tracemalloc
— Trace memory allocations¶
Novo na versão 3.4.
Código-fonte: Lib/tracemalloc.py
The tracemalloc module is a debug tool to trace memory blocks allocated by Python. It provides the following information:
Traceback where an object was allocated
Statistics on allocated memory blocks per filename and per line number: total size, number and average size of allocated memory blocks
Compute the differences between two snapshots to detect memory leaks
To trace most memory blocks allocated by Python, the module should be started
as early as possible by setting the PYTHONTRACEMALLOC
environment
variable to 1
, or by using -X
tracemalloc
command line
option. The tracemalloc.start()
function can be called at runtime to
start tracing Python memory allocations.
By default, a trace of an allocated memory block only stores the most recent
frame (1 frame). To store 25 frames at startup: set the
PYTHONTRACEMALLOC
environment variable to 25
, or use the
-X
tracemalloc=25
command line option.
Exemplos¶
Exibe o top 10¶
Display the 10 files allocating the most memory:
import tracemalloc
tracemalloc.start()
# ... run your application ...
snapshot = tracemalloc.take_snapshot()
top_stats = snapshot.statistics('lineno')
print("[ Top 10 ]")
for stat in top_stats[:10]:
print(stat)
Example of output of the Python test suite:
[ Top 10 ]
<frozen importlib._bootstrap>:716: size=4855 KiB, count=39328, average=126 B
<frozen importlib._bootstrap>:284: size=521 KiB, count=3199, average=167 B
/usr/lib/python3.4/collections/__init__.py:368: size=244 KiB, count=2315, average=108 B
/usr/lib/python3.4/unittest/case.py:381: size=185 KiB, count=779, average=243 B
/usr/lib/python3.4/unittest/case.py:402: size=154 KiB, count=378, average=416 B
/usr/lib/python3.4/abc.py:133: size=88.7 KiB, count=347, average=262 B
<frozen importlib._bootstrap>:1446: size=70.4 KiB, count=911, average=79 B
<frozen importlib._bootstrap>:1454: size=52.0 KiB, count=25, average=2131 B
<string>:5: size=49.7 KiB, count=148, average=344 B
/usr/lib/python3.4/sysconfig.py:411: size=48.0 KiB, count=1, average=48.0 KiB
We can see that Python loaded 4855 KiB
data (bytecode and constants) from
modules and that the collections
module allocated 244 KiB
to build
namedtuple
types.
See Snapshot.statistics()
for more options.
Compute differences¶
Take two snapshots and display the differences:
import tracemalloc
tracemalloc.start()
# ... start your application ...
snapshot1 = tracemalloc.take_snapshot()
# ... call the function leaking memory ...
snapshot2 = tracemalloc.take_snapshot()
top_stats = snapshot2.compare_to(snapshot1, 'lineno')
print("[ Top 10 differences ]")
for stat in top_stats[:10]:
print(stat)
Example of output before/after running some tests of the Python test suite:
[ Top 10 differences ]
<frozen importlib._bootstrap>:716: size=8173 KiB (+4428 KiB), count=71332 (+39369), average=117 B
/usr/lib/python3.4/linecache.py:127: size=940 KiB (+940 KiB), count=8106 (+8106), average=119 B
/usr/lib/python3.4/unittest/case.py:571: size=298 KiB (+298 KiB), count=589 (+589), average=519 B
<frozen importlib._bootstrap>:284: size=1005 KiB (+166 KiB), count=7423 (+1526), average=139 B
/usr/lib/python3.4/mimetypes.py:217: size=112 KiB (+112 KiB), count=1334 (+1334), average=86 B
/usr/lib/python3.4/http/server.py:848: size=96.0 KiB (+96.0 KiB), count=1 (+1), average=96.0 KiB
/usr/lib/python3.4/inspect.py:1465: size=83.5 KiB (+83.5 KiB), count=109 (+109), average=784 B
/usr/lib/python3.4/unittest/mock.py:491: size=77.7 KiB (+77.7 KiB), count=143 (+143), average=557 B
/usr/lib/python3.4/urllib/parse.py:476: size=71.8 KiB (+71.8 KiB), count=969 (+969), average=76 B
/usr/lib/python3.4/contextlib.py:38: size=67.2 KiB (+67.2 KiB), count=126 (+126), average=546 B
We can see that Python has loaded 8173 KiB
of module data (bytecode and
constants), and that this is 4428 KiB
more than had been loaded before the
tests, when the previous snapshot was taken. Similarly, the linecache
module has cached 940 KiB
of Python source code to format tracebacks, all
of it since the previous snapshot.
