案例 1：爬取百度产品列表
# ------------------------------------------------1.导包
import requests
# -------------------------------------------------2.确定url
base_url = 'https://www.baidu.com/more/'
# ----------------------------------------------3.发送请求，获取响应
response = requests.get(base_url)
# -----------------------------------------------4.查看页面内容,可能出现 乱码
# print(response.text)
# print(response.encoding)
# ---------------------------------------------------5.解决乱码
# ---------------------------方法一：转换成utf-8格式
# response.encoding='utf-8'
# print(response.text)
# -------------------------------方法二：解码为utf-8
with open('index.html', 'w', encoding='utf-8') as fp:
fp.write(response.content.decode('utf-8'))
print(response.status_code)
print(response.headers)
print(type(response.text))
print(type(response.content))
案例 2：爬取新浪新闻指定搜索内容
import requests
# ------------------爬取带参数的get请求-------------------爬取新浪新闻，指定的内容
# 1.寻找基础url
base_url = 'https://search.sina.com.cn/?'
# 2.设置headers字典和params字典，再发请求
headers = {
'user-agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
}
key = '孙悟空' # 搜索内容
params = {
'q': key,
'c': 'news',
'from': 'channel',
'ie': 'utf-8',
}
response = requests.get(base_url, headers=headers, params=params)
with open('sina_news.html', 'w', encoding='gbk') as fp:
fp.write(response.content.decode('gbk'))
-
分页类型
-
第一步：找出分页参数的规律
-
第二步：headers 和 params 字典
-
第三步：用 for 循环
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案例 3：爬取百度贴吧前十页（get 请求）
# _--------------------爬取百度贴吧搜索某个贴吧的前十页
import requests, os
base_url = 'https://tieba.baidu.com/f?'
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
}
dirname = './tieba/woman/'
if not os.path.exists(dirname):
os.makedirs(dirname)
for i in range(0, 10):
params = {
'ie': 'utf-8',
'kw': '美女',
'pn': str(i * 50)
}
response = requests.get(base_url, headers=headers, params=params)
with open(dirname + '美女第%s页.html' % (i+1), 'w', encoding='utf-8') as file:
file.write(response.content.decode('utf-8'))
案例 4：爬取百度翻译接口
python
import requests
base_url = 'https://fanyi.baidu.com/sug'
kw = input('请输入要翻译的英文单词：')
data = {
'kw': kw
}
headers = {
# 由于百度翻译没有反扒措施，因此可以不写请求头
'content-length': str(len(data)),
'content-type': 'application/x-www-form-urlencoded; charset=UTF-8',
'referer': 'https://fanyi.baidu.com/',
'x-requested-with': 'XMLHttpRequest'
}
response = requests.post(base_url, headers=headers, data=data)
# print(response.json())
#结果：{'errno': 0, 'data': [{'k': 'python', 'v': 'n. 蟒; 蚺蛇;'}, {'k': 'pythons', 'v': 'n. 蟒; 蚺蛇; python的复数;'}]}
#-----------------------------把他变成一行一行
result=''
for i in response.json()['data']:
result+=i['v']+'
'
print(kw+'的翻译结果为：')
print(result)
案例 5：爬取菜鸟教程的 python100 例
import requests
from lxml import etree
base_url = 'https://www.runoob.com/python/python-exercise-example%s.html'
def get_element(url):
headers = {
'cookie': '__gads=Test; Hm_lvt_3eec0b7da6548cf07db3bc477ea905ee=1573454862,1573470948,1573478656,1573713819; Hm_lpvt_3eec0b7da6548cf07db3bc477ea905ee=1573714018; SERVERID=fb669a01438a4693a180d7ad8d474adb|1573713997|1573713863',
'referer': 'https://www.runoob.com/python/python-100-examples.html',
'user-agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36'
}
response = requests.get(url, headers=headers)
return etree.HTML(response.text)
def write_py(i, text):
with open('练习实例%s.py' % i, 'w', encoding='utf-8') as file:
file.write(text)
def main():
for i in range(1, 101):
html = get_element(base_url % i)
content = '题目：' + html.xpath('//div[@id="content"]/p[2]/text()')[0] + '
'
fenxi = html.xpath('//div[@id="content"]/p[position()>=2]/text()')[0]
daima = ''.join(html.xpath('//div[@class="hl-main"]/span/text()')) + '
'
haha = '"""
' + content + fenxi + daima + '
"""'
write_py(i, haha)
print(fenxi)
if __name__ == '__main__':
main()
案例 6：登录人人网（cookie）
import requests
base_url = 'http://www.renren.com/909063513'
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'Cookie': 'cookie',
}
response=requests.get(base_url,headers=headers)
if '死性不改' in response.text:
print('登录成功')
else:
print('登录失败')
由于我们登录进入人人网在人人网 html 页面就会显示用户名，因此可以通过用户名是否存在来判断是否登录成功
案例 7：登录人人网（session）
import requests
base_url = 'http://www.renren.com/PLogin.do'
headers= {
'Host': 'www.renren.com',
'Referer': 'http://safe.renren.com/security/account',
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36',
}
data = {
'email':邮箱,
'password':密码,
}
#创建一个session对象
se = requests.session()
#用session对象来发送post请求进行登录。
se.post(base_url,headers=headers,data=data)
response = se.get('http://www.renren.com/971682585')
if '鸣人' in response.text:
print('登录成功！')
else:
print(response.text)
print('登录失败！')
案例 8：爬取猫眼电影（正则表达式）
爬取目标：爬取前一百个电影的信息
import re, requests, json
class Maoyan:
def __init__(self, url):
self.url = url
self.movie_list = []
self.headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36'
}
self.parse()
def parse(self):
# 爬去页面的代码
# 1.发送请求，获取响应
# 分页
for i in range(10):
url = self.url + '?offset={}'.format(i * 10)
response = requests.get(url, headers=self.headers)
'''
1.电影名称
2、主演
3、上映时间
4、评分
'''
# 用正则筛选数据，有个原则：不断缩小筛选范围。
dl_pattern = re.compile(r'<dl class="board-wrapper">(.*?)</dl>', re.S)
dl_content = dl_pattern.search(response.text).group()
dd_pattern = re.compile(r'<dd>(.*?)</dd>', re.S)
dd_list = dd_pattern.findall(dl_content)
# print(dd_list)
movie_list = []
for dd in dd_list:
print(dd)
item = {}
# ------------电影名字
movie_pattern = re.compile(r'title="(.*?)" class=', re.S)
movie_name = movie_pattern.search(dd).group(1)
# print(movie_name)
actor_pattern = re.compile(r'<p class="star">(.*?)</p>', re.S)
actor = actor_pattern.search(dd).group(1).strip()
# print(actor)
play_time_pattern = re.compile(r'<p class="releasetime">(.*?)：(.*?)</p>', re.S)
play_time = play_time_pattern.search(dd).group(2).strip()
# print(play_time)
# 评分
score_pattern_1 = re.compile(r'<i class="integer">(.*?)</i>', re.S)
score_pattern_2 = re.compile(r'<i class="fraction">(.*?)</i>', re.S)
score = score_pattern_1.search(dd).group(1).strip() + score_pattern_2.search(dd).group(1).strip()
# print(score)
item['电影名字：'] = movie_name
item['主演：'] = actor
item['时间：'] = play_time
item['评分：'] = score
# print(item)
self.movie_list.append(item)
# 将电影信息保存到json文件中
with open('movie.json', 'w', encoding='utf-8') as fp:
json.dump(self.movie_list, fp)
if __name__ == '__main__':
base_url = 'https://maoyan.com/board/4'
Maoyan(base_url)
with open('movie.json', 'r') as fp:
movie_list = json.load(fp)
print(movie_list)
案例 9：爬取股吧（正则表达式）
爬取目标： 爬取前十页的阅读数, 评论数, 标题, 作者, 更新时间, 详情页 url
import json
import re
import requests
class GuBa(object):
def __init__(self):
self.base_url = 'http://guba.eastmoney.com/default,99_%s.html'
self.headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36'
}
self.infos = []
self.parse()
def parse(self):
for i in range(1, 13):
response = requests.get(self.base_url % i, headers=self.headers)
'''阅读数,评论数,标题,作者,更新时间,详情页url'''
ul_pattern = re.compile(r'<ul id="itemSearchList" class="itemSearchList">(.*?)</ul>', re.S)
ul_content = ul_pattern.search(response.text)
if ul_content:
ul_content = ul_content.group()
li_pattern = re.compile(r'<li>(.*?)</li>', re.S)
li_list = li_pattern.findall(ul_content)
# print(li_list)
for li in li_list:
item = {}
reader_pattern = re.compile(r'<cite>(.*?)</cite>', re.S)
info_list = reader_pattern.findall(li)
# print(info_list)
reader_num = ''
comment_num = ''
if info_list:
reader_num = info_list[0].strip()
comment_num = info_list[1].strip()
print(reader_num, comment_num)
title_pattern = re.compile(r'title="(.*?)" class="note">', re.S)
title = title_pattern.search(li).group(1)
# print(title)
author_pattern = re.compile(r'target="_blank"><font>(.*?)</font></a><input type="hidden"', re.S)
author = author_pattern.search(li).group(1)
# print(author)
date_pattern = re.compile(r'<cite class="last">(.*?)</cite>', re.S)
date = date_pattern.search(li).group(1)
# print(date)
detail_pattern = re.compile(r' <a href="(.*?)" title=', re.S)
detail_url = detail_pattern.search(li)
if detail_url:
detail_url = 'http://guba.eastmoney.com' + detail_url.group(1)
else:
detail_url = ''
print(detail_url)
