爬取百度諮詢

獲取url，就是把關鍵字進行urlencode。整理爬取的內容，就是把一些【回車】，【空格】等雜七雜八的東西過濾掉。輸出結果下面是**：

import re

from urllib import parse
import time
import requests
from bs4 import beautifulsoup
import pandas as pd
def html_decode
(url)
:    agent =
headers =
time.
sleep(5
)    html = requests.
get(url, headers=headers)
content = html.content
soup =
beautifulsoup
(content, fromencoding=
'utf-8'
)    content_list =
author_list =
time_list =
for mulu in soup.
findall
('div'
, attrs=):
# get subject
subject = mulu.h3.a.
get_text()
author_time = mulu.div.p.
get_text()
text1 = re.
sub(r"\n|      ",''
, subject)
text2 = re.
sub(r"\n|      ",''
, author_time)
text2.
strip()
author = text2.
split
('  										')[
0]time = text2.
split
('  										')[
1]content_list.
(text1)
author_list.
(author)
time_list.
(time)
return content_list, author_list, time_list
def get_context
(keyword, page)
:    all_content =
all_author =
all_time =
agent =
headers =
parameter_page = page *
10if
type
(keyword)
== str:
main_url =r''
parameter =
# print
(str
(url_data)
)else
:print
('url wrong!'
)    # get first page
url_data = parse.
urlencode
(parameter)
first_page_paramter =
str(url_data)
.split
('&inputt')[
0]first_page = parse.
urljoin
(main_url,
's?'
+str
(first_page_paramter)
)    first_item, first_author_list, first_time_list =
html_decode
(first_page)
all_content.
extend
(first_item)
all_author.
extend
(first_author_list)
all_time.
extend
(first_time_list)
# get other pages
for num in
range(1
, page+1)
:print
('this is page %d!'
%(num)
)        parameter[
'pn'
]= num *
10        url_data = parse.
urlencode
(parameter)
all_url = parse.
urljoin
(main_url,
's?'
+str
(url_data)
)        # print
(all_url)
other_items, other_author_list, other_time_list =
html_decode
(all_url)
all_content.
extend
(other_items)
all_author.
extend
(other_author_list)
all_time.
extend
(other_time_list)
return all_content, all_author, all_time
if __name__ ==
'__main__'
:    date = time.
strftime
('%m-%d'
,time.
localtime()
)    key_word =
'華山'
page_num =
5    all_content, all_author, all_time =
get_context
(key_word, page_num)
result = pd.
dataframe()
result.
to_excel
('result_%s.xlsx'
%date)
print
('總共%d條資料!'
%len
(all_content)
)print
('爬取完畢！'
)

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