有多条这样类似的数据
{ "_id" : ObjectId("56d06f01c3666e08d0f0c844"),
"http://tieba.baidu.com/p/4345287300" : "【关于更新】作者原话",
"http://tieba.baidu.com/p/4328978430" : "服务。",
"http://tieba.baidu.com/p/4372502982" : "『诛魂记』第331章:圣东王府",
"http://tieba.baidu.com/p/4355241530" : "『诛魂记』第322章:麒麟之威",
"http://tieba.baidu.com/p/4329505585" : "『诛魂记』第313章:泣血跪求",
"http://tieba.baidu.com/p/4343824178" : "新年快乐啦啦啦",
"http://tieba.baidu.com/p/4328603018" : "写小说好看吗",
"http://tieba.baidu.com/p/4333008061" : "来吧,你我君臣一场",
"http://tieba.baidu.com/p/4315565196" : "『诛魂记』第305章:临危受命",
"http://tieba.baidu.com/p/4340906961" : "『诛魂记』第320章:擒贼擒王",
"http://tieba.baidu.com/p/4337476352" : "新年到了,是不是发红包了"
}
我想在上面的数据当中获得能够匹配:『诛魂记』 的连接以及后面的文本数据,例如
"http://tieba.baidu.com/p/4329505585" : "『诛魂记』第313章:泣血跪求"
这样,
同时把得查询到的结构存到另外一个表中,以及得到
"http://tieba.baidu.com/p/4329505585" : "『诛魂记』第313章:泣血跪求"
中的连接 http://tieba.baidu.com/p/4329505585
最近开始在接触一些爬虫相关的东西,想自己做个东西出来,实在是捉急了。
下面是python里面的代码
def craw(self, root_urls):
for new_url in root_urls:
html_cont = self.downloader.download(new_url)
new_chapter_urls, new_linkdatas = self.parser.parselink(root_chapter_url, html_cont)
mid_data = zip(new_chapter_urls,new_linkdatas)
mid_mid_datas = dict((new_chapter_urls,new_linkdatas) for new_chapter_urls,new_linkdatas in mid_data)
c = pymongo.MongoClient(host='127.0.0.1', port=27017)
db = c.spider
db.chapter_datas.insert(mid_mid_datas, check_keys=False)
某草草2017-05-02 09:19:52
Why not filter it directly based on whether the content in the data contains ""Hun Zhu Ji"" when crawling?
>>> s = "『诛魂记』第331章:圣东王府"
>>> "『诛魂记』" in s
True
>>> s = "新年快乐啦啦啦"
>>> "『诛魂记』" in s
False