item['title'] = title
item['author'] = author
item['date'] = date
item['reader_num'] = reader_num
item['comment_num'] = comment_num
item['detail_url'] = detail_url
self.infos.append(item)
with open('guba.json', 'w', encoding='utf-8') as fp:
json.dump(self.infos, fp)
gb=GuBa()
案例 10：爬取某药品网站（正则表达式）
爬取目标：爬取五十页的药品信息
'''
要求：抓取50页
字段：总价，描述，评论数量，详情页链接
用正则爬取。
'''
import requests, re,json
class Drugs:
def __init__(self):
self.url = url = 'https://www.111.com.cn/categories/953710-j%s.html'
self.headers = {
'user-agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36'
}
self.Drugs_list=[]
self.parse()
def parse(self):
for i in range(51):
response = requests.get(self.url % i, headers=self.headers)
# print(response.text)
# 字段：药名，总价，评论数量，详情页链接
Drugsul_pattern = re.compile('<ul id="itemSearchList" class="itemSearchList">(.*?)</ul>', re.S)
Drugsul = Drugsul_pattern.search(response.text).group()
# print(Drugsul)
Drugsli_list_pattern = re.compile('<li id="producteg(.*?)</li>', re.S)
Drugsli_list = Drugsli_list_pattern.findall(Drugsul)
Drugsli_list = Drugsli_list
# print(Drugsli_list)
for drug in Drugsli_list:
# ---药名
item={}
name_pattern = re.compile('alt="(.*?)"', re.S)
name = name_pattern.search(str(drug)).group(1)
# print(name)
# ---总价
total_pattern = re.compile('<span>(.*?)</span>', re.S)
total = total_pattern.search(drug).group(1).strip()
# print(total)
# ----评论
comment_pattern = re.compile('<em>(.*?)</em>')
comment = comment_pattern.search(drug)
if comment:
comment_group = comment.group(1)
else:
comment_group = '0'
# print(comment_group)
# ---详情页链接
href_pattern = re.compile('" href="//(.*?)"')
href='https://'+href_pattern.search(drug).group(1).strip()
# print(href)
item['药名']=name
item['总价']=total
item['评论']=comment
item['链接']=href
self.Drugs_list.append(item)
drugs = Drugs()
print(drugs.Drugs_list)
案例 11：使用 xpath 爬取扇贝英语单词（xpath）
需求：爬取三页单词 
import json
import requests
from lxml import etree
base_url = 'https://www.shanbay.com/wordlist/110521/232414/?page=%s'
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36'
}
def get_text(value):
if value:
return value[0]
return ''
word_list = []
for i in range(1, 4):
# 发送请求
response = requests.get(base_url % i, headers=headers)
# print(response.text)
html = etree.HTML(response.text)
tr_list = html.xpath('//tbody/tr')
# print(tr_list)
for tr in tr_list:
item = {}#构造单词列表
en = get_text(tr.xpath('.//td[@class="span2"]/strong/text()'))
tra = get_text(tr.xpath('.//td[@class="span10"]/text()'))
print(en, tra)
if en:
item[en] = tra
word_list.append(item)
面向对象：
import requests
from lxml import etree
class Shanbei(object):
def __init__(self):
self.base_url = 'https://www.shanbay.com/wordlist/110521/232414/?page=%s'
self.headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36'
}
self.word_list = []
self.parse()
def get_text(self, value):
# 防止为空报错
if value:
return value[0]
return ''
def parse(self):
for i in range(1, 4):
# 发送请求
response = requests.get(self.base_url % i, headers=self.headers)
# print(response.text)
html = etree.HTML(response.text)
tr_list = html.xpath('//tbody/tr')
# print(tr_list)
for tr in tr_list:
item = {} # 构造单词列表
en = self.get_text(tr.xpath('.//td[@class="span2"]/strong/text()'))
tra = self.get_text(tr.xpath('.//td[@class="span10"]/text()'))
print(en, tra)
if en:
item[en] = tra
self.word_list.append(item)
shanbei = Shanbei()
案例 12：爬取网易云音乐的所有歌手名字（xpath）
import requests,json
from lxml import etree
url = 'https://music.163.com/discover/artist'
singer_infos = []
# ---------------通过url获取该页面的内容，返回xpath对象
def get_xpath(url):
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36'
}
response = requests.get(url, headers=headers)
return etree.HTML(response.text)
# --------------通过get_xpath爬取到页面后，我们获取华宇，华宇男等分类
def parse():
html = get_xpath(url)
fenlei_url_list = html.xpath('//ul[@class="nav f-cb"]/li/a/@href') # 获取华宇等分类的url
# print(fenlei_url_list)
# --------将热门和推荐两栏去掉筛选
new_list = [i for i in fenlei_url_list if 'id' in i]
for i in new_list:
fenlei_url = 'https://music.163.com' + i
parse_fenlei(fenlei_url)
# print(fenlei_url)
# -------------通过传入的分类url，获取A,B，C页面内容
def parse_fenlei(url):
html = get_xpath(url)
# 获得字母排序，每个字母的链接
zimu_url_list = html.xpath('//ul[@id="initial-selector"]/li[position()>1]/a/@href')
for i in zimu_url_list:
zimu_url = 'https://music.163.com' + i
parse_singer(zimu_url)
# ---------------------传入获得的字母链接，开始爬取歌手内容
def parse_singer(url):
html = get_xpath(url)
item = {}
singer_names = html.xpath('//ul[@id="m-artist-box"]/li/p/a/text()')
# --详情页看到页面结构会有两个a标签，所以取第一个
singer_href = html.xpath('//ul[@id="m-artist-box"]/li/p/a[1]/@href')
# print(singer_names,singer_href)
for i, name in enumerate(singer_names):
item['歌手名'] = name
item['音乐链接'] = 'https://music.163.com' + singer_href[i].strip()
# 获取歌手详情页的链接
url = item['音乐链接'].replace(r'?id', '/desc?id')
# print(url)
parse_detail(url, item)
print(item)
# ---------获取详情页url和存着歌手名字和音乐列表的字典，在字典中添加详情页数据
def parse_detail(url, item):
html = get_xpath(url)
desc_list = html.xpath('//div[@class="n-artdesc"]/p/text()')
item['歌手信息'] = desc_list
singer_infos.append(item)
write_singer(item)
# ----------------将数据字典写入歌手文件
def write_singer(item):
with open('singer.json', 'a+', encoding='utf-8') as file:
json.dump(item,file)
if __name__ == '__main__':
parse()
面向对象
import json, requests
from lxml import etree
class Wangyiyun(object):
def __init__(self):
self.url = 'https://music.163.com/discover/artist'
self.singer_infos = []
self.headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36'
}
self.parse()
# ---------------通过url获取该页面的内容，返回xpath对象
def get_xpath(self, url):
response = requests.get(url, headers=self.headers)
return etree.HTML(response.text)
# --------------通过get_xpath爬取到页面后，我们获取华宇，华宇男等分类
def parse(self):
html = self.get_xpath(self.url)
fenlei_url_list = html.xpath('//ul[@class="nav f-cb"]/li/a/@href') # 获取华宇等分类的url
# print(fenlei_url_list)
# --------将热门和推荐两栏去掉筛选
new_list = [i for i in fenlei_url_list if 'id' in i]
for i in new_list:
fenlei_url = 'https://music.163.com' + i
self.parse_fenlei(fenlei_url)
# print(fenlei_url)
# -------------通过传入的分类url，获取A,B，C页面内容
def parse_fenlei(self, url):
html = self.get_xpath(url)
# 获得字母排序，每个字母的链接
zimu_url_list = html.xpath('//ul[@id="initial-selector"]/li[position()>1]/a/@href')
for i in zimu_url_list:
zimu_url = 'https://music.163.com' + i
self.parse_singer(zimu_url)
# ---------------------传入获得的字母链接，开始爬取歌手内容
def parse_singer(self, url):
html = self.get_xpath(url)
item = {}
singer_names = html.xpath('//ul[@id="m-artist-box"]/li/p/a/text()')
# --详情页看到页面结构会有两个a标签，所以取第一个
singer_href = html.xpath('//ul[@id="m-artist-box"]/li/p/a[1]/@href')
# print(singer_names,singer_href)
for i, name in enumerate(singer_names):
item['歌手名'] = name
item['音乐链接'] = 'https://music.163.com' + singer_href[i].strip()
# 获取歌手详情页的链接
url = item['音乐链接'].replace(r'?id', '/desc?id')
# print(url)
self.parse_detail(url, item)
print(item)
# ---------获取详情页url和存着歌手名字和音乐列表的字典，在字典中添加详情页数据
def parse_detail(self, url, item):
html = self.get_xpath(url)
desc_list = html.xpath('//div[@class="n-artdesc"]/p/text()')[0]
item['歌手信息'] = desc_list
self.singer_infos.append(item)
self.write_singer(item)
# ----------------将数据字典写入歌手文件
def write_singer(self, item):
with open('sing.json', 'a+', encoding='utf-8') as file:
json.dump(item, file)
music = Wangyiyun()
案例 13：爬取酷狗音乐的歌手和歌单（xpath）
需求：爬取酷狗音乐的歌手和歌单和歌手简介 
import json, requests
from lxml import etree
base_url = 'https://www.kugou.com/yy/singer/index/%s-%s-1.html'
# ---------------通过url获取该页面的内容，返回xpath对象
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36'
}
# ---------------通过url获取该页面的内容，返回xpath对象
def get_xpath(url, headers):
try:
response = requests.get(url, headers=headers)
return etree.HTML(response.text)
except Exception:
print(url, '该页面没有相应！')
return ''
# --------------------通过歌手详情页获取歌手简介
def parse_info(url):
html = get_xpath(url, headers)
info = html.xpath('//div[@class="intro"]/p/text()')
return info
# --------------------------写入方法
def write_json(value):
with open('kugou.json', 'a+', encoding='utf-8') as file:
json.dump(value, file)