If the system has little free memory, snapshots can be written on disk using
the Snapshot.dump()
method to analyze the snapshot offline. Then use the
Snapshot.load()
method reload the snapshot.
Get the traceback of a memory block¶
Code to display the traceback of the biggest memory block:
import tracemalloc
# Store 25 frames
tracemalloc.start(25)
# ... run your application ...
snapshot = tracemalloc.take_snapshot()
top_stats = snapshot.statistics('traceback')
# pick the biggest memory block
stat = top_stats[0]
print("%s memory blocks: %.1f KiB" % (stat.count, stat.size / 1024))
for line in stat.traceback.format():
print(line)
Example of output of the Python test suite (traceback limited to 25 frames):
903 memory blocks: 870.1 KiB
File "<frozen importlib._bootstrap>", line 716
File "<frozen importlib._bootstrap>", line 1036
File "<frozen importlib._bootstrap>", line 934
File "<frozen importlib._bootstrap>", line 1068
File "<frozen importlib._bootstrap>", line 619
File "<frozen importlib._bootstrap>", line 1581
File "<frozen importlib._bootstrap>", line 1614
File "/usr/lib/python3.4/doctest.py", line 101
import pdb
File "<frozen importlib._bootstrap>", line 284
File "<frozen importlib._bootstrap>", line 938
File "<frozen importlib._bootstrap>", line 1068
File "<frozen importlib._bootstrap>", line 619
File "<frozen importlib._bootstrap>", line 1581
File "<frozen importlib._bootstrap>", line 1614
File "/usr/lib/python3.4/test/support/__init__.py", line 1728
import doctest
File "/usr/lib/python3.4/test/test_pickletools.py", line 21
support.run_doctest(pickletools)
File "/usr/lib/python3.4/test/regrtest.py", line 1276
test_runner()
File "/usr/lib/python3.4/test/regrtest.py", line 976
display_failure=not verbose)
File "/usr/lib/python3.4/test/regrtest.py", line 761
match_tests=ns.match_tests)
File "/usr/lib/python3.4/test/regrtest.py", line 1563
main()
File "/usr/lib/python3.4/test/__main__.py", line 3
regrtest.main_in_temp_cwd()
File "/usr/lib/python3.4/runpy.py", line 73
exec(code, run_globals)
File "/usr/lib/python3.4/runpy.py", line 160
"__main__", fname, loader, pkg_name)
We can see that the most memory was allocated in the importlib
module to
load data (bytecode and constants) from modules: 870.1 KiB
. The traceback is
where the importlib
loaded data most recently: on the import pdb
line of the doctest
module. The traceback may change if a new module is
loaded.
Pretty top¶
Code to display the 10 lines allocating the most memory with a pretty output,
ignoring <frozen importlib._bootstrap>
and <unknown>
files:
import linecache
import os
import tracemalloc
def display_top(snapshot, key_type='lineno', limit=10):
snapshot = snapshot.filter_traces((
tracemalloc.Filter(False, "<frozen importlib._bootstrap>"),
tracemalloc.Filter(False, "<unknown>"),
))
top_stats = snapshot.statistics(key_type)
print("Top %s lines" % limit)
for index, stat in enumerate(top_stats[:limit], 1):
frame = stat.traceback[0]
print("#%s: %s:%s: %.1f KiB"
% (index, frame.filename, frame.lineno, stat.size / 1024))
line = linecache.getline(frame.filename, frame.lineno).strip()
if line:
print(' %s' % line)
other = top_stats[limit:]
if other:
size = sum(stat.size for stat in other)
print("%s other: %.1f KiB" % (len(other), size / 1024))
total = sum(stat.size for stat in top_stats)
print("Total allocated size: %.1f KiB" % (total / 1024))
tracemalloc.start()
