusive

    def _match(self, trace):
        raise NotImplementedError


class Filter(BaseFilter):
    def __init__(self, inclusive, filename_pattern,
                 lineno=None, all_frames=False, domain=None):
        super().__init__(inclusive)
        self.inclusive = inclusive
        self._filename_pattern = _normalize_filename(filename_pattern)
        self.lineno = lineno
        self.all_frames = all_frames
        self.domain = domain

    @property
    def filename_pattern(self):
        return self._filename_pattern

    def _match_frame_impl(self, filename, lineno):
        filename = _normalize_filename(filename)
        if not fnmatch.fnmatch(filename, self._filename_pattern):
            return False
        if self.lineno is None:
            return True
        else:
            return (lineno == self.lineno)

    def _match_frame(self, filename, lineno):
        return self._match_frame_impl(filename, lineno) ^ (not self.inclusive)

    def _match_traceback(self, traceback):
        if self.all_frames:
            if any(self._match_frame_impl(filename, lineno)
                   for filename, lineno in traceback):
                return self.inclusive
            else:
                return (not self.inclusive)
        else:
            filename, lineno = traceback[0]
            return self._match_frame(filename, lineno)

    def _match(self, trace):
        domain, size, traceback = trace
        res = self._match_traceback(traceback)
        if self.domain is not None:
            if self.inclusive:
                return res and (domain == self.domain)
            else:
                return res or (domain != self.domain)
        return res


class DomainFilter(BaseFilter):
    def __init__(self, inclusive, domain):
        super().__init__(inclusive)
        self._domain = domain

    @property
    def domain(self):
        return self._domain

    def _match(self, trace):
        domain, size, traceback = trace
        return (domain == self.domain) ^ (not self.inclusive)


class Snapshot:
    """
    Snapshot of traces of memory blocks allocated by Python.
    """

    def __init__(self, traces, traceback_limit):
        # traces is a tuple of trace tuples: see _Traces constructor for
        # the exact format
        self.traces = _Traces(traces)
        self.traceback_limit = traceback_limit

    def dump(self, filename):
        """
        Write the snapshot into a file.
        """
        with open(filename, "wb") as fp:
            pickle.dump(self, fp, pickle.HIGHEST_PROTOCOL)

    @staticmethod
    def load(filename):
        """
        Load a snapshot from a file.
        """
        with open(filename, "rb") as fp:
            return pickle.load(fp)

    def _filter_trace(self, include_filters, exclude_filters, trace):
        if include_filters:
            if not any(trace_filter._match(trace)
                       for trace_filter in include_filters):
                return False
        if exclude_filters:
            if any(not trace_filter._match(trace)
                   for trace_filter in exclude_filters):
                return False
        return True

    def filter_traces(self, filters):
        """
        Create a new Snapshot instance with a filtered traces sequence, filters
        is a list of Filter or DomainFilter instances.  If filters is an empty
        list, return a new Snapshot instance with a copy of the traces.
        """
        if not isinstance(filters, Iterable):
            raise TypeError("filters must be a list of filters, not %s"
                            % type(filters).__name__)
        if filters:
            include_filters = []
            exclude_filters = []
            for trace_filter in filters:
                if trace_filter.inclusive:
                    include_filters.append(trace_filter)
                else:
                    exclude_filters.append(trace_filter)
            new_traces = [trace for trace in self.traces._traces
                          if self._filter_trace(include_filters,
                                                exclude_filters,
                                                trace)]
        else:
            new_traces = self.traces._traces.copy()
        return Snapshot(new_traces, self.traceback_limit)

    def _group_by(self, key_type, cumulative):
        if key_type not in ('traceback', 'filename', 'lineno'):
            raise ValueError("unknown key_type: %r" % (key_type,))
        if cumulative and key_type not in ('lineno', 'filename'):
            raise ValueError("cumulative mode cannot by used "
                             "with key type %r" % key_type)

        stats = {}
        tracebacks = {}
        if not cumulative:
            for trace in self.traces._traces:
                domain, size, trace_traceback = trace
                try:
                    traceback = tracebacks[trace_traceback]
                except KeyError:
                    if key_type == 'traceback':
                        frames = trace_traceback
                    elif key_type == 'lineno':
                        frames = trace_traceback[:1]
                    else: # key_type == 'filename':
                        frames = ((trace_traceback[0][0], 0),)
                    traceback = Traceback(frames)
                    tracebacks[trace_traceback] = traceback
                try:
                    stat = stats[traceback]
                    stat.size += size
                    stat.count += 1
                except KeyError:
                    stats[traceback] = Statistic(traceback, size, 1)
        else:
            # cumulative statistics
            for trace in self.traces._traces:
                domain, size, trace_traceback = trace
                for frame in trace_traceback:
                    try:
                        traceback = tracebacks[frame]
                    except KeyError:
                        if key_type == 'lineno':
                            frames = (frame,)
                        else: # key_type == 'filename':
                            frames = ((frame[0], 0),)
                        traceback = Traceback(frames)
                        tracebacks[frame] = traceback
                    try:
                        stat = stats[traceback]
                        stat.size += size
                        stat.count += 1
                    except KeyError:
                        stats[traceback] = Statistic(traceback, size, 1)
        return stats

    def statistics(self, key_type, cumulative=False):
        """
        Group statistics by key_type. Return a sorted list of Statistic
        instances.
        """
        grouped = self._group_by(key_type, cumulative)
        statistics = list(grouped.values())
        statistics.sort(reverse=True, key=Statistic._sort_key)
        return statistics

