python performance profiling

']= "k.tcp.conn[established]" forx,y initems.items ():printx,y,dip os.system (' mkdir-p/data/zabbix/cvs/%s ' %dip) cmds= "" " python/data/zabbix/fetch_items_to_csv.py-s '%s ' -n '%s ' -k '%s ' -u '%s ' -p '%s ' -t1 ' 2015-06-2300:00:01 ' -t2 ' 2015-06-30 00:00:01 ' -o/data/zabbix/cvs/%s/%s_%s.cvs "" "% (moniter,dip,y,users,pawd,dip,dip,x) os.system (CMDS) def work (): NBSP;NBSP;NBsp;moniter= ' 192.168.1.1 ' ip_list=[' 192.168.1.11 ', ' 192.168.1.2

Python monitors process performance data and saves it as a PDF file,Introduction Psutil module (https://pypi.python.org/pypi/psutil/) can be very convenient to monitor the system CPU, memory, disk I/O, network bandwidth and other performance parameters, the following code is to monitor a specific program of CPU resource consumption, print the monitoring data, dis

Solution 2: optimize the code To do well, you must first sharpen your tools. To optimize the code, you must first find the bottleneck of the Code. The most common method is to add log or print, and delete the code after debugging is complete, which is troublesome. Python also provides many profile tools: profile, cProfile, hotshot, and pystats. However, these tools provide poor readability, the function or row takes the most time at a glance.

Some scenarios for improving Python performance. Function call optimization (space span, avoid access to memory) The key point of program optimization is to minimize the operation span, including the span of code execution time and the space span in memory. 1. Large data summation, using sum A = range (100000) %timeit-n sum (a) loops, Best of 3:3.15 ms per loop %%timeit ...: s = 0 ...: For I

Recently learning Golang, always want to experience the next concurrency in the end have more, will I big python strong how much. Learned the official tutorial HTTP service, using the Performance test Tool WRK test, found the result is very surprising ~WRK can refer to my blog, there are basic usage notes: http://blog.yuanzhaoyi.cn/2018/01/12/test.htmlTest command: wrk-t10-d1m-c200 http://127.0.0.1:8080Mean

New in many ways Python performance optimizations see the value of swapping two variables can be usedA, B = b,aThis can improve performance>>> from Timeit import timer>>> Timer ("t=a;a=b;b=t", "a=1;b=2"). Timeit () 0.06279781319366587> >> Timer ("A,b=b,a", "a=1;b=2"). Timeit () 0.0378979925538232>>>From the running time, it really saved half the time.Get

;> c = Circle(2)>>> print c.areaComputing area12.5663706144>>> print c.area12.5663706144 "Computing area" is printed every time calculated in area (). after calling c. area twice in a row, "Computing area" is printed only once. This benefits from LazyProperty. after a call, no matter how many subsequent calls are called, the calculation will not be repeated. --> The above is a detailed description of delayed initialization for Python

The garbage Collection, GC) mechanism used by Python is the reference count (Reference count), which is the principle of a reference count for each memory object, so that when a large number of objects are created or deleted, it is necessary to make a large number of modifications to the reference count. Affect the performance of the program. To prevent this from happening, you can disable the GC before a l

Python comes with several performance Analysis modules: Profile, Cprofile, and Hotshot, all of which are basically the same way, nothing more than a pure Python or C-written module. This article describes cprofile.ExampleImport Time def func1 (): = 0 for in range (1000000): + = idef Func2 (): time.sleep (ten) func1 () Func2 ()Rundel. pyRun res

running and putting load on. Execute commandMake an AJAX request, agent asynchronous processing, return to the library, and then use AJAX dynamic call database API display 650) this.width=650; "src=" http://s3.51cto.com/wyfs02/M00/6F/00/wKioL1WPaBmwynchAAKYmIduKQg139.jpg "style=" float: none; "title=" 10.jpg "alt=" Wkiol1wpabmwynchaakymidukqg139.jpg "/> Summary:This architecture is very flexible, arbitrary disassembly splicing, if small, can function integrated in a little, if large, can a

