tracemalloc — Trace memory allocations¶Added in version 3.4.
Source code: 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.
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.
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.
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.
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.
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=}")
Output:
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(...))).
Get the traceback where the Python object obj was allocated.
Return a Traceback instance, or None if the tracemalloc
module is not tracing memory allocations or did not trace the allocation of
the object.
See also gc.get_referrers() and sys.getsizeof() functions.
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.
Get the current size and peak size of memory blocks traced by the
tracemalloc module as a tuple: (current: int, peak: int).
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 with
take_snapshot() before a call to reset_peak() can be
meaningfully compared to snapshots taken after the call.
See also get_traced_memory().
Added in version 3.9.
Get the memory usage in bytes of the tracemalloc module used to store
traces of memory blocks.
Return an int.
True if the tracemalloc module is tracing Python memory
allocations, False otherwise.
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 to 1.
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 the
Snapshot.compare_to() and Snapshot.statistics() methods.
Storing more frames increases the memory and CPU overhead of the
tracemalloc module. Use the get_tracemalloc_memory() function
to measure how much memory is used by the tracemalloc 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() and get_traceback_limit()
functions.
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() and clear_traces()
functions.
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 the start() function to store more frames.
The tracemalloc module must be tracing memory allocations to take a
snapshot, see the start() function.
See also the get_object_traceback() function.
Filter traces of memory blocks by their address space (domain).
Added in version 3.6.
If inclusive is True (include), match memory blocks allocated
in the address space domain.
If inclusive is False (exclude), match memory blocks not allocated
in the address space domain.
Address space of a memory block (int). Read-only property.
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'.
Examples:
Filter(True, subprocess.__file__) only includes traces of the
subprocess module
Filter(False, tracemalloc.__file__) excludes traces of the
tracemalloc module
Filter(False, "<unknown>") excludes empty tracebacks
Changed in version 3.5: The '.pyo' file extension is no longer replaced with '.py'.
Changed in version 3.6: Added the domain attribute.
Address space of a memory block (int or None).
tracemalloc uses the domain 0 to trace memory allocations made by
Python. C extensions can use other domains to trace other resources.
If inclusive is True (include), only match memory blocks allocated
in a file with a name matching filename_pattern at line number
lineno.
If inclusive is False (exclude), ignore memory blocks allocated in
a file with a name matching filename_pattern at line number
lineno.
Line number (int) of the filter. If lineno is None, the filter
matches any line number.
Filename pattern of the filter (str). Read-only property.
If all_frames is True, all frames of the traceback are checked. If
all_frames is False, only the most recent frame is checked.
This attribute has no effect if the traceback limit is 1. See the
get_traceback_limit() function and Snapshot.traceback_limit
attribute.
Snapshot of traces of memory blocks allocated by Python.
The take_snapshot() function creates a snapshot instance.
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 of StatisticDiff.count_diff, Statistic.count and
then by StatisticDiff.traceback.
Create a new Snapshot instance with a filtered traces
sequence, filters is a list of DomainFilter and
Filter instances. If filters is an empty list, return a new
Snapshot 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.
Changed in version 3.6: DomainFilter instances are now also accepted in filters.
Get statistics as a sorted list of Statistic instances grouped
by key_type:
key_type |
description |
|---|---|
|
filename |
|
filename and line number |
|
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 by
Statistic.traceback.
Maximum number of frames stored in the traceback of traces:
result of the get_traceback_limit() when the snapshot was taken.
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 on memory allocations.
Snapshot.statistics() returns a list of Statistic instances.
See also the StatisticDiff class.
Number of memory blocks (int).
Total size of memory blocks in bytes (int).
Statistic difference on memory allocations between an old and a new
Snapshot instance.
Snapshot.compare_to() returns a list of StatisticDiff
instances. See also the Statistic class.
Number of memory blocks in the new snapshot (int): 0 if
the memory blocks have been released in the new snapshot.
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.
Total size of memory blocks in bytes in the new snapshot (int):
0 if the memory blocks have been released in the new snapshot.
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 of a memory block.
The Snapshot.traces attribute is a sequence of Trace
instances.
Changed in version 3.6: Added the domain attribute.
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 of the memory block in bytes (int).
Sequence of Frame instances sorted from the oldest frame to the
most recent frame.
A traceback contains at least 1 frame. If the tracemalloc module
failed to get a frame, the filename "<unknown>" at line number 0 is
used.
When a snapshot is taken, tracebacks of traces are limited to
get_traceback_limit() frames. See the take_snapshot() function.
The original number of frames of the traceback is stored in the
Traceback.total_nframe attribute. That allows to know if a traceback
has been truncated by the traceback limit.
The Trace.traceback attribute is an instance of Traceback
instance.
Changed in version 3.7: Frames are now sorted from the oldest to the most recent, instead of most recent to oldest.
Total number of frames that composed the traceback before truncation.
This attribute can be set to None if the information is not
available.
Changed in version 3.9: The Traceback.total_nframe attribute was added.
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 the
abs(limit) oldest frames. If most_recent_first is True, 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 that
format() does not include newlines.
Example:
print("Traceback (most recent call first):")
for line in traceback:
print(line)
Output:
Traceback (most recent call first):
File "test.py", line 9
obj = Object()
File "test.py", line 12
tb = tracemalloc.get_object_traceback(f())