在运行脚本之前，请确定你是否按照了MySQLdb库，安装方法可以去百度一下。
下面是我的代码。
#!/usr/local/bin/python#coding:utf8# 2015-6-26 DaoXinimport pycurl, json, MySQLdbimport StringIOimport urllib, urllib2from random import choiceimport sys reload(sys)sys.setdefaultencoding('utf8')#useragent 列表，大家可以自行去收集。不过在本例中似乎不需要这个AGENTS = [ "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/43.0.2357.81 Safari/537.36", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/534.27 (KHTML, like Gecko) Chrome/12.0.712.0 Safari/534.27", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/13.0.782.24 Safari/535.1", "Mozilla/5.0 (Windows NT 6.0) AppleWebKit/535.2 (KHTML, like Gecko) Chrome/15.0.874.120 Safari/535.2", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.7 (KHTML, like Gecko) Chrome/16.0.912.36 Safari/535.7", "Mozilla/5.0 (Windows NT 6.1; WOW64; rv:2.0b4pre) Gecko/20100815 Minefield/4.0b4pre", "Mozilla/5.0 (Windows; U; Windows NT 6.1; zh-CN) AppleWebKit/533.19.4 (KHTML, like Gecko) Version/5.0.2 Safari/533.18.5", "Mozilla/5.0 (Windows; U; Windows NT 6.1; en-GB; rv:1.9.1.17) Gecko/20110123 (like Firefox/3.x) SeaMonkey/2.0.12", "Mozilla/5.0 (Windows NT 5.2; rv:10.0.1) Gecko/20100101 Firefox/10.0.1 SeaMonkey/2.7.1", "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_5_8; zh-CN) AppleWebKit/532.8 (KHTML, like Gecko) Chrome/4.0.302.2 Safari/532.8", "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_4; zh-CN) AppleWebKit/534.3 (KHTML, like Gecko) Chrome/6.0.464.0 Safari/534.3", "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_5; zh-CN) AppleWebKit/534.13 (KHTML, like Gecko) Chrome/9.0.597.15 Safari/534.13", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_2) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/14.0.835.186 Safari/535.1", "Mozilla/5.0 (Macintosh; U; PPC Mac OS X; en) AppleWebKit/125.2 (KHTML, like Gecko) Safari/125.8", "Mozilla/5.0 (Macintosh; U; PPC Mac OS X; fr-fr) AppleWebKit/312.5 (KHTML, like Gecko) Safari/312.3", "Mozilla/5.0 (Macintosh; U; PPC Mac OS X; en) AppleWebKit/418.8 (KHTML, like Gecko) Safari/419.3", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.6; rv:2.0.1) Gecko/20100101 Firefox/4.0.1 Camino/2.2.1", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.6; rv:2.0b6pre) Gecko/20100907 Firefox/4.0b6pre Camino/2.2a1pre", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_2) AppleWebKit/537.4 (KHTML like Gecko) Chrome/22.0.1229.79 Safari/537.4", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_2; rv:10.0.1) Gecko/20100101 Firefox/10.0.1", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.8; rv:16.0) Gecko/20120813 Firefox/16.0", "Mozilla/5.0 (Macintosh; U; Intel Mac OS X; zh-CN) AppleWebKit/528.16 (KHTML, like Gecko, Safari/528.16) OmniWeb/v622.8.0.112941", "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_5_6; zh-CN) AppleWebKit/528.16 (KHTML, like Gecko, Safari/528.16) OmniWeb/v622.8.0",]UserAgent = choice(AGENTS)#如果需要把挖出来的关键词保存到数据库，需要配置数据库相关信息class ConnDb(): global host, user, passwd, db host = '111.111.111.111' #数据库IP user = 'python' #数据库用户名 passwd = 'pass' #数据库密码 db = 'dbnamelllllll' # 数据库名 def connDb(self): global cur conn = MySQLdb.connect(host=host, user=user, passwd=passwd, db=db, port=3306, charset = 'utf8') cur = conn.cursor() return cur# 这个curl方法是从zero那里扒过来的。