jac*_*501 3 python performance
编辑:我运行了python profiler和两个最耗时的东西(这是在我决定注释掉webbrowser部分和Firefox部分代码之后,因为我知道它们将是最慢的部分......),我程序中最慢的部分是re.findall和re.compile(len)和(附加到列表).
我不知道是否应该立即在这里发布我的所有代码,因为我在我的程序上工作非常努力(即使它不太好),所以现在我只想问......怎么样如何让我的Python程序更快?
我现在有3个嫌犯,因为它太慢了:
也许我的电脑很慢
也许我的互联网太慢了(有时我的程序必须下载网页的html,然后通过html搜索特定的文本)
我的代码很慢(可能有太多循环?还有其他什么?我是新手,所以我不知道!)
如果有人能给我建议,我将非常感激!
谢谢!
编辑:
我认为我的代码使用了很多循环...另外,对于程序工作,你必须登录到这个网站:http://www.locationary.com/
from urllib import urlopen
from gzip import GzipFile
from cStringIO import StringIO
import re
import urllib
import urllib2
import webbrowser
import time
from difflib import SequenceMatcher
import os
def download(url):
s = urlopen(url).read()
if s[:2] == '\x1f\x8b': # assume it's gzipped data
with GzipFile(mode='rb', fileobj=StringIO(s)) as ifh:
s = ifh.read()
return s
for t in range(3,39):
print t
s = download('http://www.locationary.com/place/en/US/Utah/Provo-page' + str(t) + '/?ACTION_TOKEN=NumericAction')
findLoc = re.compile('http://www\.locationary\.com/place/en/US/.{1,50}/.{1,50}/.{1,100}\.jsp')
findLocL = re.findall(findLoc,s)
W = []
X = []
XA = []
Y = []
YA = []
Z = []
ZA = []
for i in range(0,25):
b = download(findLocL[i])
findYP = re.compile('http://www\.yellowpages\.com/')
findYPL = re.findall(findYP,b)
findTitle = re.compile('<title>(.*) \(\d{1,10}.{1,100}\)</title>')
getTitle = re.findall(findTitle,b)
findAddress = re.compile('<title>.{1,100}\((.*), .{4,14}, United States\)</title>')
getAddress = re.findall(findAddress,b)
if not findYPL:
if not getTitle:
print ""
else:
W.append(findLocL[i])
b = download(findLocL[i])
if not getTitle:
print ""
else:
X.append(getAddress)
b = download(findLocL[i])
if not getTitle:
print ""
else:
Y.append(getTitle)
sizeWXY = len(W)
def XReplace(text, dic):
for i, j in dic.iteritems():
text = text.replace(i, j)
XA.append(text)
def YReplace(text2, dic2):
for k, l in dic2.iteritems():
text2 = text2.replace(k, l)
YA.append(text2)
for d in range(0,sizeWXY):
old = str(X[d])
reps = {' ':'-', ',':'', '\'':'', '[':'', ']':''}
XReplace(old, reps)
old2 = str(Y[d])
YReplace(old2, reps)
count = 0
for e in range(0,sizeWXY):
newYPL = "http://www.yellowpages.com/" + XA[e] + "/" + YA[e] + "?order=distance"
v = download(newYPL)
abc = str('<h3 class="business-name fn org">\n<a href="')
dfe = str('" class="no-tracks url "')
findFinal = re.compile(abc + '(.*)' + dfe)
getFinal = re.findall(findFinal, v)
if not getFinal:
W.remove(W[(e-count)])
X.remove(X[(e-count)])
count = (count+1)
else:
for f in range(0,1):
Z.append(getFinal[f])
XA = []
for c in range(0,(len(X))):
aGd = re.compile('(.*), .{1,50}')
bGd = re.findall(aGd, str(X[c]))
XA.append(bGd)
LenZ = len(Z)
V = []
for i in range(0,(len(W))):
if i == 0:
countTwo = 0
gda = download(Z[i-(countTwo)])
ab = str('"street-address">\n')
cd = str('\n</span>')
ZAddress = re.compile(ab + '(.*)' + cd)
ZAddress2 = re.findall(ZAddress, gda)
for b in range(0,(len(ZAddress2))):
if not ZAddress2[b]:
print ""
else:
V.append(str(ZAddress2[b]))
a = str(W[i-(countTwo)])
n = str(Z[i-(countTwo)])
c = str(XA[i])
d = str(V[i])
#webbrowser.open(a)
#webbrowser.open(n)
m = SequenceMatcher(None, c, d)
if m.ratio() < 0.50:
Z.remove(Z[i-(countTwo)])
W.remove(W[i-(countTwo)])
countTwo = (countTwo+1)
def ZReplace(text3, dic3):
for p, q in dic3.iteritems():
text3 = text3.replace(p, q)
ZA.append(text3)
for y in range(0,len(Z)):
old3 = str(Z[y])
reps2 = {':':'%3A', '/':'%2F', '?':'%3F', '=':'%3D'}
ZReplace(old3, reps2)
for z in range(0,len(ZA)):
findPID = re.compile('\d{5,20}')
getPID = re.findall(findPID,str(W[z]))
newPID = re.sub("\D", "", str(getPID))
finalURL = "http://www.locationary.com/access/proxy.jsp?ACTION_TOKEN=proxy_jsp$JspView$SaveAction&inPlaceID=" + str(newPID) + "&xxx_c_1_f_987=" + str(ZA[z])
webbrowser.open(finalURL)
time.sleep(5)
os.system("taskkill /F /IM firefox.exe")
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Eri*_*got 32
程序缓慢时要做的第一件事就是找出瓶颈 ; 事实上,你想要优化需要很长时间的事情,而不是那些可能实际上很快的事情.在Python中,最有效的方式就是使用了一个Python的廓线,这对于性能分析的专用工具.这是一个快速入门:
python -m cProfile -o prof.dat <prog> <args>
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运行程序并在prof.dat中存储分析信息.然后,
python -m pstats prof.dat
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运行分析信息分析工具 pstats.重要的pstat命令包括:
sort time
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它按照在它们中花费的时间对函数进行排序,并且可以使用不同的键而不是time(cumulative,...)来使用它们.另一个重要的命令是
stats
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哪些打印统计(或stats 10打印前10个最耗时的功能).您可以获得帮助?,或help <command>.
优化程序的方法包括处理导致瓶颈的特定代码.您可以发布计时结果,也可以获得一些可以最有效优化的程序部分的更具体的帮助.