python 内存泄漏查找方法
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2022-03-15 15:06:49
方法import tracemallocdef test():tracemalloc.start()snapshot1 = tracemalloc.take_snapshot()## 你的各种数据操作………………snapshot2 = tracemalloc.take_snapshot() top_stats = snapshot2.compare_to(snapshot1, 'lineno') print(top_stats[0:10])打印结果:[<...
方法
import tracemalloc
def test():
tracemalloc.start()
snapshot1 = tracemalloc.take_snapshot()
## 你的各种数据操作
………………
snapshot2 = tracemalloc.take_snapshot()
top_stats = snapshot2.compare_to(snapshot1, 'lineno')
print(top_stats[0:10])
打印结果:
[<StatisticDiff traceback=<Traceback (<Frame filename='/Users/opt/anaconda3/envs/python36/lib/python3.6/json/decoder.py' lineno=355>,)> size=10123317 (+9533677) count=304448 (+297771)>,
<StatisticDiff traceback=<Traceback (<Frame filename='/Users/opt/anaconda3/envs/python36/lib/python3.6/re.py' lineno=191>,)> size=44658 (+44658) count=387 (+387)>,
<StatisticDiff traceback=<Traceback (<Frame filename='/Users/PycharmProjects/algo-question/src/main.py' lineno=87>,)> size=25024 (+22784) count=391 (+356)>,
<StatisticDiff traceback=<Traceback (<Frame filename='/Users/PycharmProjects/algo-question/src/main.py' lineno=90>,)> size=3240 (+3240) count=1 (+1)>,
<StatisticDiff traceback=<Traceback (<Frame filename='/Users/opt/anaconda3/envs/python36/lib/python3.6/site-packages/sklearn/svm/_base.py' lineno=616>,)> size=3176 (+3176) count=2 (+2)>,
<StatisticDiff traceback=<Traceback (<Frame filename='/Users/opt/anaconda3/envs/python36/lib/python3.6/site-packages/pandas/core/indexes/base.py' lineno=409>,)> size=3840 (+1920) count=6 (+3)>,
<StatisticDiff traceback=<Traceback (<Frame filename='/Users/opt/anaconda3/envs/python36/lib/python3.6/site-packages/requests/utils.py' lineno=313>,)> size=2424 (+1344) count=26 (+21)>,
<StatisticDiff traceback=<Traceback (<Frame filename='/Users/opt/anaconda3/envs/python36/lib/python3.6/http/client.py' lineno=1209>,)> size=1344 (+1344) count=21 (+21)>,
<StatisticDiff traceback=<Traceback (<Frame filename='/Users/opt/anaconda3/envs/python36/lib/python3.6/site-packages/requests/structures.py' lineno=46>,)> size=1928 (+1200) count=13 (+10)>,
<StatisticDiff traceback=<Traceback (<Frame filename='/Users/opt/anaconda3/envs/python36/lib/python3.6/threading.py' lineno=237>,)> size=2320 (+1056) count=6 (+2)>]
结果显示的是你一次调用后,内存新增情况,比如:size=3176 (+3176)
就代表内存为3176,比上次新增3176,说明初始内存为0;
size=2424 (+1344) 表示初始内存 为1080, 内存有残留,当然最终要多运行几次来查看内存情况。
其他方法:
显示变量引用次数
print('sentences:{}'.format(sys.getrefcount(sentences)))
保存各个类型内存增长情况:
with open('log_del.txt', 'a+') as f:
objgraph.show_most_common_types(limit=50, file=f)
f.close()
打印内存增长情况:
objgraph.show_growth()
本文地址:https://blog.csdn.net/qq_34624315/article/details/109625625
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