# ... run your application ...
snapshot = tracemalloc.take_snapshot()
display_top(snapshot)
Example of output of the Python test suite:
Top 10 lines
#1: Lib/base64.py:414: 419.8 KiB
_b85chars2 = [(a + b) for a in _b85chars for b in _b85chars]
#2: Lib/base64.py:306: 419.8 KiB
_a85chars2 = [(a + b) for a in _a85chars for b in _a85chars]
#3: collections/__init__.py:368: 293.6 KiB
exec(class_definition, namespace)
#4: Lib/abc.py:133: 115.2 KiB
cls = super().__new__(mcls, name, bases, namespace)
#5: unittest/case.py:574: 103.1 KiB
testMethod()
#6: Lib/linecache.py:127: 95.4 KiB
lines = fp.readlines()
#7: urllib/parse.py:476: 71.8 KiB
for a in _hexdig for b in _hexdig}
#8: <string>:5: 62.0 KiB
#9: Lib/_weakrefset.py:37: 60.0 KiB
self.data = set()
#10: Lib/base64.py:142: 59.8 KiB
_b32tab2 = [a + b for a in _b32tab for b in _b32tab]
6220 other: 3602.8 KiB
Total allocated size: 5303.1 KiB
See Snapshot.statistics()
for more options.
Record the current and peak size of all traced memory blocks¶
The following code computes two sums like 0 + 1 + 2 + ...
inefficiently, by
creating a list of those numbers. This list consumes a lot of memory
temporarily. We can use get_traced_memory()
and reset_peak()
to
observe the small memory usage after the sum is computed as well as the peak
memory usage during the computations:
import tracemalloc
tracemalloc.start()
# Example code: compute a sum with a large temporary list
large_sum = sum(list(range(100000)))
first_size, first_peak = tracemalloc.get_traced_memory()
tracemalloc.reset_peak()
# Example code: compute a sum with a small temporary list
small_sum = sum(list(range(1000)))
second_size, second_peak = tracemalloc.get_traced_memory()
print(f"{first_size=}, {first_peak=}")
print(f"{second_size=}, {second_peak=}")
Saída:
first_size=664, first_peak=3592984
second_size=804, second_peak=29704
Using reset_peak()
ensured we could accurately record the peak during the
computation of small_sum
, even though it is much smaller than the overall
peak size of memory blocks since the start()
call. Without the call to
reset_peak()
, second_peak
would still be the peak from the
computation large_sum
(that is, equal to first_peak
). In this case,
both peaks are much higher than the final memory usage, and which suggests we
could optimise (by removing the unnecessary call to list
, and writing
sum(range(...))
).
API¶
Funções¶
-
tracemalloc.
get_object_traceback
(obj)¶ Get the traceback where the Python object obj was allocated. Return a
Traceback
instance, orNone
if thetracemalloc
module is not tracing memory allocations or did not trace the allocation of the object.See also
gc.get_referrers()
andsys.getsizeof()
functions.
-
tracemalloc.
get_traceback_limit
()¶ Get the maximum number of frames stored in the traceback of a trace.
The
tracemalloc
module must be tracing memory allocations to get the limit, otherwise an exception is raised.The limit is set by the
start()
function.
-
tracemalloc.
get_traced_memory
()¶ Get the current size and peak size of memory blocks traced by the
tracemalloc
module as a tuple:(current: int, peak: int)
.
-
tracemalloc.
reset_peak
()¶ Set the peak size of memory blocks traced by the
tracemalloc
module to the current size.Do nothing if the
tracemalloc
module is not tracing memory allocations.This function only modifies the recorded peak size, and does not modify or clear any traces, unlike
clear_traces()
. Snapshots taken withtake_snapshot()
before a call toreset_peak()
can be meaningfully compared to snapshots taken after the call.See also
get_traced_memory()
.Novo na versão 3.9.
-
tracemalloc.
get_tracemalloc_memory
()¶ Get the memory usage in bytes of the
tracemalloc
module used to store traces of memory blocks. Return anint
.
-
tracemalloc.
is_tracing
()¶ True
if thetracemalloc
module is tracing Python memory allocations,False
otherwise.
