有没有办法让我的Python程序运行得更快?

Joh*_*ley 0 python performance

我在python中编写了一个计算机程序,但运行速度比我想要的慢得多.

这是代码:

from gzip import GzipFile
from cStringIO import StringIO
import re
import webbrowser
import time
from difflib import SequenceMatcher
import os
import sys
from BeautifulSoup import BeautifulSoup
import eventlet
from eventlet.green import urllib2
import urllib
import urllib2
import cookielib

TITLE_MATCH = re.compile(r'(.*) \(\d{1,10}.{1,100}\)$')
ADDRESS_MATCH = re.compile(r'.{1,100}\((.*), .{4,14}, United States\)$')
LOCATION_LISTING = re.compile(r'http://www\.locationary\.com/place/en/US/.{1,50}/.{1,50}/.{1,100}\.jsp')

def download(url):
    print "Downloading:", url
    s = urllib2.urlopen(url).read()
    if s[:2] == '\x1f\x8b': # assume it's gzipped data
        ifh = GzipFile(mode='rb', fileobj=StringIO(s))
        s = ifh.read()
    print "Downloaded: ", url
    return s

def replace_chars(text, replacements):
    return ''.join(replacements.get(x,x) for x in text)

def handle_listing(listing_url):
    listing_document = BeautifulSoup(download(listing_url))

    # ignore pages that link to yellowpages
    if not listing_document.find("a", href=re.compile(re.escape("http://www.yellowpages.com/") + ".*")):
        listing_title = listing_document.title.text
        reps = {' ':'-', ',':'', '\'':'', '[':'', ']':''}
        if TITLE_MATCH.match(listing_title) is not None:
            title, = TITLE_MATCH.match(listing_title).groups()
            address, = ADDRESS_MATCH.match(listing_title).groups()

            yellow_page_url = "http://www.yellowpages.com/%s/%s?order=distance" % (
                replace_chars(address, reps),
                replace_chars(title, reps),
            )

            yellow_page = BeautifulSoup(download(yellow_page_url))

            page_url = yellow_page.find("h3", {"class" : "business-name fn org"})
            if page_url:
                page_url = page_url.a["href"]

                business_name = title[:title.index(",")]

                page = BeautifulSoup(download(page_url))
                yellow_page_address =  page.find("span", {"class" : "street-address"})
                if yellow_page_address:

                    if SequenceMatcher(None, address, yellow_page_address.text).ratio() >= 0.5:
                        pid, = re.search(r'p(\d{5,20})\.jsp', listing_url).groups(0)
                        page_escaped = replace_chars(page_url, {':':'%3A', '/':'%2F', '?':'%3F', '=':'%3D'})

                        final_url = "http://www.locationary.com/access/proxy.jsp?ACTION_TOKEN=proxy_jsp$JspView$SaveAction&inPlaceID=%s&xxx_c_1_f_987=%s" % (
                                pid, page_escaped)
                        return final_url

def log_in(final_url):
    data = urllib.urlencode({"inUserName":"jacob.grannis@gmail.com", "inUserPass":"secretword"})
    jar = cookielib.FileCookieJar("cookies")
    opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(jar))
    opener.addheaders.append(('User-agent', 'Mozilla/4.0'))
    opener.addheaders.append(('Referer', 'http://www.locationary.com/'))
    opener.addheaders.append(('Cookie','site_version=REGULAR; __utma=47547066.912030359.1322003402.1324959960.1325009956.58; __utmz=47547066.1324655802.52.13.utmcsr=google|utmccn=(organic)|utmcmd=organic|utmctr=cache:dr23PN5fUj4J:www.locationary.com/%20locationary; nickname=jacob501; jforumUserId=1; PMS=1; locaCountry=1033; locaState=1786; locaCity=Vancouver; JSESSIONID=5CDDA2D527C20A6CDD04936115DE3FA2; PSESSIONID=c677beb4e6b8d58f1443d9b9585b225f579ef29a; Locacookie=enable; __utmb=47547066.1.10.1325009956; __utmc=47547066'))
    opener.addheaders.append(('Cookie','Cookie: site_version=REGULAR; __utma=47547066.912030359.1322003402.1324959960.1325009956.58; __utmz=47547066.1324655802.52.13.utmcsr=google|utmccn=(organic)|utmcmd=organic|utmctr=cache:dr23PN5fUj4J:www.locationary.com/%20locationary; nickname=jacob501; jforumUserId=1; PMS=1; locaCountry=1033; locaState=1786; locaCity=Vancouver; JSESSIONID=5CDDA2D527C20A6CDD04936115DE3FA2; PSESSIONID=c677beb4e6b8d58f1443d9b9585b225f579ef29a; Locacookie=enable; __utmb=47547066.4.10.1325009956; __utmc=47547066'))
    request = urllib2.Request("https://www.locationary.com/index.jsp?ACTION_TOKEN=tile_loginBar_jsp$JspView$LoginAction", data)
    response = opener.open(request) 
    url = str(final_url)
    anything = opener.open(url)
    page = anything.read()

