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)