# -----------------------------用ASCII码值来变换abcd...
for j in range(97, 124):
# 小写字母为97-122，当等于123的时候我们按歌手名单的其他算，路由为null
if j < 123:
p = chr(j)
else:
p = "null"
for i in range(1, 6):
response = requests.get(base_url % (i, p), headers=headers)
# print(response.text)
html = etree.HTML(response.text)
# 由于数据分两个url，所以需要加起来数据列表
name_list1 = html.xpath('//ul[@id="list_head"]/li/strong/a/text()')
sing_list1 = html.xpath('//ul[@id="list_head"]/li/strong/a/@href')
name_list2 = html.xpath('//div[@id="list1"]/ul/li/a/text()')
sing_list2 = html.xpath('//div[@id="list1"]/ul/li/a/@href')
singer_name_list = name_list1 + name_list2
singer_sing_list = sing_list1 + sing_list2
# print(singer_name_list,singer_sing_list)
for i, name in enumerate(singer_name_list):
item = {}
item['名字'] = name
item['歌单'] = singer_sing_list[i]
# item['歌手信息']=parse_info(singer_sing_list[i])#被封了
write_json(item)
面向对象：
import json, requests
from lxml import etree
class KuDog(object):
def __init__(self):
self.base_url = 'https://www.kugou.com/yy/singer/index/%s-%s-1.html'
self.headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36'
}
self.parse()
# ---------------通过url获取该页面的内容，返回xpath对象
def get_xpath(self, url, headers):
try:
response = requests.get(url, headers=headers)
return etree.HTML(response.text)
except Exception:
print(url, '该页面没有相应！')
return ''
# --------------------通过歌手详情页获取歌手简介
def parse_info(self, url):
html = self.get_xpath(url, self.headers)
info = html.xpath('//div[@class="intro"]/p/text()')
return info[0]
# --------------------------写入方法
def write_json(self, value):
with open('kugou.json', 'a+', encoding='utf-8') as file:
json.dump(value, file)
# -----------------------------用ASCII码值来变换abcd...
def parse(self):
for j in range(97, 124):
# 小写字母为97-122，当等于123的时候我们按歌手名单的其他算，路由为null
if j < 123:
p = chr(j)
else:
p = "null"
for i in range(1, 6):
response = requests.get(self.base_url % (i, p), headers=self.headers)
# print(response.text)
html = etree.HTML(response.text)
# 由于数据分两个url，所以需要加起来数据列表
name_list1 = html.xpath('//ul[@id="list_head"]/li/strong/a/text()')
sing_list1 = html.xpath('//ul[@id="list_head"]/li/strong/a/@href')
name_list2 = html.xpath('//div[@id="list1"]/ul/li/a/text()')
sing_list2 = html.xpath('//div[@id="list1"]/ul/li/a/@href')
singer_name_list = name_list1 + name_list2
singer_sing_list = sing_list1 + sing_list2
# print(singer_name_list,singer_sing_list)
for i, name in enumerate(singer_name_list):
item = {}
item['名字'] = name
item['歌单'] = singer_sing_list[i]
# item['歌手信息']=parse_info(singer_sing_list[i])#被封了
print(item)
self.write_json(item)
music = KuDog()
案例 14：爬取扇贝读书图书信息（selenium+Phantomjs）
由于数据有 js 方法写入，因此不好在利用 requests 模块获取，所以使用 selenium+Phantomjs 获取
import time, json
from lxml import etree
from selenium import webdriver
base_url = 'https://search.douban.com/book/subject_search?search_text=python&cat=1001&start=%s'
driver = webdriver.PhantomJS()
def get_text(text):
if text:
return text[0]
return ''
def parse_page(text):
html = etree.HTML(text)
div_list = html.xpath('//div[@id="root"]/div/div/div/div/div/div[@class="item-root"]')
# print(div_list)
for div in div_list:
item = {}
'''
图书名称,评分,评价数,详情页链接,作者,出版社,价格,出版日期
'''
name = get_text(div.xpath('.//div[@class="title"]/a/text()'))
scores = get_text(div.xpath('.//span[@class="rating_nums"]/text()'))
comment_num = get_text(div.xpath('.//span[@class="pl"]/text()'))
detail_url = get_text(div.xpath('.//div[@class="title"]/a/@href'))
detail = get_text(div.xpath('.//div[@class="meta abstract"]/text()'))
if detail:
detail_list = detail.split('/')
else:
detail_list = ['未知', '未知', '未知', '未知']
# print(detail_list)
if all([name, detail_url]): # 如果名字和详情链接为true
item['书名'] = name
item['评分'] = scores
item['评论'] = comment_num
item['详情链接'] = detail_url
item['出版社'] = detail_list[-3]
item['价格'] = detail_list[-1]
item['出版日期'] = detail_list[-2]
author_list = detail_list[:-3]
author = ''
for aut in author_list:
author += aut + ' '
item['作者'] = author
print(item)
write_singer(item)
def write_singer(item):
with open('book.json', 'a+', encoding='utf-8') as file:
json.dump(item, file)
if __name__ == '__main__':
for i in range(10):
driver.get(base_url % (i * 15))
# 等待
time.sleep(2)
html_str = driver.page_source
parse_page(html_str)
面向对象：
from lxml import etree
from selenium import webdriver
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
from urllib import parse
class Douban(object):
def __init__(self, url):
self.url = url
self.driver = webdriver.PhantomJS()
self.wait = WebDriverWait(self.driver, 10)
self.parse()
# 判断数据是否存在，不存在返回空字符
def get_text(self, text):
if text:
return text[0]
return ''
def get_content_by_selenium(self, url, xpath):
self.driver.get(url)
# 等待,locator对象是一个元组,此处获取xpath对应的元素并加载出来
webelement = self.wait.until(EC.presence_of_element_located((By.XPATH, xpath)))
return self.driver.page_source
def parse(self):
html_str = self.get_content_by_selenium(self.url, '//div[@id="root"]/div/div/div/div')
html = etree.HTML(html_str)
div_list = html.xpath('//div[@id="root"]/div/div/div/div/div')
for div in div_list:
item = {}
'''图书名称+评分+评价数+详情页链接+作者+出版社+价格+出版日期'''
name = self.get_text(div.xpath('.//div[@class="title"]/a/text()'))
scores = self.get_text(div.xpath('.//span[@class="rating_nums"]/text()'))
comment_num = self.get_text(div.xpath('.//span[@class="pl"]/text()'))
detail_url = self.get_text(div.xpath('.//div[@class="title"]/a/@href'))
detail = self.get_text(div.xpath('.//div[@class="meta abstract"]/text()'))
if detail:
detail_list = detail.split('/')
else:
detail_list = ['未知', '未知', '未知', '未知']
if all([name, detail_url]): # 如果列表里的数据为true方可执行
item['书名'] = name
item['评分'] = scores
item['评论'] = comment_num
item['详情链接'] = detail_url
item['出版社'] = detail_list[-3]
item['价格'] = detail_list[-1]
item['出版日期'] = detail_list[-2]
author_list = detail_list[:-3]
author = ''
for aut in author_list:
author += aut + ' '
item['作者'] = author
print(item)
if __name__ == '__main__':
kw = 'python'
base_url = 'https://search.douban.com/book/subject_search?'