-
tracemalloc.
start
(nframe: int=1)¶ Start tracing Python memory allocations: install hooks on Python memory allocators. Collected tracebacks of traces will be limited to nframe frames. By default, a trace of a memory block only stores the most recent frame: the limit is
1
. nframe must be greater or equal to1
.You can still read the original number of total frames that composed the traceback by looking at the
Traceback.total_nframe
attribute.Storing more than
1
frame is only useful to compute statistics grouped by'traceback'
or to compute cumulative statistics: see theSnapshot.compare_to()
andSnapshot.statistics()
methods.Storing more frames increases the memory and CPU overhead of the
tracemalloc
module. Use theget_tracemalloc_memory()
function to measure how much memory is used by thetracemalloc
module.The
PYTHONTRACEMALLOC
environment variable (PYTHONTRACEMALLOC=NFRAME
) and the-X
tracemalloc=NFRAME
command line option can be used to start tracing at startup.See also
stop()
,is_tracing()
andget_traceback_limit()
functions.
-
tracemalloc.
stop
()¶ Stop tracing Python memory allocations: uninstall hooks on Python memory allocators. Also clears all previously collected traces of memory blocks allocated by Python.
Call
take_snapshot()
function to take a snapshot of traces before clearing them.See also
start()
,is_tracing()
andclear_traces()
functions.
-
tracemalloc.
take_snapshot
()¶ Take a snapshot of traces of memory blocks allocated by Python. Return a new
Snapshot
instance.The snapshot does not include memory blocks allocated before the
tracemalloc
module started to trace memory allocations.Tracebacks of traces are limited to
get_traceback_limit()
frames. Use the nframe parameter of thestart()
function to store more frames.The
tracemalloc
module must be tracing memory allocations to take a snapshot, see thestart()
function.See also the
get_object_traceback()
function.
DomainFilter¶
-
class
tracemalloc.
DomainFilter
(inclusive: bool, domain: int)¶ Filter traces of memory blocks by their address space (domain).
Novo na versão 3.6.
-
inclusive
¶ If inclusive is
True
(include), match memory blocks allocated in the address spacedomain
.If inclusive is
False
(exclude), match memory blocks not allocated in the address spacedomain
.
-
domain
¶ Address space of a memory block (
int
). Read-only property.
-
Filter¶
-
class
tracemalloc.
Filter
(inclusive: bool, filename_pattern: str, lineno: int=None, all_frames: bool=False, domain: int=None)¶ Filter on traces of memory blocks.
See the
fnmatch.fnmatch()
function for the syntax of filename_pattern. The'.pyc'
file extension is replaced with'.py'
.Exemplos:
Filter(True, subprocess.__file__)
only includes traces of thesubprocess
moduleFilter(False, tracemalloc.__file__)
excludes traces of thetracemalloc
moduleFilter(False, "<unknown>")
excludes empty tracebacks
Alterado na versão 3.5: The
'.pyo'
file extension is no longer replaced with'.py'
.Alterado na versão 3.6: Added the
domain
attribute.-
domain
¶ Address space of a memory block (
int
orNone
).tracemalloc uses the domain
0
to trace memory allocations made by Python. C extensions can use other domains to trace other resources.
-
inclusive
¶ If inclusive is
True
(include), only match memory blocks allocated in a file with a name matchingfilename_pattern
at line numberlineno
.If inclusive is
False
(exclude), ignore memory blocks allocated in a file with a name matchingfilename_pattern
at line numberlineno
.
-
lineno
¶ Line number (
int
) of the filter. If lineno isNone
, the filter matches any line number.
-
filename_pattern
¶ Filename pattern of the filter (
str
). Read-only property.
-
all_frames
¶ If all_frames is
True
, all frames of the traceback are checked. If all_frames isFalse
, only the most recent frame is checked.This attribute has no effect if the traceback limit is
1
. See theget_traceback_limit()
function andSnapshot.traceback_limit
attribute.
Frame¶
Snapshot¶
-
class
tracemalloc.
Snapshot
¶ Snapshot of traces of memory blocks allocated by Python.
The
take_snapshot()
function creates a snapshot instance.-
compare_to
(old_snapshot: Snapshot, key_type: str, cumulative: bool=False)¶ Compute the differences with an old snapshot. Get statistics as a sorted list of
StatisticDiff
instances grouped by key_type.See the
Snapshot.statistics()
method for key_type and cumulative parameters.The result is sorted from the biggest to the smallest by: absolute value of
StatisticDiff.size_diff
,StatisticDiff.size
, absolute value ofStatisticDiff.count_diff
,Statistic.count
and then byStatisticDiff.traceback
.
-
filter_traces
(filters)¶ Create a new
Snapshot
instance with a filteredtraces
sequence, filters is a list ofDomainFilter
andFilter
instances. If filters is an empty list, return a newSnapshot
instance with a copy of the traces.All inclusive filters are applied at once, a trace is ignored if no inclusive filters match it. A trace is ignored if at least one exclusive filter matches it.