States = [#'Alabama',
          #'Alaska',
          'Arizona',
          'Arkansas',
          'California',
          'Colorado',
          'Connecticut',
          'Delaware',
          'Florida',
          'Georgia',
          'Hawaii',
          'Idaho',
          'Illinois',
          'Indiana',
          'Iowa',
          'Kansas',
          'Kentucky',
          'Louisiana',
          'Maine',
          'Maryland',
          'Massachusetts',
          'Michigan',
          'Minnesota',
          'Mississippi',
          'Missouri',
          'Montana',
          'Nebraska',
          'Nevada',
          'New_Hampshire',
          'New_Jersey',
          'New_Mexico',
          'New_York',
          'North_Carolina',
          'North_Dakota',
          'Ohio',
          'Oklahoma',
          'Oregon',
          'Pennsylvania',
          'Rhode_Island',
          'South_Carolina',
          'South_Dakota',
          'Tennessee',
          'Texas',
          'Utah',
          'Vermont',
          'Virginia',
          'Washington',
          'West_Virginia',
          'Wisconsin',
          'Wyoming']

Cities = []

def find_cities(state):
    state_url = 'http://www.locationary.com/place/en/US/' + str(state)
    state_document = download(str(state_url))
    findCities = re.compile('<b>(.*)</b>')
    getCities = re.findall(findCities,state_document)

    for City in getCities:
        reps = {' ':'_'}
        City = replace_chars(City, reps)
        Cities.append(str(City))

bestworst = ['0','1']

def main():
    for state in States:
        find_cities(state)
        for city in Cities:
            for num in range(0,1):
                for pagenum in range(15,16):
                    print '------------------------------------------------------------------------------------------------------------------------------------------------------------'
                    print '------------------------------------------------------------------------------------------------------------------------------------------------------------'
                    if str(num) == '0':
                        print str(state) + ', ' + str(city) + ', ' + 'Best Profiles' + ', ' + 'Page ' + str(pagenum)
                    else:
                        print str(state) + ', ' + str(city) + ', ' + 'Worst Profiles' + ', ' + 'Page ' + str(pagenum)
                    START_URL = 'http://www.locationary.com/place/en/US/' + str(state) + '/' + city + '-page' + str(pagenum) + '/?ACTION_TOKEN=NumericAction&order=' + str(num)
                    pool = eventlet.GreenPool()
                    listings_document = BeautifulSoup(download(START_URL))
                    listings = listings_document.findAll("a", href = LOCATION_LISTING)
                    listings = [listing['href'] for listing in listings]

                    count_listings = 0

                    for final_url in pool.imap(handle_listing, listings):
                        print final_url
                        if final_url is not None:
                            log_in(final_url)

if __name__ == '__main__':
    main()
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有没有办法让它更快或不可能?它必须从互联网上下载很多网址,但我很确定我不能使我的互联网连接速度比现在快10到50倍......而且我的电脑不是很慢......所以,是有没有办法让我的程序,比如说快10-50倍?我知道这可能听起来很荒谬,但专业程序员如何让他们的程序更快呢?

Ern*_*ill 6

加速任何计划的第一步是了解为什么它的速度很慢 - 即,时间在哪里?用于执行此操作的工具程序员称为分析器.标准Python包括以下几种:您可以在这里了解它们.

一旦学会了使用分析器,就可以在程序中运行它来识别热点或程序花费最多时间的位置.然后尝试以两种方式之一加速程序:

  1. 尽量让热点花费更少的时间; 要么
  2. 尝试使热点执行次数更少.

通常#2更有成效.选择更好或更合适的算法可以减少执行的代码量.

不要浪费时间猜测为什么程序很慢; 测量它,然后投入精力来解决真正的问题.众所周知,程序员在猜测性能问题所在的位置上是不好的.