用Python的Flask框架结合MySQL写一个内存监控程序-Python教學-PHP中文網

首頁

後端開發

Python教學

用Python的Flask框架结合MySQL写一个内存监控程序

WBOYWBOYWBOYWBOYWBOYWBOYWBOYWBOYWBOYWBOYWBOYWBOYWB

Jun 10, 2016 pm 03:07 PM

flaskmysql

这里以监控内存使用率为例，写的一个简单demo性程序，具体操作根据51reboot提供的教程写如下。

一、建库建表

创建falcon数据库：

mysql> create database falcon character set utf8;
Query OK, 1 row affected (0.00 sec)

创建内存监控使用的表stat，表结构如下：

CREATE TABLE `stat` (
 `id` int(11) unsigned NOT NULL AUTO_INCREMENT,
 `host` varchar(256) DEFAULT NULL,
 `mem_free` int(11) DEFAULT NULL,
 `mem_usage` int(11) DEFAULT NULL,
 `mem_total` int(11) DEFAULT NULL,
 `load_avg` varchar(128) DEFAULT NULL,
 `time` bigint(11) DEFAULT NULL,
 PRIMARY KEY (`id`),
 KEY `host` (`host`(255))
) ENGINE=InnoDB AUTO_INCREMENT=0 DEFAULT CHARSET=utf8;

二、flask web端设置

首先我们设计一个web服务，实现如下功能：

完成监控页面展示
接受POST提交上来的数据
提供json数据GET接口
具体框架结构图如下：

2015117174700956.png (907×380)

目录结构如下：

web
├── flask_web.py
└── templates
 └── mon.html

flask_web代码如下：

import MySQLdb as mysql
import json
from flask import Flask, request, render_template
app = Flask(__name__)
db = mysql.connect(user="361way", passwd="123456", \
  db="falcon", charset="utf8")
db.autocommit(True)
c = db.cursor()
@app.route("/", methods=["GET", "POST"])
def hello():
 sql = ""
 if request.method == "POST":
  data = request.json
  try:
   sql = "INSERT INTO `stat` (`host`,`mem_free`,`mem_usage`,`mem_total`,`load_avg`,`time`) VALUES('%s', '%d', '%d', '%d', '%s', '%d')" % (data['Host'], data['MemFree'], data['MemUsage'], data['MemTotal'], data['LoadAvg'], int(data['Time']))
   ret = c.execute(sql)
  except mysql.IntegrityError:
   pass
  return "OK"
 else:
  return render_template("mon.html")
@app.route("/data", methods=["GET"])
def getdata():
 c.execute("SELECT `time`,`mem_usage` FROM `stat`")
 ones = [[i[0]*1000, i[1]] for i in c.fetchall()]
 return "%s(%s);" % (request.args.get('callback'), json.dumps(ones))
if __name__ == "__main__":
 app.run(host="0.0.0.0", port=8888, debug=True)

这里使用的汇图JS为highcharts、highstock ，具体模板页面内容如下：

[root@91it templates]# cat mon.html

<title>memory monitor</title>
<!DOCTYPE HTML>
<html>
 <head>
  <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
  <title>Highstock Example</title>
  <!-- <script type="text/javascript" src="{{ url_for('static', filename='jquery.min.js') }}"></script> -->
  <script type="text/javascript" src="http://ajax.useso.com/ajax/libs/jquery/1.8.2/jquery.min.js"></script>
  <style type="text/css">
${demo.css}
  </style>
  <script type="text/javascript">
$(function () {
 $.getJSON('/data&#63;callback=&#63;', function (data) {
  // Create the chart
  $('#container').highcharts('StockChart', {
   rangeSelector: {
    inputEnabled: $('#container').width() > 480,
    selected: 1
   },
   title: {
    text: 'memory monitor'
   },
   series: [{
    name: 'memory monitor',
    data: data,
    type: 'spline',
    tooltip: {
     valueDecimals: 2
    }
   }]
  });
 });
});
  </script>
 </head>
 <body>
<!-- <script src="{{ url_for('static', filename='highstock.js') }}"></script> -->
<script src="http://cdnjs.cloudflare.com/ajax/libs/highstock/2.0.4/highstock.js"></script>
<!-- <script src="{{ url_for('static', filename='exporting.js') }}"></script> -->
<script src="http://code.highcharts.com/modules/exporting.js"></script>
<div id="container" style="height: 400px"></div>
 </body>
</html>

注：这里的JS代码都直接使用互联网上的代码，如果主机无法连接互联网的，可以将上面的三段代取取下来，在templates 的同级目录创建static 目录，将下载下来的三个文件放到该目录，删除模板中三处引用javascript处的代码，使用当前注释的三段。

三、agent被监控端设置

web展示页面完成了，运行起来：python flask_web.py 监听在8888端口上。我们需要做一个agent来采集数据，并通过post方法请求flask_web页面，将数据上传写入数据库。这里以监控内存为例，具体监控代码如下：