http://www.seoqx.com/post/341def curl(url, debug=False, **kwargs): while 1: try: s = StringIO.StringIO() c = pycurl.Curl() c.setopt(pycurl.URL, url) c.setopt(pycurl.REFERER, url) c.setopt(pycurl.FOLLOWLOCATION, True) c.setopt(pycurl.TIMEOUT, 60) c.setopt(pycurl.ENCODING, 'gzip') c.setopt(pycurl.USERAGENT, UserAgent) c.setopt(pycurl.NOSIGNAL, True) c.setopt(pycurl.WRITEFUNCTION, s.write) for k, v in kwargs.iteritems(): c.setopt(vars(pycurl)[k], v) c.perform() c.close() return s.getvalue() except: if debug: raise continuecommand = int(raw_input("请选择导出形式；1：导出为txt，2：导入道数据库: "))if command == 1:FileWrite = open("output.txt", 'w')for line in open('sourceword.txt'):kw = str(line)jsons = curl('http://honeyimg.bdimg.com/recomword/recomWordCache_findRecomWord.htm?area_id=&word=' + urllib.quote_plus(kw))d = json.loads(jsons)try:dlist = d['data']['list']for item in dlist:indexs = item['total']keywords = item['word'].encode('utf-8')outstr = str(indexs) + ',' + str(keywords) + '\n'FileWrite.write(outstr)except TypeError, e:print 'TypeError, Pass', econtinueprint 'done to txt'elif command == 2:conndb = ConnDb()conndb.connDb()for line in open('sourceword.txt'):kw = str(line)jsons = curl('http://honeyimg.bdimg.com/recomword/recomWordCache_findRecomWord.htm?area_id=&word=' + urllib.quote_plus(kw))d = json.loads(jsons)try:dlist = d['data']['list']for item in dlist:indexs = item['total']#keywords = unicode(item['word'], 'utf-8')keywords = item['word'].encode("utf-8")sql = "insert into shangqing_keyword (id, total, keyword) values (null, '%s', '%s')"try:cur.execute(sql % (indexs, keywords))except MySQLdb.Error, e:print 'MySql error', econtinueexcept TypeError, e:print 'TypeError, Pass' , econtinueprint 'done to mysql'else:print '只有两种导出方式，请输入1或者2'
使用方法：
1、将你的词根放到sourceword.txt 中，一行一个词，然后将本文代码随便保存成一个xxxx.py 和sourceword.txt 放在同一个目录下。
2、交互模式下，进入这两个文件所在目录，运行脚本xxx.py（一般是输入python xxx.py即可）
3、会有提示选择导出模式，1为导出txt文件，2为导入到mysql中。如下图
图中的typeerror请忽略。
如果需要导入到mysql中，请配置mysql的相关信息，在代码中有注释。
不过首先需要在你的数据库中创建一个表，语句如下：
CREATE TABLE `shangqing_keyword` ( `id` int(11) unsigned NOT NULL AUTO_INCREMENT, `keyword` varchar(200) DEFAULT NULL, `total` int(11) DEFAULT NULL, PRIMARY KEY (`id`), UNIQUE KEY `keyword` (`keyword`)) ENGINE=MyISAM AUTO_INCREMENT=1 DEFAULT CHARSET=utf8;
4、等待完成。
个人认为导入到mysql更好管理，txt比较好处理一些。
我的sourceword中有6000个词，挖出来差不多30多万我就停止了。应该能挖出来更多
这个是导出为txt格式的样子。
导入到mysql是这样的。还是mysql用起来顺手一些。个人喜好。
注意：导出txt格式是存在重复词的，因为我不知道怎么去过滤。但是导入到mysql中 重复词是会自动过滤掉的。不过反正都无所谓，后期处理的时候大家总能找到办法的。
