tracemalloc --- 追蹤記憶體配置¶
在 3.4 版被加入.
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.
範例¶
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.
更多選項請見 Snapshot.statistics()。
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