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PHP 8.1.31
Preview: tracemalloc.py Size: 16.68 KB
//usr/lib/python3.8/tracemalloc.py
from collections.abc 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 oldest frame
    to the most recent 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; it is reversed, because _tracemalloc
        # returns frames sorted from most recent to oldest, but the
        # Python API expects oldest to most recent
        self._frames = tuple(reversed(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, most_recent_first=False):
        lines = []
        if limit is not None:
            if limit > 0:
                frame_slice = self[-limit:]
            else:
                frame_slice = self[:limit]
        else:
            frame_slice = self

        if most_recent_first:
            frame_slice = reversed(frame_slice)
        for frame in frame_slice:
            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)

Directory Contents

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Kotlin Archives - Weelorum https://weelorum.com/technology/kotlin/ Full Cycle Mobile App Development Services For Startups Sun, 01 Mar 2026 20:04:38 +0000 en-US hourly 1 https://wordpress.org/?v=7.0 PayFlow https://weelorum.com/portfolio-projects/payflow/ Sun, 01 Mar 2026 20:04:38 +0000 https://weelorum.com/success-stories/payflow/ PayFlow is a fintech application that simplifies international money transfers and currency exchange. Users can hold multiple currencies, send money globally with competitive rates, and receive instant notifications. The app features biometric authentication and real-time transaction tracking.

Сообщение PayFlow появились сначала на Weelorum.

]]> PayFlow is a fintech application that simplifies international money transfers and currency exchange. Users can hold multiple currencies, send money globally with competitive rates, and receive instant notifications. The app features biometric authentication and real-time transaction tracking.

Сообщение PayFlow появились сначала на Weelorum.

]]> Knock Knock https://weelorum.com/portfolio-projects/knock-knock/ Sun, 01 Mar 2026 20:04:37 +0000 https://weelorum.com/success-stories/knock-knock/ Knock Knock is a real-time restaurant discovery app. It shows users what’s happening inside venues, how crowded they are, and offers live previews via photos and video. The app uses geolocation to help people choose where to eat or socialize based on current ambiance.

Сообщение Knock Knock появились сначала на Weelorum.

]]> Knock Knock is a real-time restaurant discovery app. It shows users what’s happening inside venues, how crowded they are, and offers live previews via photos and video. The app uses geolocation to help people choose where to eat or socialize based on current ambiance.

Сообщение Knock Knock появились сначала на Weelorum.

]]>