for i in range(10):
params = {
'search_text': kw,
'cat': '1001',
'start': str(i * 15),
}
url = base_url + parse.urlencode(params)
Douban(url)
案例 15：爬取腾讯招聘的招聘信息（selenium+Phantomjs）
import time
from lxml import etree
from selenium import webdriver
driver = webdriver.PhantomJS()
base_url = 'https://careers.tencent.com/search.html?index=%s'
job=[]
def getText(text):
if text:
return text[0]
else:
return ''
def parse(text):
html = etree.HTML(text)
div_list = html.xpath('//div[@class="correlation-degree"]/div[@class="recruit-wrap recruit-margin"]/div')
# print(div_list)
for i in div_list:
item = {}
job_name = i.xpath('a/h4/text()') # ------职位
job_loc = i.xpath('a/p/span[2]/text()') # --------地点
job_gangwei = i.xpath('a/p/span[3]/text()') # -----岗位
job_time = i.xpath('a/p/span[4]/text()') # -----发布时间
item['职位']=job_name
item['地点']=job_loc
item['岗位']=job_gangwei
item['发布时间']=job_time
job.append(item)
if __name__ == '__main__':
for i in range(1, 11):
driver.get(base_url % i)
text = driver.page_source
# print(text)
time.sleep(1)
parse(text)
print(job)
面向对象：
import json
from lxml import etree
from selenium import webdriver
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
from urllib import parse
class Tencent(object):
def __init__(self,url):
self.url = url
self.driver = webdriver.PhantomJS()
self.wait = WebDriverWait(self.driver,10)
self.parse()
def get_text(self,text):
if text:
return text[0]
return ''
def get_content_by_selenium(self,url,xpath):
self.driver.get(url)
webelement = self.wait.until(EC.presence_of_element_located((By.XPATH,xpath)))
return self.driver.page_source
def parse(self):
html_str = self.get_content_by_selenium(self.url,'//div[@class="correlation-degree"]')
html = etree.HTML(html_str)
div_list = html.xpath('//div[@class="recruit-wrap recruit-margin"]/div')
# print(div_list)
for div in div_list:
'''title,工作简介,工作地点,发布时间,岗位类别,详情页链接'''
job_name = self.get_text(div.xpath('.//h4[@class="recruit-title"]/text()'))
job_loc = self.get_text(div.xpath('.//p[@class="recruit-tips"]/span[2]/text()'))
job_gangwei = self.get_text(div.xpath('.//p/span[3]/text()') ) # -----岗位
job_time = self.get_text(div.xpath('.//p/span[4]/text()') ) # -----发布时间
item = {}
item['职位'] = job_name
item['地点'] = job_loc
item['岗位'] = job_gangwei
item['发布时间'] = job_time
print(item)
self.write_(item)
def write_(self,item):
with open('Tencent_job_100page.json', 'a+', encoding='utf-8') as file:
json.dump(item, file)
if __name__ == '__main__':
base_url = 'https://careers.tencent.com/search.html?index=%s'
for i in range(1,100):
Tencent(base_url %i)
案例 16：爬取腾讯招聘（ajax 版 + 多线程版）
通过分析我们发现，腾讯招聘使用的是 ajax 的数据接口，因此我们直接去寻找 ajax 的数据接口链接。
import requests, json
class Tencent(object):
def __init__(self):
self.base_url = 'https://careers.tencent.com/tencentcareer/api/post/Query?'
self.headers = {
'sec-fetch-mode': 'cors',
'sec-fetch-site': 'same-origin',
'user-agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'referer': 'https://careers.tencent.com/search.html'
}
self.parse()
def parse(self):
for i in range(1, 3):
params = {
'timestamp': '1572850838681',
'countryId': '',
'cityId': '',
'bgIds': '',
'productId': '',
'categoryId': '',
'parentCategoryId': '',
'attrId': '',
'keyword': '',
'pageIndex': str(i),
'pageSize': '10',
'language': 'zh-cn',
'area': 'cn'
}
response = requests.get(self.base_url, headers=self.headers, params=params)
self.parse_json(response.text)
def parse_json(self, text):
# 将json字符串编程python内置对象
infos = []
json_dict = json.loads(text)
for data in json_dict['Data']['Posts']:
RecruitPostName = data['RecruitPostName']
CategoryName = data['CategoryName']
Responsibility = data['Responsibility']
LastUpdateTime = data['LastUpdateTime']
detail_url = data['PostURL']
item = {}
item['RecruitPostName'] = RecruitPostName
item['CategoryName'] = CategoryName
item['Responsibility'] = Responsibility
item['LastUpdateTime'] = LastUpdateTime
item['detail_url'] = detail_url
# print(item)
infos.append(item)
self.write_to_file(infos)
def write_to_file(self, list_):
for item in list_:
with open('infos.txt', 'a+', encoding='utf-8') as fp:
fp.writelines(str(item))
if __name__ == '__main__':
t = Tencent()
改为多线程版后
import requests, json, threading
class Tencent(object):
def __init__(self):
self.base_url = 'https://careers.tencent.com/tencentcareer/api/post/Query?'
self.headers = {
'sec-fetch-mode': 'cors',
'sec-fetch-site': 'same-origin',
'user-agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'referer': 'https://careers.tencent.com/search.html'
}
self.parse()
def parse(self):
for i in range(1, 3):
params = {
'timestamp': '1572850838681',
'countryId': '',
'cityId': '',
'bgIds': '',
'productId': '',
'categoryId': '',
'parentCategoryId': '',
'attrId': '',
'keyword': '',
'pageIndex': str(i),
'pageSize': '10',
'language': 'zh-cn',
'area': 'cn'
}
response = requests.get(self.base_url, headers=self.headers, params=params)
self.parse_json(response.text)
def parse_json(self, text):
# 将json字符串编程python内置对象
infos = []
json_dict = json.loads(text)
for data in json_dict['Data']['Posts']:
RecruitPostName = data['RecruitPostName']
CategoryName = data['CategoryName']
Responsibility = data['Responsibility']
LastUpdateTime = data['LastUpdateTime']
detail_url = data['PostURL']
item = {}
item['RecruitPostName'] = RecruitPostName
item['CategoryName'] = CategoryName
item['Responsibility'] = Responsibility
item['LastUpdateTime'] = LastUpdateTime
item['detail_url'] = detail_url
# print(item)
infos.append(item)
self.write_to_file(infos)
def write_to_file(self, list_):
for item in list_:
with open('infos.txt', 'a+', encoding='utf-8') as fp:
fp.writelines(str(item))
if __name__ == '__main__':
tencent = Tencent()
t = threading.Thread(target=tencent.parse)
t.start()
改成多线程版的线程类：
import requests, json, threading
class Tencent(threading.Thread):
def __init__(self, i):
super().__init__()
self.i = i
self.base_url = 'https://careers.tencent.com/tencentcareer/api/post/Query?'
self.headers = {
'sec-fetch-mode': 'cors',
'sec-fetch-site': 'same-origin',
'user-agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'referer': 'https://careers.tencent.com/search.html'
}
def run(self):
self.parse()
def parse(self):
params = {
'timestamp': '1572850838681',
'countryId': '',
'cityId': '',
'bgIds': '',
'productId': '',
'categoryId': '',
'parentCategoryId': '',
'attrId': '',
'keyword': '',
'pageIndex': str(self.i),
'pageSize': '10',
'language': 'zh-cn',
'area': 'cn'
}
response = requests.get(self.base_url, headers=self.headers, params=params)
self.parse_json(response.text)
def parse_json(self, text):
# 将json字符串编程python内置对象
infos = []
json_dict = json.loads(text)
for data in json_dict['Data']['Posts']:
RecruitPostName = data['RecruitPostName']
CategoryName = data['CategoryName']
Responsibility = data['Responsibility']
LastUpdateTime = data['LastUpdateTime']
detail_url = data['PostURL']
item = {}
item['RecruitPostName'] = RecruitPostName
item['CategoryName'] = CategoryName
item['Responsibility'] = Responsibility
item['LastUpdateTime'] = LastUpdateTime
item['detail_url'] = detail_url
# print(item)
infos.append(item)
self.write_to_file(infos)
def write_to_file(self, list_):
for item in list_:
with open('infos.txt', 'a+', encoding='utf-8') as fp:
fp.writelines(str(item) + '
')
if __name__ == '__main__':
for i in range(1, 50):
t = Tencent(i)
t.start()
这样的弊端是如果有多个多线程同时运行，会导致系统的崩溃，因此我们使用队列，控制线程数量
import requests,json,time,threading
from queue import Queue
class Tencent(threading.Thread):
def __init__(self,url,headers,name,q):
super().__init__()
self.url= url
self.name = name
self.q = q
self.headers = headers
def run(self):
self.parse()
def write_to_file(self,list_):
with open('infos1.txt', 'a+', encoding='utf-8') as fp:
for item in list_:
fp.write(str(item))
def parse_json(self,text):
#将json字符串编程python内置对象
infos = []
json_dict = json.loads(text)
for data in json_dict['Data']['Posts']:
RecruitPostName = data['RecruitPostName']
CategoryName = data['CategoryName']
Responsibility = data['Responsibility']
LastUpdateTime = data['LastUpdateTime']
detail_url = data['PostURL']
item = {}
item['RecruitPostName'] = RecruitPostName
item['CategoryName'] = CategoryName
item['Responsibility'] = Responsibility
item['LastUpdateTime'] = LastUpdateTime
item['detail_url'] = detail_url
# print(item)
infos.append(item)
self.write_to_file(infos)
def parse(self):
while True:
if self.q.empty():
break
page = self.q.get()
print(f'==================第{page}页==========================in{self.name}')
params = {
'timestamp': '1572850797210',
'countryId':'',
'cityId':'',
'bgIds':'',
'productId':'',
'categoryId':'',
'parentCategoryId':'',
'attrId':'',
'keyword':'',
'pageIndex': str(page),
'pageSize': '10',
'language': 'zh-cn',
'area': 'cn'
}
response = requests.get(self.url,params=params,headers=self.headers)
self.parse_json(response.text)
if __name__ == '__main__':
start = time.time()
base_url = 'https://careers.tencent.com/tencentcareer/api/post/Query?'