    def compare_to(self, old_snapshot, key_type, cumulative=False):
        """
        Compute the differences with an old snapshot old_snapshot. Get
        statistics as a sorted list of StatisticDiff instances, grouped by
        group_by.
        """
        new_group = self._group_by(key_type, cumulative)
        old_group = old_snapshot._group_by(key_type, cumulative)
        statistics = _compare_grouped_stats(old_group, new_group)
        statistics.sort(reverse=True, key=StatisticDiff._sort_key)
        return statistics


def take_snapshot():
    """
    Take a snapshot of traces of memory blocks allocated by Python.
    """
    if not is_tracing():
        raise RuntimeError("the tracemalloc module must be tracing memory "
                           "allocations to take a snapshot")
    traces = _get_traces()
    traceback_limit = get_traceback_limit()
    return Snapshot(traces, traceback_limit)
blog

blog

Vavada Зеркало Вход на официальный сайт.2559 (2)

Вавада казино | Vavada Зеркало Вход на официальный сайт ▶️ ИГРАТЬ Содержимое Вавада казино – надежный партнер для игроков Официальный сайт Vavada – доступ к играм и бонусам Преимущества официального сайта Vavada Преимущества и функции казино Vavada – почему игроки выбирают это казино Уникальные функции казино Vavada Преимущества игроков в …

Read More »

казино – Официальный сайт Pin up играть онлайн Зеркало и вход.4776

Пин Ап казино – Официальный сайт Pin up играть онлайн | Зеркало и вход ▶️ ИГРАТЬ Содержимое Pin Up Casino – Официальный сайт Играть онлайн, зеркало и вход Зеркало Pin Up Casino Вход в Pin Up Casino В современном мире азартных игр, где каждый день появляются новые онлайн-казино, сложно найти …

Read More »

казино – Официальный сайт Pin up играть онлайн Зеркало и вход.4776

Пин Ап казино – Официальный сайт Pin up играть онлайн | Зеркало и вход ▶️ ИГРАТЬ Содержимое Pin Up Casino – Официальный сайт Играть онлайн, зеркало и вход Зеркало Pin Up Casino Вход в Pin Up Casino В современном мире азартных игр, где каждый день появляются новые онлайн-казино, сложно найти …

Read More »

Sweet Bonanza Slot by Pragmatic Play Features and Symbols.421

Sweet Bonanza Slot by Pragmatic Play – Features and Symbols ▶️ PLAY Содержимое Unlocking the Secrets of the Game The Power of the Wilds Exploring the Symbols and Their Meanings Get ready to indulge in a world of sweet treats and big wins with the Sweet Bonanza slot by Pragmatic …

Read More »

Sahabet – Sahabet Casino – Sahabet Giriş.8257

Sahabet – Sahabet Casino – Sahabet Giriş ▶️ OYNAMAK Содержимое Sahabet Giriş ve Sahabet Girişi Sahabet Girişi Güncel Yöntemler Sahabet Bahis ve Sahadanbet Sahabet Casino Hakkında Temel Bilgiler Sahabet Casino Oyunları Sahabet ve Sahabet Casino ile ilgili güncel bilgileri ve giriş yollarını anlatacağım. Sahabet, güvenli ve profesyonel bir platform olarak …

Read More »

Betting sites UK How to Make the Most of Your Bets.101

Betting sites UK – How to Make the Most of Your Bets ▶️ PLAY Содержимое Choosing the Right Bookmaker for Your Needs Top 20 Betting Sites UK: A Comprehensive Guide In the world of sports betting, the UK is a hub of activity, with numerous new betting sites emerging to …

Read More »

Casino en ligne Quatro Collection de jeux.1192

Casino en ligne Quatro – Collection de jeux ▶️ JOUER Содержимое Casino en ligne Quatro: Collection de jeux Casino en ligne Quatro: Collection de jeux Table Games Connexion and Mobile Wide Range of Games to Choose From Quatro Casino Login and Rewards High-Quality Game Providers Constantly Updated and Expanded Are …

Read More »

Казино Официальный сайт Pin Up Casino играть онлайн – Вход, Зеркало.7655

Пин Ап Казино Официальный сайт | Pin Up Casino играть онлайн – Вход, Зеркало ▶️ ИГРАТЬ Содержимое Pin Up Casino – Официальный Сайт Играть Онлайн – Вход, Зеркало Как играть на Пин Ап Казино Зеркало Пин Ап Казино В современном мире азартных игр, где каждый день появляются новые онлайн-казино, найти …

Read More »

BasariBet Casino Giriş – Canlı Casino Oyunları.1997

BasariBet Casino Giriş – Canlı Casino Oyunları ▶️ OYNAMAK Содержимое BasariBet Casino’de Canlı Casino Oyunları Nasıl Oynanır? BasariBet Casino’de Canlı Casino Oyunları için En İyi Seçenekler BasariBet Casino’de Canlı Casino Oyunları: Güvenlik ve Destek Hizmetleri BasariBet Casino, oyun sevdiklerinin en güvenilir ve eğlenceli seçeneklerinden biridir. Bu platform, kullanıcılarına canlı casino …

Read More »

1win официальный сайт букмекера — Обзор и зеркало для входа.1580

1win официальный сайт букмекера — Обзор и зеркало для входа ▶️ ИГРАТЬ Содержимое 1win Официальный Сайт Букмекера Обзор и Зеркало для Входа Преимущества и Функции 1win В мире ставок и азарта 1win является одним из самых популярных букмекеров, предлагающих широкий спектр услуг для игроков. Компания была основана в 2018 году …

Read More »