更多关注静学网http://www.seojingxue.com
下面是我的代码。
#!/usr/local/bin/python#coding:utf8# 2015-6-26 DaoXinimport pycurl, json, MySQLdbimport StringIOimport urllib, urllib2from random import choiceimport sys reload(sys)sys.setdefaultencoding('utf8')#useragent 列表，大家可以自行去收集。不过在本例中似乎不需要这个AGENTS = [ "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/43.0.2357.81 Safari/537.36", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/534.27 (KHTML, like Gecko) Chrome/12.0.712.0 Safari/534.27", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/13.0.782.24 Safari/535.1", "Mozilla/5.0 (Windows NT 6.0) AppleWebKit/535.2 (KHTML, like Gecko) Chrome/15.0.874.120 Safari/535.2", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.7 (KHTML, like Gecko) Chrome/16.0.912.36 Safari/535.7", "Mozilla/5.0 (Windows NT 6.1; WOW64; rv:2.0b4pre) Gecko/20100815 Minefield/4.0b4pre", "Mozilla/5.0 (Windows; U; Windows NT 6.1; zh-CN) AppleWebKit/533.19.4 (KHTML, like Gecko) Version/5.0.2 Safari/533.18.5", "Mozilla/5.0 (Windows; U; Windows NT 6.1; en-GB; rv:1.9.1.17) Gecko/20110123 (like Firefox/3.x) SeaMonkey/2.0.12", "Mozilla/5.0 (Windows NT 5.2; rv:10.0.1) Gecko/20100101 Firefox/10.0.1 SeaMonkey/2.7.1", "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_5_8; zh-CN) AppleWebKit/532.8 (KHTML, like Gecko) Chrome/4.0.302.2 Safari/532.8", "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_4; zh-CN) AppleWebKit/534.3 (KHTML, like Gecko) Chrome/6.0.464.0 Safari/534.3", "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_5; zh-CN) AppleWebKit/534.13 (KHTML, like Gecko) Chrome/9.0.597.15 Safari/534.13", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_2) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/14.0.835.186 Safari/535.1", "Mozilla/5.0 (Macintosh; U; PPC Mac OS X; en) AppleWebKit/125.2 (KHTML, like Gecko) Safari/125.8", "Mozilla/5.0 (Macintosh; U; PPC Mac OS X; fr-fr) AppleWebKit/312.5 (KHTML, like Gecko) Safari/312.3", "Mozilla/5.0 (Macintosh; U; PPC Mac OS X; en) AppleWebKit/418.8 (KHTML, like Gecko) Safari/419.3", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.6; rv:2.0.1) Gecko/20100101 Firefox/4.0.1 Camino/2.2.1", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.6; rv:2.0b6pre) Gecko/20100907 Firefox/4.0b6pre Camino/2.2a1pre", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_2) AppleWebKit/537.4 (KHTML like Gecko) Chrome/22.0.1229.79 Safari/537.4", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_2; rv:10.0.1) Gecko/20100101 Firefox/10.0.1", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.8; rv:16.0) Gecko/20120813 Firefox/16.0", "Mozilla/5.0 (Macintosh; U; Intel Mac OS X; zh-CN) AppleWebKit/528.16 (KHTML, like Gecko, Safari/528.16) OmniWeb/v622.8.0.112941", "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_5_6; zh-CN) AppleWebKit/528.16 (KHTML, like Gecko, Safari/528.16) OmniWeb/v622.8.0",]UserAgent = choice(AGENTS)#如果需要把挖出来的关键词保存到数据库，需要配置数据库相关信息class ConnDb(): global host, user, passwd, db host = '111.111.111.111' #数据库IP user = 'python' #数据库用户名 passwd = 'pass' #数据库密码 db = 'dbnamelllllll' # 数据库名 def connDb(self): global cur conn = MySQLdb.connect(host=host, user=user, passwd=passwd, db=db, port=3306, charset = 'utf8') cur = conn.cursor() return cur# 这个curl方法是从zero那里扒过来的。