headers= {
'referer': 'https: // careers.tencent.com / search.html',
'user-agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36',
'sec-fetch-mode': 'cors',
'sec-fetch-site': 'same-origin'
}
#1创建任务队列
q = Queue()
#2给队列添加任务，任务是每一页的页码
for page in range(1,50):
q.put(page)
# print(queue)
# while not q.empty():
# print(q.get())
#3.创建一个列表
crawl_list = ['aa','bb','cc','dd','ee']
list_ = []
for name in crawl_list:
t = Tencent(base_url,headers,name,q)
t.start()
list_.append(t)
for l in list_:
l.join()
# 3.4171955585479736
print(time.time()-start)
案例 17：爬取英雄联盟所有英雄名字和技能（selenium+phantomjs+ajax 接口）
from selenium import webdriver
from lxml import etree
import requests, json
driver = webdriver.PhantomJS()
base_url = 'https://lol.qq.com/data/info-heros.shtml'
driver.get(base_url)
html = etree.HTML(driver.page_source)
hero_url_list = html.xpath('.//ul[@id="jSearchHeroDiv"]/li/a/@href')
hero_list = [] # 存放所有英雄的列表
for hero_url in hero_url_list:
id = hero_url.split('=')[-1]
# print(id)
detail_url = 'https://game.gtimg.cn/images/lol/act/img/js/hero/' + id + '.js'
# print(detail_url)
headers = {
'Referer': 'https://lol.qq.com/data/info-defail.shtml?id =4',
'Sec-Fetch-Mode': 'cors',
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36'
}
response = requests.get(detail_url, headers=headers)
n = json.loads(response.text)
hero = [] # 存放单个英雄
item_name = {}
item_name['英雄名字'] = n['hero']['name'] + ' ' + n['hero']['title']
hero.append(item_name)
for i in n['spells']: # 技能
item_skill = {}
item_skill['技能名字'] = i['name']
item_skill['技能描述'] = i['description']
hero.append(item_skill)
hero_list.append(hero)
# print(hero_list)
with open('hero.json','w') as file:
json.dump(hero_list,file)
案例 18：爬取豆瓣电影（requests + 多线程）
需求：获得每个分类里的所有电影 
import json
import re, requests
from lxml import etree
# 获取网页的源码
def get_content(url, headers):
response = requests.get(url, headers=headers)
return response.text
# 获取电影指定信息
def get_movie_info(text):
text = json.loads(text)
item = {}
for data in text:
score = data['score']
image = data['cover_url']
title = data['title']
actors = data['actors']
detail_url = data['url']
vote_count = data['vote_count']
types = data['types']
item['评分'] = score
item['图片'] = image
item['电影名'] = title
item['演员'] = actors
item['详情页链接'] = detail_url
item['评价数'] = vote_count
item['电影类别'] = types
print(item)
# 获取电影api数据的
def get_movie(type, url):
headers = {
'X-Requested-With': 'XMLHttpRequest',
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
}
n = 0
# 获取api数据，并判断分页
while True:
text = get_content(url.format(type, n), headers=headers)
if text == '[]':
break
get_movie_info(text)
n += 20
# 主方法
def main():
base_url = 'https://movie.douban.com/chart'
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'Referer': 'https://movie.douban.com/explore'
}
html_str = get_content(base_url, headers=headers) # 分类页首页
html = etree.HTML(html_str)
movie_urls = html.xpath('//div[@class="types"]/span/a/@href') # 获得每个分类的连接，但是切割type
for url in movie_urls:
p = re.compile('type=(.*?)&interval_id=')
type_ = p.search(url).group(1)
ajax_url = 'https://movie.douban.com/j/chart/top_list?type={}&interval_id=100%3A90&action=&start={}&limit=20'
get_movie(type_, ajax_url)
if __name__ == '__main__':
main()
多线程
import json, threading
import re, requests
from lxml import etree
from queue import Queue
class DouBan(threading.Thread):
def __init__(self, q=None):
super().__init__()
self.base_url = 'https://movie.douban.com/chart'
self.headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'Referer': 'https://movie.douban.com/explore'
}
self.q = q
self.ajax_url = 'https://movie.douban.com/j/chart/top_list?type={}&interval_id=100%3A90&action=&start={}&limit=20'
# 获取网页的源码
def get_content(self, url, headers):
response = requests.get(url, headers=headers)
return response.text
# 获取电影指定信息
def get_movie_info(self, text):
text = json.loads(text)
item = {}
for data in text:
score = data['score']
image = data['cover_url']
title = data['title']
actors = data['actors']
detail_url = data['url']
vote_count = data['vote_count']
types = data['types']
item['评分'] = score
item['图片'] = image
item['电影名'] = title
item['演员'] = actors
item['详情页链接'] = detail_url
item['评价数'] = vote_count
item['电影类别'] = types
print(item)
# 获取电影api数据的
def get_movie(self):
headers = {
'X-Requested-With': 'XMLHttpRequest',
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
}
# 获取api数据，并判断分页
while True:
if self.q.empty():
break
n = 0
while True:
text = self.get_content(self.ajax_url.format(self.q.get(), n), headers=headers)
if text == '[]':
break
self.get_movie_info(text)
n += 20
# 获取所有类型的type——id
def get_types(self):
html_str = self.get_content(self.base_url, headers=self.headers) # 分类页首页
html = etree.HTML(html_str)
types = html.xpath('//div[@class="types"]/span/a/@href') # 获得每个分类的连接，但是切割type
# print(types)
type_list = []
for i in types:
p = re.compile('type=(.*?)&interval_id=') # 筛选id，拼接到api接口的路由
type = p.search(i).group(1)
type_list.append(type)
return type_list
def run(self):
self.get_movie()
if __name__ == '__main__':
# 创建消息队列
q = Queue()
# 将任务队列初始化，将我们的type放到消息队列中
t = DouBan()
types = t.get_types()
for tp in types:
q.put(tp[0])
# 创建一个列表，列表的数量就是开启线程的树木
crawl_list = [1, 2, 3, 4]
for crawl in crawl_list:
# 实例化对象
movie = DouBan(q=q)
movie.start()
案例 19：爬取瓜子二手车的所有车（requests）
需求：获得每个车类型的所有信息 
import json
import requests, re
from lxml import etree
# 获取网页的源码
def get_content(url, headers):
response = requests.get(url, headers=headers)
return response.text
# 获取子页原代码
def get_info(text):
item = {}
title_list = text.xpath('//ul[@class="carlist clearfix js-top"]/li/a/@title')
price_list = text.xpath('//div[@class="t-price"]/p/text()')
year_list = text.xpath('//div[@class="t-i"]/text()[1]')
millon_list = text.xpath('//div[@class="t-i"]/text()[2]')
picture_list = text.xpath('//ul[@class="carlist clearfix js-top"]/li/a/img/@src')
details_list = text.xpath('//ul[@class="carlist clearfix js-top"]/li/a/@href')
for i, title in enumerate(title_list):
item['标题'] = title
item['价格'] = price_list[i] + '万'
item['公里数'] = millon_list[i]
item['年份'] = year_list[i]
item['照片链接'] = picture_list[i]
item['详情页链接'] = 'https://www.guazi.com' + details_list[i]
print(item)
# 主函数
def main():
base_url = 'https://www.guazi.com/bj/buy/'
