一篇文章教小白会Python 绘制Android CPU和内存增长曲线

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一篇文章教小白会Python 绘制android CPU和内存增长曲线

🏳️‍🌈目录

😊开讲啦！！！！

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。
在这里插入图片描述

🏳️‍🌈1、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。
在这里插入图片描述
在这里插入图片描述

🏳️‍🌈2、具体逻辑实现详解

😉2.1、CPU图表的Python实现

代码如下：

# -*- coding: utf-8 -*-

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.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.tight_layout()
    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()

😉2.2、内存图表的Python实现

代码如下：

# -*- coding: utf-8 -*-

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.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.tight_layout()
    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  '<JSONString>'  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后面具题写的：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。

[
 {
 "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
 },
 ...
]

😉3.1、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) + '\\''

3.3、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 <module>
    import matplotlib.pyplot as plt
  File "/home/arc/.local/lib/python2.7/site-packages/matplotlib/pyplot.py", line 115, in <module>
    _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 <module>
    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 <module>
    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 <module>
    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 -y 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 <module>
    from pyecharts import options as opts
  File "/usr/local/lib/python2.7/site-packages/pyecharts/__init__.py", line 1, in <module>
    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 <module>
    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

🏳️‍🌈9、图像显示不全问题

测试过程中发现依次保存CPU和内存数据，可能会出现其中一张图片显示有缺失，只显示一半图像内容。在matplotlib中，轴Axes的位置以标准化图形坐标指定，可能发生的情况是轴标签、标题、刻度标签等等会超出图形区域，导致显示不全。后面加上tight_layout自适应调用之后问题修复。tight_layout会自动调整子图参数，使之填充整个图像区域。

plt.tight_layout()

❤️‍🔥后续需要关注的文章：

Android 性能监控之内存监控

Android 性能监控之CPU监控

在这里插入图片描述

关注苏州程序大白，持续更新技术分享。谢谢大家支持

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