Because the Node. js version of the Fl engine is considered in the future, the character processing performance of Node. js and PHP is compared. I found that Node. js really dumped several streets in PHP and tested Python again, which is slower than PHP. Test Cases are divided into functions and classes for reading a large string of characters one by one. Test code Node. js Function var fs = require("fs")

(thinktime) #print"Thread%s"%T #打印线程 T.setdaemon (True) T.start () t.join () Endtime=Datetime.datetime.now () print"Request End Time%s"%Endtime Time.sleep (3) Averagetime="{:. 3f}". Format (float(SUM (myreq.times))/float(Len (myreq.times))) #计算数组的平均值, retain 3 decimal places print"Average Response Time%s Ms"%averagetime #打印平均响应时间 usetime= STR (Endtime-starttime) Hour= Usetime.split (':'). Pop (0) Minute= Usetime.split (':'). Pop (1) Second= Usetime.split (':'). Pop (2) TotalTime=float(Hour) * -

Comparison of Character Processing Performance between Node. js and PHP and Python, node. jspython Test Cases are divided into functions and classes for reading a large string of characters one by one. Test code Node. js Function var fs = require("fs");var content = fs.readFileSync("page.html", { encoding: "utf-8"});function chars(content){ var length = content.length; var pos = 0; while(pos ++ Class var f

Modify the main loop in Python pyxmpp2 to improve its performance. Introduction Previously, the default mainloop of pyxmpp2 used by clubot is a main loop of poll. However, after clubot went online, the resource usage was very high. Using strace tracking, we found that clubot was continuously running poll, check the pyxmpp2 code and find that poll of pyxmpp2 uses the minimum timeout time when timeout blockin

==I:number=I BreakCount+=1ifNumber==-1: Print 'None' Else: date[1][count]=raw_input ('Please your name:') date[2][count]=raw_input ('Please your 中文版:') date[3][count]=raw_input ('Please your math:') date[4][count]=raw_input ('Your science:')defallprint (date): Count=Len (date[0])ifcount==0:Print'None' Else: forIinchRange (count): Printone (base,i)defDeletebyid (date): number=-1Count=0 Key=raw_input ('Please enter your ID') forIinchDate[0]:ifkey==I:number=I BreakCount+=1i

Method 01:# #利用python的标准库cProfile# #nova/api/openstack/wsgi.pyImport TimeImportCProfile, pstats, Stringio fromOslo_middlewareImportREQUEST_IDPR=cprofile.profile () pr.enable () start_time=time.time () dosomething () End_time=time.time () pr.disable () s=Stringio.stringio () sortby='Cumulative'PS= Pstats. Stats (PR, stream=s). Sort_stats (SortBy) ps.print_stats () req_id=Request.environ.get (request_id. ENV_REQUEST_ID) P= Open ("/tmp/test/"+ STR (req_i

Mem%"'+ start_date +"00:00:00\ ""+end_date+'23:59:00 "--xls/root/reports/freemem.xls >/dev/null' #Print Cmd_memOs.popen (cmd_mem) Cmd_disk='nohup zabbix_api--report "free disk space on"'+ start_date +"00:00:00\ ""+end_date+'23:59:00 "--xls/root/reports/freedisk.xls >/dev/null' #Print Cmd_diskOs.popen (Cmd_disk)if __name__=='__main__': Date_range=Get_date_range ()#Print Date_range Print 'begin generating Reports In/root/reports ...'gen_report_files (Date_range)A

"" "" "" "" "" "" "" "" "" "" "" "" "" "" "" "" "", "" "". "" "" "" "" "" "" "" "," "" "" "," "" "" "," "" "," "" ">> Disk Information .py>> Author: Liu Yang>> e-mail: [emailprotected] "" "" "" "" "" "" "" "" "" "" "" "" "" "" "" "." "" "" "" "" "" "" "" "" "" "" "" "" "" "" "" "" #!/usr/bin/env python#-*-coding:utf-8-*-import sys,osimport Psutilfrom Time Import sleep ' judgment Platform ' def Platform_judge (): # Returns the platform Information lowe