本次实战目标是爬取一本名叫《大千界域》的小说，本次实战仅供交流学习，支持作者，请上起点中文网订阅观看。
点击检查，获取页面的html信息，我发现每一章都对应一个url链接，故我们只要得到本页面html信息，然后通过Beautifulsoup，re等工具，就可将所有章节的url全部得到存成一个url列表然后挨个访问便可获取到所有章节内容，本次爬虫也就大功告成了！
按照我的想法，我用如下代码获取了页面html，并在后端输出显示，结果发现返回的html信息不全，包含章节链接的body标签没有被爬取到，就算补全了headers信息，还是无法获取到body标签里的内容，看来起点对反爬做的措施不错嘛，这条道走不通，咱们换一条。
import requests
def get():
url = '/info/3144877#Catalog'
req = requests.get(url)
print(req.text)
if __name__ == '__main__':
get()
既然这个页面是动态加载的，故可能应用ajax与后端数据库进行了数据交互，然后渲染到了页面上，我们只需拦截这次交互请求，获取到交互的数据即可。
打开网页/info/3144877#Catalog，再次右键点击检查即审查元素，因为是要找到数据交互，故点击network里的XHR请求，精确捕获XHR对象，我们发现一个url为/ajax/book/category?_csrfToken=1iiVodIPe2qL9Z53jFDIcXlmVghqnB6jSwPP5XKF&bookId=3144877的请求返回的response是一个包含所有卷id和章节id的json对象，这就是我们要寻找的交互数据。
通过如下代码，便可获取到该json对象
import requests
import random
def random_user_agent():
list = ['Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36',
'Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.36 (KHTML like Gecko) Chrome/44.0.2403.155 Safari/537.36',
'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2227.0 Safari/537.36',
'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2226.0 Safari/537.36',
'Mozilla/5.0 (Windows NT 6.4; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2225.0 Safari/537.36',
'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2225.0 Safari/537.36']
seed = random.randint(0, len(list)-1)
return list[seed]
def getJson():
url = '/ajax/book/category?_csrfToken=BXnzDKmnJamNAgLu4O3GknYVL2YuNX5EE86tTBAm&bookId=3144877'
headers = {'User-Agent': random_user_agent(),
'Referer': '/info/3144877',
'Cookie': '_csrfToken=BXnzDKmnJamNAgLu4O3GknYVL2YuNX5EE86tTBAm; newstatisticUUID=1564467217_1193332262; qdrs=0%7C3%7C0%7C0%7C1; showSectionCommentGuide=1; qdgd=1; lrbc=1013637116%7C436231358%7C0%2C1003541158%7C309402995%7C0; rcr=1013637116%2C1003541158; bc=1003541158%2C1013637116; e1=%7B%22pid%22%3A%22qd_P_limitfree%22%2C%22eid%22%3A%22qd_E01%22%2C%22l1%22%3A4%7D; e2=%7B%22pid%22%3A%22qd_P_free%22%2C%22eid%22%3A%22qd_A18%22%2C%22l1%22%3A3%7D'
}
res = requests.get(url=url, params=headers)
json_str = res.text
print(json_str)
if __name__ == '__main__':
getJson()
在小说的章节信息页面里我发现有分卷阅读，点击进入后发现该页面包含该卷的所有章节内容，且每一个分卷阅读的前半段url都是/hankread/3144877/，变得只是该卷的id号，例如第一卷初来乍到的id为8478272，故阅读整个第一卷内容的链接为/hankread/3144877/8478272。故我们只需要在上述json对象里截取所有卷id，便可以爬取整本了！
爬取效果如下：
完整代码如下：
import requests
import re
from bs4 import BeautifulSoup
from requests.exceptions import *
import random
import json
import time
import os
import sys
def random_user_agent():
list = ['Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36',
'Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.36 (KHTML like Gecko) Chrome/44.0.2403.155 Safari/537.36',
'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2227.0 Safari/537.36',
'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2226.0 Safari/537.36',
'Mozilla/5.0 (Windows NT 6.4; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2225.0 Safari/537.36',
'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2225.0 Safari/537.36']
seed = random.randint(0, len(list)-1)
return list[seed]
def getJson():
url = '/ajax/book/category?_csrfToken=BXnzDKmnJamNAgLu4O3GknYVL2YuNX5EE86tTBAm&bookId=3144877'
headers = {'User-Agent': random_user_agent(),
'Referer': '/info/3144877',
'Cookie': '_csrfToken=BXnzDKmnJamNAgLu4O3GknYVL2YuNX5EE86tTBAm; newstatisticUUID=1564467217_1193332262; qdrs=0%7C3%7C0%7C0%7C1; showSectionCommentGuide=1; qdgd=1; lrbc=1013637116%7C436231358%7C0%2C1003541158%7C309402995%7C0; rcr=1013637116%2C1003541158; bc=1003541158%2C1013637116; e1=%7B%22pid%22%3A%22qd_P_limitfree%22%2C%22eid%22%3A%22qd_E01%22%2C%22l1%22%3A4%7D; e2=%7B%22pid%22%3A%22qd_P_free%22%2C%22eid%22%3A%22qd_A18%22%2C%22l1%22%3A3%7D'
}
try:
res = requests.get(url=url, params=headers)
if res.status_code == 200:
json_str = res.text
list = json.loads(json_str)['data']['vs']
response = {
'VolumeId_List': [],
'VolumeNum_List': []
}
for i in range(len(list)):
json_str = json.dumps(list[i]).replace(" ", "")
volume_id = re.search('.*?"vId":(.*?),', json_str, re.S).group(1)
volume_num = re.search('.*?"cCnt":(.*?),', json_str, re.S).group(1)
response['VolumeId_List'].append(volume_id)
response['VolumeNum_List'].append(volume_num)
return response
else:
print('No response')
return None
except ReadTimeout:
print("ReadTimeout!")