Alterado na versão 3.6:
DomainFilter
instances are now also accepted in filters.
-
statistics
(key_type: str, cumulative: bool=False)¶ Get statistics as a sorted list of
Statistic
instances grouped by key_type:key_type
description
'filename'
filename
'lineno'
filename and line number
'traceback'
traceback
If cumulative is
True
, cumulate size and count of memory blocks of all frames of the traceback of a trace, not only the most recent frame. The cumulative mode can only be used with key_type equals to'filename'
and'lineno'
.The result is sorted from the biggest to the smallest by:
Statistic.size
,Statistic.count
and then byStatistic.traceback
.
-
traceback_limit
¶ Maximum number of frames stored in the traceback of
traces
: result of theget_traceback_limit()
when the snapshot was taken.
-
traces
¶ Traces of all memory blocks allocated by Python: sequence of
Trace
instances.The sequence has an undefined order. Use the
Snapshot.statistics()
method to get a sorted list of statistics.
-
Statistic¶
-
class
tracemalloc.
Statistic
¶ Statistic on memory allocations.
Snapshot.statistics()
returns a list ofStatistic
instances.See also the
StatisticDiff
class.-
count
¶ Number of memory blocks (
int
).
-
size
¶ Total size of memory blocks in bytes (
int
).
-
StatisticDiff¶
-
class
tracemalloc.
StatisticDiff
¶ Statistic difference on memory allocations between an old and a new
Snapshot
instance.Snapshot.compare_to()
returns a list ofStatisticDiff
instances. See also theStatistic
class.-
count
¶ Number of memory blocks in the new snapshot (
int
):0
if the memory blocks have been released in the new snapshot.
-
count_diff
¶ Difference of number of memory blocks between the old and the new snapshots (
int
):0
if the memory blocks have been allocated in the new snapshot.
-
size
¶ Total size of memory blocks in bytes in the new snapshot (
int
):0
if the memory blocks have been released in the new snapshot.
-
size_diff
¶ Difference of total size of memory blocks in bytes between the old and the new snapshots (
int
):0
if the memory blocks have been allocated in the new snapshot.
-
Trace¶
-
class
tracemalloc.
Trace
¶ Trace of a memory block.
The
Snapshot.traces
attribute is a sequence ofTrace
instances.Alterado na versão 3.6: Added the
domain
attribute.-
domain
¶ Address space of a memory block (
int
). Read-only property.tracemalloc uses the domain
0
to trace memory allocations made by Python. C extensions can use other domains to trace other resources.
-
size
¶ Size of the memory block in bytes (
int
).
-
Traceback¶
-
class
tracemalloc.
Traceback
¶ Sequence of
Frame
instances sorted from the oldest frame to the most recent frame.A traceback contains at least
1
frame. If thetracemalloc
module failed to get a frame, the filename"<unknown>"
at line number0
is used.When a snapshot is taken, tracebacks of traces are limited to
get_traceback_limit()
frames. See thetake_snapshot()
function. The original number of frames of the traceback is stored in theTraceback.total_nframe
attribute. That allows to know if a traceback has been truncated by the traceback limit.The
Trace.traceback
attribute is an instance ofTraceback
instance.Alterado na versão 3.7: Frames are now sorted from the oldest to the most recent, instead of most recent to oldest.
-
total_nframe
¶ Total number of frames that composed the traceback before truncation. This attribute can be set to
None
if the information is not available.
Alterado na versão 3.9: The
Traceback.total_nframe
attribute was added.-
format
(limit=None, most_recent_first=False)¶ Format the traceback as a list of lines. Use the
linecache
module to retrieve lines from the source code. If limit is set, format the limit most recent frames if limit is positive. Otherwise, format theabs(limit)
oldest frames. If most_recent_first isTrue
, the order of the formatted frames is reversed, returning the most recent frame first instead of last.Similar to the
traceback.format_tb()
function, except thatformat()
does not include newlines.Exemplo:
print("Traceback (most recent call first):") for line in traceback: print(line)
Saída:
Traceback (most recent call first): File "test.py", line 9 obj = Object() File "test.py", line 12 tb = tracemalloc.get_object_traceback(f())
-