如何通过 Python 挖掘带流量 Seo 关键词
更新时间：2018-10-06 分类：推广技巧 浏览量：3388
方法博客上分享通过百度商情数据接口挖掘关键词的 Shell 。同时，也提供一个 Python 脚本源码。
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。
代码如下：
#!/usr/local/bin/python
#coding:utf8
# 2015-6-26 DaoXin
import pycurl, json, MySQLdb
import StringIO
import urllib, urllib2
from random import choice
import 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/341
def 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
continue
command = 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', e
continue
print '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', e
continue
except TypeError, e:
print 'TypeError, Pass' , e
continue
print '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。
效果截图：
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。
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