Python 绘制Android CPU和内存增长曲线

在做性能监控的时候,如果能把监控的CPU和内存增长变化用图表展示出来会比较直观,花了点时间用Python实现了下,来看下怎么用Python绘制Android CPU和内存变化曲线,生成增长曲线图表的PNG图片。


一、实现效果

一开始想通过采集的CPU和内存数据,导出到Excel生成增长曲线图表。做了下调研,并没有比较好的实现方法。后面看了下用Python来绘制图表实现起来挺容易的,而且Python的学习成本低,语法之类的做过开发的稍微看下就知道怎么用,容易上手。
具体实现的效果如下,CPU和内存采集的数据是独立进程的,内存分三块数据,应用总内存,Native内存和Dalvik内存,如果存在内存泄漏,要么在Native,要么在Dalvik,从图表增长曲线上很容易看出来。


二、具体逻辑实现详解


1. CPU图表的Python实现

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import json
import sys
import time
import traceback

def startDump():
  try:
    cpuData = json.loads(sys.argv[1])
    imagePath = sys.argv[2]
    cpuRateArray = []
    timeArray = []
    for cpuItem in cpuData:
      cpuRateArray.append(float(cpuItem["cpuRate"]))
      timeArray.append((float(float(cpuItem["time"]) - float(cpuData[0]["time"]))/1000))

    plt.title("Monitor Cpu Rate")
    plt.figure(figsize=(10, 8))
    plt.tight_layout()
    plt.plot(timeArray, cpuRateArray, c='red', label='Process CPU')
    plt.ylabel("CPURate (%)", fontsize=12)
    plt.xlabel("TimeRange:" + formatTime(float(cpuData[0]["time"])) + ' - ' + formatTime(float(cpuData[len(cpuData) -1]["time"])), fontsize=10)
    plt.legend()
    plt.savefig(imagePath)

  except Exception:
    print 'exeption occur:' + traceback.format_exc()

def formatTime(timeMillis):
  timeSeconds = float(timeMillis/1000)
  timelocal = time.localtime(timeSeconds)
  timeFormat = time.strftime("%Y-%m-%d %H:%M:%S", timelocal)
  return timeFormat

if __name__ == '__main__':
  startDump()


2. 内存图表的Python实现

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import json
import sys
import time
import traceback

def startDump():
  try:
    memoryData = json.loads(sys.argv[1])
    imagePath = sys.argv[2]
    totalPssArray = []
    nativePssArray = []
    dalvikPssArray = []
    timeArray = []
    for memoryItem in memoryData:
      totalPssArray.append(float(memoryItem["totalPss"])/1024)
      nativePssArray.append(float(memoryItem["nativePss"])/1024)
      dalvikPssArray.append(float(memoryItem["dalvikPss"])/1024)
      timeArray.append((float(float(memoryItem["time"]) - float(memoryData[0]["time"]))/1000))

    plt.title("Monitor Memory")
    plt.figure(figsize=(10, 8))
    plt.tight_layout()
    plt.plot(timeArray, totalPssArray, c='red', label='Total Memory')
    plt.plot(timeArray, nativePssArray, c='yellow', label='Native Memory')
    plt.plot(timeArray, dalvikPssArray, c='blue', label='Dalvik Memory')
    plt.ylabel("Memory (MB)", fontsize=12)
    plt.xlabel("TimeRange:" + formatTime(float(memoryData[0]["time"])) + ' - ' + formatTime(float(memoryData[len(memoryData) -1]["time"])), fontsize=10)
    plt.legend()
    plt.savefig(imagePath)

  except Exception:
    print 'exeption occur:' + traceback.format_exc()

def formatTime(timeMillis):
  timeSeconds = float(timeMillis/1000)
  timelocal = time.localtime(timeSeconds)
  timeFormat = time.strftime("%Y-%m-%d %H:%M:%S", timelocal)
  return timeFormat

if __name__ == '__main__':
  startDump()


3. 实现说明

脚本传入的参数有两个,一个是监控的JSON数据字符串值sys.argv[1],一个是保存的图片文件完整路径sys.argv[2]。关于传入的 JSON参数字符串值需要加上单引号修饰
,否则会导致解析异常,传入的JSON参数也 不能直接是JSON对象
,必须转化成字符串,示例调用命令如下:

python dump_chart.py  ''  cpu_chart.png 

1)采样CPU示例数据,time是设备的系统时间戳,CPU的占用率的计算可以查看前面写的: Android 性能监控之CPU监控

[
 {
 "time": "1589435564442.279053",
 "cpuRate": "2.17"
 },
 {
 "time": "1589435565655.333008",
 "cpuRate": "3.26"
 },
 {
 "time": "1589435566954.137939",
 "cpuRate": "2.52"
 },
 ...
]