return None
except RequestException:
print("请求页面出错！")
return None
def getPage(VolId_List, VolNum_List):
'''
通过卷章Id找到要爬取的页面，并返回页面html信息
:param VolId_List: 卷章Id列表
:param VolNum_List: 每一卷含有的章节数量列表
:return:
'''
size = len(VolId_List)
for i in range(size):
path = 'C://Users//49881//Projects//PycharmProjects//Spider2起点中文网//大千界域//卷' + str(i + 1)
mkdir(path)
url = '/hankread/3144877/'+VolId_List[i]
print('\n当前访问路径：'+url)
headers = {
'User-Agent': random_user_agent(),
'Referer': '/info/3144877',
'Cookie': 'e1=%7B%22pid%22%3A%22qd_P_hankRead%22%2C%22eid%22%3A%22%22%2C%22l1%22%3A3%7D; e2=%7B%22pid%22%3A%22qd_P_hankRead%22%2C%22eid%22%3A%22%22%2C%22l1%22%3A2%7D; _csrfToken=BXnzDKmnJamNAgLu4O3GknYVL2YuNX5EE86tTBAm; newstatisticUUID=1564467217_1193332262; qdrs=0%7C3%7C0%7C0%7C1; showSectionCommentGuide=1; qdgd=1; e1=%7B%22pid%22%3A%22qd_P_limitfree%22%2C%22eid%22%3A%22qd_E01%22%2C%22l1%22%3A4%7D; e2=%7B%22pid%22%3A%22qd_P_free%22%2C%22eid%22%3A%22qd_A18%22%2C%22l1%22%3A3%7D; rcr=3144877%2C1013637116%2C1003541158; lrbc=3144877%7C52472447%7C0%2C1013637116%7C436231358%7C0%2C1003541158%7C309402995%7C0; bc=3144877'
}
try:
res = requests.get(url=url, params=headers)
if res.status_code == 200:
print('第'+str(i+1)+'卷已开始爬取：')
parsePage(res.text, url, path, int(VolNum_List[i]))
else:
print('No response')
return None
except ReadTimeout:
print("ReadTimeout!")
return None
except RequestException:
print("请求页面出错！")
return None
time.sleep(3)
def parsePage(html, url, path, chapNum):
'''
解析小说内容页面，将每章内容写入txt文件，并存储到相应的卷目录下
:param html: 小说内容页面
:param url: 访问路径
:param path: 卷目录路径
:return: None
'''
if html == None:
print('访问路径为'+url+'的页面为空')
return
soup = BeautifulSoup(html, 'lxml')
ChapInfoList = soup.find_all('div', attrs={'class': 'main-text-wrap'})
alreadySpiderNum = 0.0
for i in range(len(ChapInfoList)):
sys.stdout.write('\r已爬取{0}'.format('%.2f%%' % float(alreadySpiderNum/chapNum*100)))
sys.stdout.flush()
time.sleep(0.5)
soup1 = BeautifulSoup(str(ChapInfoList[i]), 'lxml')
ChapName = soup1.find('h3', attrs={'class': 'j_chapterName'}).span.string
ChapName = re.sub('[\/:*?"<>|]', '', ChapName)
if ChapName == '无题':
ChapName = '第'+str(i+1)+'章 无题'
filename = path+'//'+ChapName+'.txt'
readContent = soup1.find('div', attrs={'class': 'read-content j_readContent'}).find_all('p')
for item in readContent:
paragraph = re.search('.*?
(.*?)
', str(item), re.S).group(1)
save2file(filename, paragraph)
alreadySpiderNum += 1.0
sys.stdout.write('\r已爬取{0}'.format('%.2f%%' % float(alreadySpiderNum / chapNum * 100)))
def save2file(filename, content):
with open(r''+filename, 'a', encoding='utf-8') as f:
f.write(content+'\n')
f.close()
def mkdir(path):
'''
创建卷目录文件夹
:param path: 创建路径
:return: None
'''
folder = os.path.exists(path)
if not folder:
os.makedirs(path)
else:
print('路径'+path+'已存在')
def main():
response = getJson()
if response != None:
VolId_List = response['VolumeId_List']
VolNum_List = response['VolumeNum_List']
getPage(VolId_List, VolNum_List)
else:
print('无法爬取该小说！')
print("小说爬取完毕!")
if __name__ == '__main__':
main()