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'Cookie': 'track_id=7534369675321344; uuid=c129325e-6fea-4fd0-dea5-3632997e0419; antipas=wL2L859nHt69349594j71850u61; cityDomain=bj; clueSourceCode=10103000312%2300; user_city_id=12; ganji_uuid=6616956591030214317551; sessionid=5f3261c7-27a6-4bd6-e909-f70312d46c39; lg=1; cainfo=%7B%22ca_a%22%3A%22-%22%2C%22ca_b%22%3A%22-%22%2C%22ca_s%22%3A%22pz_baidu%22%2C%22ca_n%22%3A%22tbmkbturl%22%2C%22ca_medium%22%3A%22-%22%2C%22ca_term%22%3A%22-%22%2C%22ca_content%22%3A%22%22%2C%22ca_campaign%22%3A%22%22%2C%22ca_kw%22%3A%22-%22%2C%22ca_i%22%3A%22-%22%2C%22scode%22%3A%2210103000312%22%2C%22keyword%22%3A%22-%22%2C%22ca_keywordid%22%3A%22-%22%2C%22ca_transid%22%3A%22%22%2C%22platform%22%3A%221%22%2C%22version%22%3A1%2C%22track_id%22%3A%227534369675321344%22%2C%22display_finance_flag%22%3A%22-%22%2C%22client_ab%22%3A%22-%22%2C%22guid%22%3A%22c129325e-6fea-4fd0-dea5-3632997e0419%22%2C%22ca_city%22%3A%22bj%22%2C%22sessionid%22%3A%225f3261c7-27a6-4bd6-e909-f70312d46c39%22%7D; preTime=%7B%22last%22%3A1572951901%2C%22this%22%3A1572951534%2C%22pre%22%3A1572951534%7D',
}
html = etree.HTML(get_content(base_url, headers))
brand_url_list = html.xpath('//div[@class="dd-all clearfix js-brand js-option-hid-info"]/ul/li/p/a/@href')
for url in brand_url_list:
headers = {
'Referer': 'https://www.guazi.com/bj/buy/',
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'Cookie': 'track_id=7534369675321344; uuid=c129325e-6fea-4fd0-dea5-3632997e0419; antipas=wL2L859nHt69349594j71850u61; cityDomain=bj; clueSourceCode=10103000312%2300; user_city_id=12; ganji_uuid=6616956591030214317551; sessionid=5f3261c7-27a6-4bd6-e909-f70312d46c39; lg=1; cainfo=%7B%22ca_a%22%3A%22-%22%2C%22ca_b%22%3A%22-%22%2C%22ca_s%22%3A%22pz_baidu%22%2C%22ca_n%22%3A%22tbmkbturl%22%2C%22ca_medium%22%3A%22-%22%2C%22ca_term%22%3A%22-%22%2C%22ca_content%22%3A%22%22%2C%22ca_campaign%22%3A%22%22%2C%22ca_kw%22%3A%22-%22%2C%22ca_i%22%3A%22-%22%2C%22scode%22%3A%2210103000312%22%2C%22keyword%22%3A%22-%22%2C%22ca_keywordid%22%3A%22-%22%2C%22ca_transid%22%3A%22%22%2C%22platform%22%3A%221%22%2C%22version%22%3A1%2C%22track_id%22%3A%227534369675321344%22%2C%22display_finance_flag%22%3A%22-%22%2C%22client_ab%22%3A%22-%22%2C%22guid%22%3A%22c129325e-6fea-4fd0-dea5-3632997e0419%22%2C%22ca_city%22%3A%22bj%22%2C%22sessionid%22%3A%225f3261c7-27a6-4bd6-e909-f70312d46c39%22%7D; preTime=%7B%22last%22%3A1572953403%2C%22this%22%3A1572951534%2C%22pre%22%3A1572951534%7D',
}
brand_url = 'https://www.guazi.com' + url.split('/#')[0] + '/o%s/#bread' # 拼接每个品牌汽车的url
for i in range(1, 3):
html = etree.HTML(get_content(brand_url % i, headers=headers))
get_info(html)
if __name__ == '__main__':
main()
多线程：
import requests, threading
from lxml import etree
from queue import Queue
class Guazi(threading.Thread):
def __init__(self, list_=None):
super().__init__()
self.base_url = 'https://www.guazi.com/bj/buy/'
self.headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'Cookie': 'track_id=7534369675321344; uuid=c129325e-6fea-4fd0-dea5-3632997e0419; antipas=wL2L859nHt69349594j71850u61; cityDomain=bj; clueSourceCode=10103000312%2300; user_city_id=12; ganji_uuid=6616956591030214317551; sessionid=5f3261c7-27a6-4bd6-e909-f70312d46c39; lg=1; cainfo=%7B%22ca_a%22%3A%22-%22%2C%22ca_b%22%3A%22-%22%2C%22ca_s%22%3A%22pz_baidu%22%2C%22ca_n%22%3A%22tbmkbturl%22%2C%22ca_medium%22%3A%22-%22%2C%22ca_term%22%3A%22-%22%2C%22ca_content%22%3A%22%22%2C%22ca_campaign%22%3A%22%22%2C%22ca_kw%22%3A%22-%22%2C%22ca_i%22%3A%22-%22%2C%22scode%22%3A%2210103000312%22%2C%22keyword%22%3A%22-%22%2C%22ca_keywordid%22%3A%22-%22%2C%22ca_transid%22%3A%22%22%2C%22platform%22%3A%221%22%2C%22version%22%3A1%2C%22track_id%22%3A%227534369675321344%22%2C%22display_finance_flag%22%3A%22-%22%2C%22client_ab%22%3A%22-%22%2C%22guid%22%3A%22c129325e-6fea-4fd0-dea5-3632997e0419%22%2C%22ca_city%22%3A%22bj%22%2C%22sessionid%22%3A%225f3261c7-27a6-4bd6-e909-f70312d46c39%22%7D; preTime=%7B%22last%22%3A1572951901%2C%22this%22%3A1572951534%2C%22pre%22%3A1572951534%7D',
}
self.list_ = list_
# 获取网页的源码
def get_content(self, url, headers):
response = requests.get(url, headers=headers)
return response.text
# 获取子页原代码
def get_info(self, text):
item = {}
title_list = text.xpath('//ul[@class="carlist clearfix js-top"]/li/a/@title')
price_list = text.xpath('//div[@class="t-price"]/p/text()')
year_list = text.xpath('//div[@class="t-i"]/text()[1]')
millon_list = text.xpath('//div[@class="t-i"]/text()[2]')
picture_list = text.xpath('//ul[@class="carlist clearfix js-top"]/li/a/img/@src')
details_list = text.xpath('//ul[@class="carlist clearfix js-top"]/li/a/@href')
for i, title in enumerate(title_list):
item['标题'] = title
item['价格'] = price_list[i] + '万'
item['公里数'] = millon_list[i]
item['年份'] = year_list[i]
item['照片链接'] = picture_list[i]
item['详情页链接'] = 'https://www.guazi.com' + details_list[i]
print(item)
# 获取汽车链接列表
def get_carsurl(self):
html = etree.HTML(self.get_content(self.base_url, self.headers))
brand_url_list = html.xpath('//div[@class="dd-all clearfix js-brand js-option-hid-info"]/ul/li/p/a/@href')
brand_url_list = ['https://www.guazi.com' + url.split('/#')[0] + '/o%s/#bread' for url in brand_url_list]
return brand_url_list
def run(self):
while True:
if self.list_.empty():
break
url = self.list_.get()
for i in range(1, 3):
html = etree.HTML(self.get_content(url % i, headers=self.headers))
self.get_info(html)
if __name__ == '__main__':
q = Queue()
gz = Guazi()
cars_url = gz.get_carsurl()
for car in cars_url:
q.put(car)
# 创建一个列表，列表的数量就是开启线程的树木
crawl_list = [1, 2, 3, 4]
for crawl in crawl_list:
# 实例化对象
car = Guazi(list_=q)
car.start()
结果： 
案例 20：爬取链家网北京每个区域的所有房子（selenium+Phantomjs + 多线程）
#爬取链家二手房信息。
# 要求：
# 1.爬取的字段:
# 名称,房间规模、价格,建设时间,朝向,详情页链接
# 2.写三个文件：
# 1.简单py 2.面向对象 3.改成多线程
from selenium import webdriver
from lxml import etree
def get_element(url):
driver.get(url)
html = etree.HTML(driver.page_source)
return html
lis = [] # 存放所有区域包括房子
driver = webdriver.PhantomJS()
html = get_element('https://bj.lianjia.com/ershoufang/')
city_list = html.xpath('//div[@data-role="ershoufang"]/div/a/@href')
city_name_list = html.xpath('//div[@data-role="ershoufang"]/div/a/text()')
for num, city in enumerate(city_list):
item = {} # 存放一个区域
sum_house = [] # 存放每个区域的房子
item['区域'] = city_name_list[num] # 城区名字
for page in range(1, 3):
city_url = 'https://bj.lianjia.com' + city + 'pg' + str(page)
html = get_element(city_url)
'''名称, 房间规模，建设时间, 朝向, 详情页链接'''
title_list = html.xpath('//div[@class="info clear"]/div/a/text()') # 所有标题
detail_url_list = html.xpath('//div[@class="info clear"]/div/a/@href') # 所有详情页
detail_list = html.xpath('//div[@class="houseInfo"]/text()') # 该页所有的房子信息列表，
city_price_list = html.xpath('//div[@class="totalPrice"]/span/text()')
for i, content in enumerate(title_list):
house = {}
detail = detail_list[i].split('|')
house['名称'] = content # 名称
house['价格']=city_price_list[i]+'万'#价格
house['规模'] = detail[0] + detail[1] # 规模
house['建设时间'] = detail[-2] # 建设时间
house['朝向'] = detail[2] # 朝向
house['详情链接'] = detail_url_list[i] # 详情链接