2)采样内存示例数据,totalPss、nativePss和dalvikPss值都是从dumpsys meminfo输出的应用内存信息中截取出来的原始数据,对应“TOTAL”、“ Native Heap“、”

Dalvik Heap“字段的Pss Total值。内存信息的监控获取参考: Android 性能监控之内存监控

[
 {
 "time": "1589636256923.429932",
 "totalPss": 177804,
 "nativePss": 27922,
 "dalvikPss": 10212
 },
 {
 "time": "1589636258236.298096",
 "totalPss": 178021,
 "nativePss": 27850,
 "dalvikPss": 9990
 },
 {
 "time": "1589636259525.219971",
 "totalPss": 177899,
 "nativePss": 27742,
 "dalvikPss": 9990
 },
 ...
]


三、实现过程中遇到的问题


1. load方法使用错误

json.load ()方法使用错误,应该替换成
json.loads ()。

exeption occur:Traceback (most recent call last):
  File "*******", line 11, in startDump
    memoryData = json.load(sys.argv[1])
  File "/usr/local/Cellar/python@2/2.7.15_1/Frameworks/Python.framework/Versions/2.7/lib/python2.7/json/__init__.py", line 287, in load
    return loads(fp.read(),
AttributeError: 'str' object has no attribute 'read'


2. JSON字符串对象入参问题

  File "******", line 11, in startDump
    memoryData = json.loads(sys.argv[1])
  File "/usr/local/Cellar/python@2/2.7.15_1/Frameworks/Python.framework/Versions/2.7/lib/python2.7/json/__init__.py", line 339, in loads
    return _default_decoder.decode(s)
  File "/usr/local/Cellar/python@2/2.7.15_1/Frameworks/Python.framework/Versions/2.7/lib/python2.7/json/decoder.py", line 364, in decode
    obj, end = self.raw_decode(s, idx=_w(s, 0).end())
  File "/usr/local/Cellar/python@2/2.7.15_1/Frameworks/Python.framework/Versions/2.7/lib/python2.7/json/decoder.py", line 382, in raw_decode
    raise ValueError("No JSON object could be decoded")
ValueError: No JSON object could be decoded

针对Python脚本调用,JSON字符串对象作为入参,传入的JSON字符串对象 需要加单引号处理,比如在JavaScript中示例处理如下:

 '\'' + JSON.stringify(cpuRateJSON) + '\''


3. Python需要显示声明参数的类型

在Python中需要指明参数的类型,解析获取到JSON对象中的值之后,Python并不会根据参数来判断是什么类型,需要指明要转化的对象参数类型,比如把系统时间戳转化成float值类型:float(memoryData[0][“time”])

Traceback (most recent call last):
  File "*******", line 21, in startDump
    timeArray.append(timeStamp(memoryItem["time"]))
  File "*******", line 36, in timeStamp
    timeStamp = float(timeNum/1000)
TypeError: unsupported operand type(s) for /: 'unicode' and 'int'


4. 编码导致的异常

SyntaxError: Non-ASCII character '\xe5' in file ******* on line 24, but no encoding declared; see http://python.org/dev/peps/pep-0263/ for details

如果运行之后报如下的异常,说明是编码出问题,在脚本开头加上编码类型声明:

#!usr/bin/python
# -*- coding: utf-8 -*-


5. 保存的文件格式限制

plt.savefig (
image_path )
保存的文件格式只能是
eps ,
pdf ,
pgf ,
png ,
ps ,
raw ,
rgba ,
svg ,
svgz 这些,不支持
jpg 图片的保存。

Traceback (most recent call last):
  File "/Users/chenwenguan/Documents/AmapAuto/Project/arc-resources/script/performanceMonitor/dump_cpu_chart_image.py", line 23, in startDump
    plt.savefig(image_path)
  File "/usr/local/lib/python2.7/site-packages/matplotlib/pyplot.py", line 695, in savefig
    res = fig.savefig(*args, **kwargs)
  File "/usr/local/lib/python2.7/site-packages/matplotlib/figure.py", line 2062, in savefig
    self.canvas.print_figure(fname, **kwargs)
  File "/usr/local/lib/python2.7/site-packages/matplotlib/backend_bases.py", line 2173, in print_figure
    canvas = self._get_output_canvas(format)
  File "/usr/local/lib/python2.7/site-packages/matplotlib/backend_bases.py", line 2105, in _get_output_canvas
    .format(fmt, ", ".join(sorted(self.get_supported_filetypes()))))
ValueError: Format 'jpg' is not supported (supported formats: eps, pdf, pgf, png, ps, raw, rgba, svg, svgz)