http://www.seoqx.com/post/341def curl(url, debug=False, **kwargs): while 1: try: s = StringIO.StringIO() c = pycurl.Curl() c.setopt(pycurl.URL, url) c.setopt(pycurl.REFERER, url) c.setopt(pycurl.FOLLOWLOCATION, True) c.setopt(pycurl.TIMEOUT, 60) c.setopt(pycurl.ENCODING, 'gzip') c.setopt(pycurl.USERAGENT, UserAgent) c.setopt(pycurl.NOSIGNAL, True) c.setopt(pycurl.WRITEFUNCTION, s.write) for k, v in kwargs.iteritems(): c.setopt(vars(pycurl)[k], v) c.perform() c.close() return s.getvalue() except: if debug: raise continuecommand = int(raw_input("请选择导出形式；1：导出为txt，2：导入道数据库: "))if command == 1:FileWrite = open("output.txt", 'w')for line in open('sourceword.txt'):kw = str(line)jsons = curl('http://honeyimg.bdimg.com/recomword/recomWordCache_findRecomWord.htm?area_id=&word=' + urllib.quote_plus(kw))d = json.loads(jsons)try:dlist = d['data']['list']for item in dlist:indexs = item['total']keywords = item['word'].encode('utf-8')outstr = str(indexs) + ',' + str(keywords) + '\n'FileWrite.write(outstr)except TypeError, e:print 'TypeError, Pass', econtinueprint 'done to txt'elif command == 2:conndb = ConnDb()conndb.connDb()for line in open('sourceword.txt'):kw = str(line)jsons = curl('http://honeyimg.bdimg.com/recomword/recomWordCache_findRecomWord.htm?area_id=&word=' + urllib.quote_plus(kw))d = json.loads(jsons)try:dlist = d['data']['list']for item in dlist:indexs = item['total']#keywords = unicode(item['word'], 'utf-8')keywords = item['word'].encode("utf-8")sql = "insert into shangqing_keyword (id, total, keyword) values (null, '%s', '%s')"try:cur.execute(sql % (indexs, keywords))except MySQLdb.Error, e:print 'MySql error', econtinueexcept TypeError, e:print 'TypeError, Pass' , econtinueprint 'done to mysql'else:print '只有两种导出方式，请输入1或者2'
使用方法：
1、将你的词根放到sourceword.txt 中，一行一个词，然后将本文代码随便保存成一个xxxx.py 和sourceword.txt 放在同一个目录下。
2、交互模式下，进入这两个文件所在目录，运行脚本xxx.py（一般是输入python xxx.py即可）
3、会有提示选择导出模式，1为导出txt文件，2为导入到mysql中。如下图
图中的typeerror请忽略。
如果需要导入到mysql中，请配置mysql的相关信息，在代码中有注释。
不过首先需要在你的数据库中创建一个表，语句如下：
CREATE TABLE `shangqing_keyword` ( `id` int(11) unsigned NOT NULL AUTO_INCREMENT, `keyword` varchar(200) DEFAULT NULL, `total` int(11) DEFAULT NULL, PRIMARY KEY (`id`), UNIQUE KEY `keyword` (`keyword`)) ENGINE=MyISAM AUTO_INCREMENT=1 DEFAULT CHARSET=utf8;
4、等待完成。
个人认为导入到mysql更好管理，txt比较好处理一些。
我的sourceword中有6000个词，挖出来差不多30多万我就停止了。应该能挖出来更多
这个是导出为txt格式的样子。
导入到mysql是这样的。还是mysql用起来顺手一些。个人喜好。
注意：导出txt格式是存在重复词的，因为我不知道怎么去过滤。但是导入到mysql中 重复词是会自动过滤掉的。不过反正都无所谓，后期处理的时候大家总能找到办法的。
更多关注静学网http://www.seojingxue.com