sum_house.append(house)
item['二手房'] = sum_house
print(item)
lis.append(item)
面向对象 + 多线程：
import json, threading
from selenium import webdriver
from lxml import etree
from queue import Queue
class Lianjia(threading.Thread):
def __init__(self, city_list=None, city_name_list=None):
super().__init__()
self.driver = webdriver.PhantomJS()
self.city_name_list = city_name_list
self.city_list = city_list
def get_element(self, url): # 获取element对象的
self.driver.get(url)
html = etree.HTML(self.driver.page_source)
return html
def get_city(self):
html = self.get_element('https://bj.lianjia.com/ershoufang/')
city_list = html.xpath('//div[@data-role="ershoufang"]/div/a/@href')
city_list = ['https://bj.lianjia.com' + url + 'pg%s' for url in city_list]
city_name_list = html.xpath('//div[@data-role="ershoufang"]/div/a/text()')
return city_list, city_name_list
def run(self):
lis = [] # 存放所有区域包括房子
while True:
if self.city_name_list.empty() and self.city_list.empty():
break
item = {} # 存放一个区域
sum_house = [] # 存放每个区域的房子
item['区域'] = self.city_name_list.get() # 城区名字
for page in range(1, 3):
# print(self.city_list.get())
html = self.get_element(self.city_list.get() % page)
'''名称, 房间规模，建设时间, 朝向, 详情页链接'''
title_list = html.xpath('//div[@class="info clear"]/div/a/text()') # 所有标题
detail_url_list = html.xpath('//div[@class="info clear"]/div/a/@href') # 所有详情页
detail_list = html.xpath('//div[@class="houseInfo"]/text()') # 该页所有的房子信息列表，
for i, content in enumerate(title_list):
house = {}
detail = detail_list[i].split('|')
house['名称'] = content # 名称
house['规模'] = detail[0] + detail[1] # 规模
house['建设时间'] = detail[-2] # 建设时间
house['朝向'] = detail[2] # 朝向
house['详情链接'] = detail_url_list[i] # 详情链接
sum_house.append(house)
item['二手房'] = sum_house
lis.append(item)
print(item)
if __name__ == '__main__':
q1 = Queue()#路由
q2 = Queue()#名字
lj = Lianjia()
city_url, city_name = lj.get_city()
for c in city_url:
q1.put(c)
for c in city_name:
q2.put(c)
# 创建一个列表，列表的数量就是开启线程的数量
crawl_list = [1, 2, 3, 4, 5]
for crawl in crawl_list:
# 实例化对象
LJ = Lianjia(city_name_list=q2,city_list=q1)
LJ.start()
结果： 
案例 21：爬取笔趣阁的所有小说（requests）
import requests
from lxml import etree
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'Referer': 'http://www.xbiquge.la/7/7931/',
'Cookie': '_abcde_qweasd=0; BAIDU_SSP_lcr=https://www.baidu.com/link?url=jUBgtRGIR19uAr-RE9YV9eHokjmGaII9Ivfp8FJIwV7&wd=&eqid=9ecb04b9000cdd69000000035dc3f80e; Hm_lvt_169609146ffe5972484b0957bd1b46d6=1573124137; _abcde_qweasd=0; bdshare_firstime=1573124137783; Hm_lpvt_169609146ffe5972484b0957bd1b46d6=1573125463',
'Accept-Encoding': 'gzip, deflate'
}
# 获取网站源码
def get_text(url, headers):
response = requests.get(url, headers=headers)
response.encoding = 'utf-8'
return response.text
# 获取小说的信息
def get_novelinfo(list1, name_list):
for i, url in enumerate(list1):
html = etree.HTML(get_text(url, headers))
name = name_list[i] # 书名
title_url = html.xpath('//div[@id="list"]/dl/dd/a/@href')
title_url = ['http://www.xbiquge.la' + i for i in title_url] # 章节地址
titlename_list = html.xpath('//div[@id="list"]/dl/dd/a/text()') # 章节名字列表
get_content(title_url, titlename_list, name)
# # 获取小说每章节的内容
def get_content(url_list, title_list, name):
for i, url in enumerate(url_list):
item = {}
html = etree.HTML(get_text(url, headers))
content_list = html.xpath('//div[@id="content"]/text()')
content = ''.join(content_list)
content=content+'
'
item['title'] = title_list[i]
item['content'] = content.replace('
', '
').replace('xa0', ' ')
print(item)
with open(name + '.txt', 'a+',encoding='utf-8') as file:
file.write(item['title']+'
')
file.write(item['content'])
def main():
base_url = 'http://www.xbiquge.la/xiaoshuodaquan/'
html = etree.HTML(get_text(base_url, headers))
novelurl_list = html.xpath('//div[@class="novellist"]/ul/li/a/@href')
name_list = html.xpath('//div[@class="novellist"]/ul/li/a/text()')
get_novelinfo(novelurl_list, name_list)
if __name__ == '__main__':
main()
多线程
import requests, threading
from lxml import etree
from queue import Queue
class Novel(threading.Thread):
def __init__(self, novelurl_list=None, name_list=None):
super().__init__()
self.headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'Referer': 'http://www.xbiquge.la/7/7931/',
'Cookie': '_abcde_qweasd=0; BAIDU_SSP_lcr=https://www.baidu.com/link?url=jUBgtRGIR19uAr-RE9YV9eHokjmGaII9Ivfp8FJIwV7&wd=&eqid=9ecb04b9000cdd69000000035dc3f80e; Hm_lvt_169609146ffe5972484b0957bd1b46d6=1573124137; _abcde_qweasd=0; bdshare_firstime=1573124137783; Hm_lpvt_169609146ffe5972484b0957bd1b46d6=1573125463',
'Accept-Encoding': 'gzip, deflate'
}
self.novelurl_list = novelurl_list
self.name_list = name_list
# 获取网站源码
def get_text(self, url):
response = requests.get(url, headers=self.headers)
response.encoding = 'utf-8'
return response.text
# 获取小说的信息
def get_novelinfo(self):
while True:
if self.name_list.empty() and self.novelurl_list.empty():
break
url = self.novelurl_list.get()
# print(url)
html = etree.HTML(self.get_text(url))
name = self.name_list.get() # 书名
# print(name)
title_url = html.xpath('//div[@id="list"]/dl/dd/a/@href')
title_url = ['http://www.xbiquge.la' + i for i in title_url] # 章节地址
titlename_list = html.xpath('//div[@id="list"]/dl/dd/a/text()') # 章节名字列表
self.get_content(title_url, titlename_list, name)
# # 获取小说每章节的内容
def get_content(self, url_list, title_list, name):
for i, url in enumerate(url_list):
item = {}
html = etree.HTML(self.get_text(url))
content_list = html.xpath('//div[@id="content"]/text()')
content = ''.join(content_list)
content = content + '
'
item['title'] = title_list[i]
item['content'] = content.replace('
', '
').replace('xa0', ' ')
print(item)
with open(name + '.txt', 'a+', encoding='utf-8') as file:
file.write(item['title'] + '
')
file.write(item['content'])
#------------------通过多线程，返回每本书的名字和每本书的连接
def get_name_url(self):
base_url = 'http://www.xbiquge.la/xiaoshuodaquan/'
html = etree.HTML(self.get_text(base_url))
novelurl_list = html.xpath('//div[@class="novellist"]/ul/li/a/@href')
name_list = html.xpath('//div[@class="novellist"]/ul/li/a/text()')
return novelurl_list, name_list
def run(self):
self.get_novelinfo()
if __name__ == '__main__':
n = Novel()
url_list, name_list = n.get_name_url()
name_queue = Queue()
url_queue = Queue()
for url in url_list:
url_queue.put(url)
for name in name_list:
name_queue.put(name)
crawl_list = [1, 2, 3, 4, 5] # 定义五个线程
for crawl in crawl_list:
# 实例化对象
novel = Novel(name_list=name_queue, novelurl_list=url_queue)
novel.start()
结果： 
案例 22：爬取新浪微博头条前 20 页（ajax+mysql）
import requests, pymysql
from lxml import etree
def get_element(i):
base_url = 'https://weibo.com/a/aj/transform/loadingmoreunlogin?'
