用memory_profiler 监控内存耗用
用于搜索某些文件，比如后缀是.py、.mp3等文件，endswith(".py")即可
root@WJL-SH4031667:/mnt/d/Downloads# cat getspecFile.py
python hljs 19行
from os import walk
from os.path import join,getmtime
@profile
def scan():
ret = {}
for path, _, files in walk("./"):
for f in files:
if not f.endswith(""):
continue
filename = join(path, f)
ret[filename] = getmtime(filename)
return ret
if __name__ == "__main__":
print(len(scan().keys())个文件)
一. 每行代码的内存损耗
root@WJL-SH4031667:/mnt/d/Downloads # python -m memory_profiler getspecFile.py
230073个文件
Filename: getspecFile.py
python hljs 17行
mem-usage列中使用了约96M的内存， increment 增量列中为什么会出现负数，不知道
Line # Mem usage Increment Line Contents
================================================
4 29.785 MiB 29.785 MiB @profile
5 def scan():
6 29.789 MiB 0.004 MiB ret = {}
7 96.504 MiB -4610.625 MiB for path, _, files in walk("./"):
8 96.504 MiB -33928.625 MiB for f in files:
9 96.504 MiB -29646.871 MiB if not f.endswith(""):
10 continue
11
12 96.504 MiB -29647.805 MiB filename = join(path, f)
13 96.504 MiB -29609.523 MiB ret[filename] = getmtime(filename)
14
15 96.504 MiB 0.000 MiB return ret
二. 生成内存损耗曲线图表
1. 首先安装pylab
root@WJL-SH4031667:/mnt/d/Downloads # pip install matplotlib
python hljs 23行
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
Collecting matplotlib
Downloading https://pypi.tuna.tsinghua.edu.cn/packages/b2/58/5842588fa67b45ffb451c4c98eda283c0c42b8f2c5e503e4f6d9ff3c3a63/matplotlib-3.0.1-cp35-cp35m-manylinux1_x86_64.whl (12.9MB)
100% |████████████████████████████████| 12.9MB 821kB/s
Collecting cycler>=0.10 (from matplotlib)
Downloading https://pypi.tuna.tsinghua.edu.cn/packages/f7/d2/e07d3ebb2bd7af696440ce7e754c59dd546ffe1bbe732c8ab68b9c834e61/cycler-0.10.0-py2.py3-none-any.whl
Collecting numpy>=1.10.0 (from matplotlib)
Downloading https://pypi.tuna.tsinghua.edu.cn/packages/98/d6/ebc4f752b683d190361248ecce4d5a0977b5c483370aa7ff63b733e8f011/numpy-1.15.3-cp35-cp35m-manylinux1_x86_64.whl (13.8MB)
100% |████████████████████████████████| 13.8MB 690kB/s
Collecting pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 (from matplotlib)
Downloading https://pypi.tuna.tsinghua.edu.cn/packages/2b/4a/f06b45ab9690d4c37641ec776f7ad691974f4cf6943a73267475b05cbfca/pyparsing-2.2.2-py2.py3-none-any.whl (57kB)
100% |████████████████████████████████| 61kB 1.7MB/s
Collecting python-dateutil>=2.1 (from matplotlib)
Downloading https://pypi.tuna.tsinghua.edu.cn/packages/74/68/d87d9b36af36f44254a8d512cbfc48369103a3b9e474be9bdfe536abfc45/python_dateutil-2.7.5-py2.py3-none-any.whl (225kB)
100% |████████████████████████████████| 235kB 1.6MB/s
Collecting kiwisolver>=1.0.1 (from matplotlib)
Downloading https://pypi.tuna.tsinghua.edu.cn/packages/7e/31/d6fedd4fb2c94755cd101191e581af30e1650ccce7a35bddb7930fed6574/kiwisolver-1.0.1-cp35-cp35m-manylinux1_x86_64.whl (949kB)
100% |████████████████████████████████| 952kB 2.7MB/s
Requirement already satisfied: six in /usr/lib/python3/dist-packages (from cycler>=0.10->matplotlib) (1.10.0)
Requirement already satisfied: setuptools in /usr/lib/python3/dist-packages (from kiwisolver>=1.0.1->matplotlib) (20.7.0)
Installing collected packages: cycler, numpy, pyparsing, python-dateutil, kiwisolver, matplotlib
Successfully installed cycler-0.10.0 kiwisolver-1.0.1 matplotlib-3.0.1 numpy-1.15.3 pyparsing-2.2.2 python-dateutil-2.7.5
2. 用mprof 来生成一个.dat文件，里面记录了内存的损耗
root@WJL-SH4031667:/mnt/d/Downloads # mprof run getspecFile.py
python hljs 4行
mprof: Sampling memory every 0.1s
running as a Python program...
230074个文件
3. 查看生成的dat文件
root@WJL-SH4031667:/mnt/d/Downloads # ls *.dat -l
-rwxrwxrwx 1 root root 25035 Oct 31 08:54 mprofile_20181031085302.dat
root@WJL-SH4031667:/mnt/d/Downloads # more mprofile_20181031085302.dat
python hljs 31行
CMDLINE /usr/bin/python3 getspecFile.py
MEM 0.257812 1540947182.6013
MEM 8.792969 1540947182.7021
MEM 12.125000 1540947182.8037
MEM 15.257812 1540947182.9046
MEM 17.632812 1540947183.0055
MEM 21.906250 1540947183.1060
MEM 24.519531 1540947183.2068
MEM 26.437500 1540947183.3075
MEM 29.242188 1540947183.4081
MEM 29.722656 1540947183.5088
MEM 29.929688 1540947183.6097
MEM 29.984375 1540947183.7102
MEM 29.996094 1540947183.8110
MEM 30.164062 1540947183.9120
MEM 30.179688 1540947184.0127
MEM 30.332031 1540947184.1137
MEM 30.339844 1540947184.2145
MEM 30.339844 1540947184.3152
MEM 30.339844 1540947184.4160
MEM 30.527344 1540947184.5168
MEM 30.527344 1540947184.6176
MEM 30.527344 1540947184.7184
MEM 30.539062 1540947184.8191
MEM 30.562500 1540947184.9199
MEM 30.578125 1540947185.0207
MEM 30.582031 1540947185.1214
MEM 30.605469 1540947185.2225
MEM 30.625000 1540947185.3231
...
4. 生成内存图
root@WJL-SH4031667:/mnt/d/Downloads # mprof plot
Using last profile data.
效果图