#!/usr/bin/env python
#coding=utf-8
import inspect
import time
import urllib, urllib2
import json
import socket
class mon:
 def __init__(self):
  self.data = {}
 def getTime(self):
  return str(int(time.time()) + 8 * 3600)
 def getHost(self):
  return socket.gethostname()
 def getLoadAvg(self):
  with open('/proc/loadavg') as load_open:
   a = load_open.read().split()[:3]
   return ','.join(a)
 def getMemTotal(self):
  with open('/proc/meminfo') as mem_open:
   a = int(mem_open.readline().split()[1])
   return a / 1024
 def getMemUsage(self, noBufferCache=True):
  if noBufferCache:
   with open('/proc/meminfo') as mem_open:
    T = int(mem_open.readline().split()[1])
    F = int(mem_open.readline().split()[1])
    B = int(mem_open.readline().split()[1])
    C = int(mem_open.readline().split()[1])
    return (T-F-B-C)/1024
  else:
   with open('/proc/meminfo') as mem_open:
    a = int(mem_open.readline().split()[1]) - int(mem_open.readline().split()[1])
    return a / 1024
 def getMemFree(self, noBufferCache=True):
  if noBufferCache:
   with open('/proc/meminfo') as mem_open:
    T = int(mem_open.readline().split()[1])
    F = int(mem_open.readline().split()[1])
    B = int(mem_open.readline().split()[1])
    C = int(mem_open.readline().split()[1])
    return (F+B+C)/1024
  else:
   with open('/proc/meminfo') as mem_open:
    mem_open.readline()
    a = int(mem_open.readline().split()[1])
    return a / 1024
 def runAllGet(self):
  #自动获取mon类里的所有getXXX方法，用XXX作为key，getXXX()的返回值作为value，构造字典
  for fun in inspect.getmembers(self, predicate=inspect.ismethod):
   if fun[0][:3] == 'get':
    self.data[fun[0][3:]] = fun[1]()
  return self.data
if __name__ == "__main__":
 while True:
  m = mon()
  data = m.runAllGet()
  print data
  req = urllib2.Request("http://test.361way.com:8888", json.dumps(data), {'Content-Type': 'application/json'})
  f = urllib2.urlopen(req)
  response = f.read()
  print response
  f.close()
  time.sleep(60)

nohup python moniItems.py >/dev/null 2>&1 & 在被监控主机上运行，如果出于实验目的，想尽快的看到展示效果，可以将time.sleep(60) 改为time.sleep(2) ，这样每2秒就会取一次数据写入数据库。

访问 http://test.361way.com:8888 就可以看到我们的监控数据了：效果图如下

2015117175842218.png (793×435)

highcharts支持将按时间拖动，也支持按指定时间段查看。并且查看到的图片可以直接保存为png、jpg或pdf、csv等格式查看。

陳述

本文內容由網友自願投稿，版權歸原作者所有。本站不承擔相應的法律責任。如發現涉嫌抄襲或侵權的內容，請聯絡admin@php.cn

Python：編譯器還是解釋器？May 13, 2025 am 12:10 AM

Python是解釋型語言，但也包含編譯過程。 1）Python代碼先編譯成字節碼。 2）字節碼由Python虛擬機解釋執行。 3）這種混合機制使Python既靈活又高效，但執行速度不如完全編譯型語言。

python用於循環與循環時：何時使用哪個？May 13, 2025 am 12:07 AM

UseeAforloopWheniteratingOveraseQuenceOrforAspecificnumberoftimes; useAwhiLeLoopWhenconTinuingUntilAcIntiment.forloopsareIdealForkNownsences，而WhileLeleLeleLeleLeleLoopSituationSituationsItuationsItuationSuationSituationswithUndEtermentersitations。

Python循環：最常見的錯誤May 13, 2025 am 12:07 AM

pythonloopscanleadtoerrorslikeinfiniteloops，modifyingListsDuringteritation，逐個偏置，零indexingissues，andnestedloopineflinefficiencies

對於循環和python中的循環時：每個循環的優點是什麼？May 13, 2025 am 12:01 AM

forloopsareadvantageousforknowniterations and sequests，供應模擬性和可讀性；而LileLoopSareIdealFordyNamicConcitionSandunknowniterations，提供ControloperRoverTermination.1）forloopsareperfectForeTectForeTerToratingOrtratingRiteratingOrtratingRitterlistlistslists，callings conspass，calplace，cal，ofstrings ofstrings，orstrings，orstrings，orstrings ofcces

Python：深入研究彙編和解釋May 12, 2025 am 12:14 AM

pythonisehybridmodeLofCompilation和interpretation：1）thepythoninterpretercompilesourcecececodeintoplatform- interpententbybytecode.2）thepythonvirtualmachine（pvm）thenexecutecutestestestestestesthisbytecode，ballancingEaseofuseEfuseWithPerformance。

Python是一種解釋或編譯語言，為什麼重要？May 12, 2025 am 12:09 AM

pythonisbothinterpretedAndCompiled.1）它的compiledTobyTecodeForportabilityAcrosplatforms.2）bytecodeisthenInterpreted，允許fordingfordforderynamictynamictymictymictymictyandrapiddefupment，儘管Ititmaybeslowerthananeflowerthanancompiledcompiledlanguages。

對於python中的循環時循環與循環：解釋了關鍵差異May 12, 2025 am 12:08 AM

在您的知識之際，而foroopsareideal insinAdvance中，而WhileLoopSareBetterForsituations則youneedtoloopuntilaconditionismet

循環時：實用指南May 12, 2025 am 12:07 AM

ForboopSareSusedwhenthentheneMberofiterationsiskNownInAdvance，而WhileLoopSareSareDestrationsDepportonAcondition.1）ForloopSareIdealForiteratingOverSequencesLikelistSorarrays.2）whileLeleLooleSuitableApeableableableableableableforscenarioscenarioswhereTheLeTheLeTheLeTeLoopContinusunuesuntilaspecificiccificcificCondond

See all articles