tracemalloc — Trace memory allocations
New 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.
27.7.1. Examples
27.7.1.1. Display the 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.
27.7.1.2. 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.
27.7.1.3. 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.
27.7.1.4. 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] # replace "/path/to/module/file.py" with "module/file.py" filename = os.sep.join(frame.filename.split(os.sep)[-2:]) print("#%s: %s:%s: %.1f KiB" % (index, 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.
27.7.2. API
27.7.2.1. Functions
-
tracemalloc.clear_traces()
-
Clear traces of memory blocks allocated by Python.
See also
stop()
.
-
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.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
.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.
27.7.2.2. DomainFilter
-
class tracemalloc.DomainFilter(inclusive: bool, domain: int)
-
Filter traces of memory blocks by their address space (domain).
New in version 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.
-
27.7.2.3. 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'
.Examples:
-
Filter(True, subprocess.__file__)
only includes traces of thesubprocess
module -
Filter(False, tracemalloc.__file__)
excludes traces of thetracemalloc
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.-
domain
-
Address space of a memory block (
int
orNone
).
-
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.
-
27.7.2.4. Frame
-
class tracemalloc.Frame
-
Frame of a traceback.
The
Traceback
class is a sequence ofFrame
instances.-
filename
-
Filename (
str
).
-
lineno
-
Line number (
int
).
-
27.7.2.5. 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
.
-
dump(filename)
-
Write the snapshot into a file.
Use
load()
to reload the snapshot.
-
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.
Changed in version 3.6:
DomainFilter
instances are now also accepted in filters.
-
classmethod load(filename)
-
Load a snapshot from a file.
See also
dump()
.
-
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.
-
27.7.2.6. 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
).
-
traceback
-
Traceback where the memory block was allocated,
Traceback
instance.
-
27.7.2.7. 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.
-
traceback
-
Traceback where the memory blocks were allocated,
Traceback
instance.
-
27.7.2.8. Trace
-
class tracemalloc.Trace
-
Trace of a memory block.
The
Snapshot.traces
attribute is a sequence ofTrace
instances.-
size
-
Size of the memory block in bytes (
int
).
-
traceback
-
Traceback where the memory block was allocated,
Traceback
instance.
-
27.7.2.9. Traceback
-
class tracemalloc.Traceback
-
Sequence of
Frame
instances sorted from the most recent frame to the oldest 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
Trace.traceback
attribute is an instance ofTraceback
instance.-
format(limit=None)
-
Format the traceback as a list of lines with newlines. Use the
linecache
module to retrieve lines from the source code. If limit is set, only format the limit most recent frames.Similar to the
traceback.format_tb()
function, except thatformat()
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())
-
© 2001–2020 Python Software Foundation
Licensed under the PSF License.
https://docs.python.org/3.6/library/tracemalloc.html