6. python-tk 依赖

Traceback (most recent call last):
  File "*******", line 2, in 
    import matplotlib.pyplot as plt
  File "/home/arc/.local/lib/python2.7/site-packages/matplotlib/pyplot.py", line 115, in 
    _backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup()
  File "/home/arc/.local/lib/python2.7/site-packages/matplotlib/backends/__init__.py", line 63, in pylab_setup
    [backend_name], 0)
  File "/home/arc/.local/lib/python2.7/site-packages/matplotlib/backends/backend_tkagg.py", line 4, in 
    from . import tkagg  # Paint image to Tk photo blitter extension.
  File "/home/arc/.local/lib/python2.7/site-packages/matplotlib/backends/tkagg.py", line 5, in 
    from six.moves import tkinter as Tk
  File "/home/arc/.local/lib/python2.7/site-packages/six.py", line 203, in load_module
    mod = mod._resolve()
  File "/home/arc/.local/lib/python2.7/site-packages/six.py", line 115, in _resolve
    return _import_module(self.mod)
  File "/home/arc/.local/lib/python2.7/site-packages/six.py", line 82, in _import_module
    __import__(name)
  File "/usr/lib/python2.7/lib-tk/Tkinter.py", line 42, in 
    raise ImportError, str(msg) + ', please install the python-tk package'

缺少
python-tk依赖,执行一下命令安装:

sudo apt-get install python-tk


7. Agg画布初始化配置

Traceback (most recent call last):
  File "******", line 22, in startDump
    plt.title("ARC Monitor Memory")
  File "/home/arc/.local/lib/python2.7/site-packages/matplotlib/pyplot.py", line 1419, in title
    return gca().set_title(s, *args, **kwargs)
  File "/home/arc/.local/lib/python2.7/site-packages/matplotlib/pyplot.py", line 969, in gca
    return gcf().gca(**kwargs)
  File "/home/arc/.local/lib/python2.7/site-packages/matplotlib/pyplot.py", line 586, in gcf
    return figure()
  File "/home/arc/.local/lib/python2.7/site-packages/matplotlib/pyplot.py", line 533, in figure
    **kwargs)
  File "/home/arc/.local/lib/python2.7/site-packages/matplotlib/backend_bases.py", line 161, in new_figure_manager
    return cls.new_figure_manager_given_figure(num, fig)
  File "/home/arc/.local/lib/python2.7/site-packages/matplotlib/backends/_backend_tk.py", line 1046, in new_figure_manager_given_figure
    window = Tk.Tk(className="matplotlib")
  File "/usr/lib/python2.7/lib-tk/Tkinter.py", line 1828, in __init__
    self.tk = _tkinter.create(screenName, baseName, className, interactive, wantobjects, useTk, sync, use)
TclError: no display name and no $DISPLAY environment variable

在Mac上运行的时候不会出现这个问题,但在Ubuntu环境下运行的时候就报异常了, 官网的解释
如下:

When using Matplotlib versions older than 3.1, it is necessary to explicitly instantiate an Agg canvas

在脚本文件开头显示声明Agg使用:

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt


8. pyecharts 版本配置问题

如果不是用Python原生方式绘图,而是用pyecharts来绘制图表,要注意下Python版本的匹配。 pyecharts v1.0.0
停止对
Python2.7
3.4~3.5 版本的支持和维护,仅支持
Python3.6+。

Traceback (most recent call last):
  File "*******", line 11, in 
    from pyecharts import options as opts
  File "/usr/local/lib/python2.7/site-packages/pyecharts/__init__.py", line 1, in 
    from pyecharts import charts, commons, components, datasets, options, render, scaffold
  File "/usr/local/lib/python2.7/site-packages/pyecharts/charts/__init__.py", line 2, in 
    from ..charts.basic_charts.bar import Bar
  File "/usr/local/lib/python2.7/site-packages/pyecharts/charts/basic_charts/bar.py", line 17
    series_name: str,
               ^
SyntaxError: invalid syntax


四、参考资料




Python

绘制计算机
CPU

占有率变化的折线图



python

pyecharts
绘制各种图表详细(代码)




python
绘制
cpu
曲线



python/matlibplot
绘制多条曲线图


Parser for command-line options, arguments and sub-commands


python 毫秒级时间,时间戳转换

扩展阅读:


Android 性能监控之内存监控


Android 性能监控之CPU监控


转载请注明出处:陈文管的博客–  Python 绘制Android CPU和内存增长曲线

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