headers = {
'Referer': 'https://weibo.com/?category=1760',
'Sec-Fetch-Mode': 'cors',
'Sec-Fetch-Site': 'same-origin',
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
'X-Requested-With': 'XMLHttpRequest'
}
params = {
'ajwvr': '6',
'category': '1760',
'page': i,
'lefnav': '0',
'cursor': '',
'__rnd': '1573735870072',
}
response = requests.get(base_url, headers=headers, params=params)
response.encoding = 'utf-8'
info = response.json()
return etree.HTML(info['data'])
def main():
for i in range(1, 20):
html = get_element(i)
# 标题，发布人，发布时间,详情链接
title = html.xpath('//a[@class="S_txt1"]/text()')
author_time = html.xpath('//span[@class]/text()')
author = [author_time[i] for i in range(len(author_time)) if i % 2 == 0]
time = [author_time[i] for i in range(len(author_time)) if i % 2 == 1]
url = html.xpath('//a[@class="S_txt1"]/@href')
for j,tit in enumerate(title):
title1=tit
time1=time[j]
url1=url[j]
author1=author[j]
# print(title1,url1,time1,author1)
connect_mysql(title1,time1,author1,url1)
def connect_mysql(title, time, author, url):
db = pymysql.connect(host='localhost', user='root', password='123456',database='news')
cursor = db.cursor()
sql = 'insert into sina_news(title,send_time,author,url) values("' + title + '","' + time + '","' + author + '","' + url + '")'
print(sql)
cursor.execute(sql)
db.commit()
cursor.close()
db.close()
if __name__ == '__main__':
main()
提前创库 news 和表 sina_news
create table sina_news(
id int not null auto_increment primary key,
title varchar(100),
send_time varchar(100),
author varchar(20),
url varchar(100)
);
案例 23：爬取搜狗指定图片（requests + 多线程）
```python
import requests, json, threading, time, os
from queue import Queue
class Picture(threading.Thread):
# 初始化
def __init__(self, num, search, url_queue=None):
super().__init__()
self.headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36'
}
self.num = num
self.search = search
# 获取爬取的页数的每页图片接口url
def get_url(self):
url_list = []
for start in range(self.num):
url = 'https://pic.sogou.com/pics?query=' + self.search + '&mode=1&start=' + str(
start * 48) + '&reqType=ajax&reqFrom=result&tn=0'
url_list.append(url)
return url_list
# 获取每页的接口资源详情
def get_page(self, url):
response = requests.get(url.format('蔡徐坤'), headers=self.headers)
return response.text
#
def run(self):
while True:
# 如果队列为空代表制定页数爬取完毕
if url_queue.empty():
break
else:
url = url_queue.get() # 本页地址
data = json.loads(self.get_page(url)) # 获取到本页图片接口资源
try:
# 每页48张图片
for i in range(1, 49):
pic = data['items'][i]['pic_url']
reponse = requests.get(pic)
# 如果文件夹不存在，则创建
if not os.path.exists(r'C:/Users/Administrator/Desktop/' + self.search):
os.mkdir(r'C:/Users/Administrator/Desktop/' + self.search)
with open(r'C:/Users/Administrator/Desktop/' + self.search + '/%s.jpg' % (
str(time.time()).replace('.', '_')), 'wb') as f:
f.write(reponse.content)
print('下载成功！')
except:
print('该页图片保存完毕')
if __name__ == '__main__':
# 1.获取初始化的爬取url
num = int(input('请输入爬取页数（每页48张）：'))
content = input('请输入爬取内容：')
pic = Picture(num, content)
url_list = pic.get_url()
# 2.创建队列
url_queue = Queue()
for i in url_list:
url_queue.put(i)
# 3.创建线程任务
crawl = [1, 2, 3, 4, 5]
for i in crawl:
pic = Picture(num, content, url_queue=url_queue)
pic.start()
案例 24：爬取链家网北京所有房子（requests + 多线程）
链家：https://bj.fang.lianjia.com/loupan/
-
1、获取所有的城市的拼音
-
2、根据拼音去拼接 url，获取所有的数据。
-
3、列表页：楼盘名称，均价，建筑面积，区域，商圈详情页：户型（[“8 室 5 厅 8 卫”, “4 室 2 厅 3 卫”, “5 室 2 厅 2 卫”]）, 朝向，图片（列表），用户点评（选爬）
难点 1： 当该区没房子的时候，猜你喜欢这个会和有房子的块 class 一样，因此需要判断 
难点 2： 获取每个区的页数，使用 js 将页数隐藏 https://bj.fang.lianjia.com/loupan / 区 / pg 页数 %s 我们可以发现规律，明明三页，当我们写 pg5 时候，会跳转第一页 因此我们可以使用 while 判断，当每个房子的链接和该区最大房子数相等代表该区爬取完毕 
完整代码：
import requests
from lxml import etree
# 获取网页源码
def get_html(url):
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
}
response = requests.get(url, headers=headers)
return response.text
# 获取城市拼音列表
def get_city_url():
url = 'https://bj.fang.lianjia.com/loupan/'
html = etree.HTML(get_html(url))
city = html.xpath('//div[@class="filter-by-area-container"]/ul/li/@data-district-spell')
city_url = ['https://bj.fang.lianjia.com/loupan/{}/pg%s'.format(i) for i in city]
return city_url
# 爬取对应区的所有房子url
def get_detail(url):
# 使用第一页来判断是否有分页
html = etree.HTML(get_html(url % (1)))
empty = html.xpath('//div[@class="no-result-wrapper hide"]')
if len(empty) != 0: # 不存在此标签代表没有猜你喜欢
i = 1
max_house = html.xpath('//span[@class="value"]/text()')[0]
house_url = []
while True: # 分页
html = etree.HTML(get_html(url % (i)))
house_url += html.xpath('//ul[@class="resblock-list-wrapper"]/li/a/@href')
i += 1
if len(house_url) == int(max_house):
break
detail_url = ['https://bj.fang.lianjia.com/' + i for i in house_url] # 该区所有房子的url
info(detail_url)
# 获取每个房子的详细信息
def info(url):
for i in url:
item = {}
page = etree.HTML(get_html(i))
item['name'] = page.xpath('//h2[@class="DATA-PROJECT-NAME"]/text()')[0]
item['price_num'] = page.xpath('//span[@class="price-number"]/text()')[0] + page.xpath(
'//span[@class="price-unit"]/text()')[0]
detail_page = etree.HTML(get_html(i + 'xiangqing'))
item['type'] = detail_page.xpath('//ul[@class="x-box"]/li[1]/span[2]/text()')[0]
item['address'] = detail_page.xpath('//ul[@class="x-box"]/li[5]/span[2]/text()')[0]
item['shop_address'] = detail_page.xpath('//ul[@class="x-box"]/li[6]/span[2]/text()')[0]
print(item)
def main():
# 1、获取所有的城市的拼音
city = get_city_url()
# 2、根据拼音去拼接url，获取所有的数据。
for url in city:
get_detail(url)
if __name__ == '__main__':
main()
多线程版：
import requests, threading
from lxml import etree
from queue import Queue
import pymongo
class House(threading.Thread):
def __init__(self, q=None):
super().__init__()
self.headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36',
}
self.q = q
# 获取网页源码
def get_html(self, url):
response = requests.get(url, headers=self.headers)
return response.text
# 获取城市拼音列表
def get_city_url(self):
url = 'https://bj.fang.lianjia.com/loupan/'
html = etree.HTML(self.get_html(url))
city = html.xpath('//div[@class="filter-by-area-container"]/ul/li/@data-district-spell')
city_url = ['https://bj.fang.lianjia.com/loupan/{}/pg%s'.format(i) for i in city]
return city_url
# 爬取对应区的所有房子url
def get_detail(self, url):
# 使用第一页来判断是否有分页
html = etree.HTML(self.get_html(url % (1)))
empty = html.xpath('//div[@class="no-result-wrapper hide"]')
if len(empty) != 0: # 不存在此标签代表没有猜你喜欢
i = 1
max_house = html.xpath('//span[@class="value"]/text()')[0]
house_url = []
while True: # 分页
html = etree.HTML(self.get_html(url % (i)))
house_url += html.xpath('//ul[@class="resblock-list-wrapper"]/li/a/@href')
i += 1
if len(house_url) == int(max_house):
break
detail_url = ['https://bj.fang.lianjia.com/' + i for i in house_url] # 该区所有房子的url
self.info(detail_url)
# 获取每个房子的详细信息
def info(self, url):
for i in url:
item = {}
page = etree.HTML(self.get_html(i))
item['name'] = page.xpath('//h2[@class="DATA-PROJECT-NAME"]/text()')[0]
item['price_num'] = page.xpath('//span[@class="price-number"]/text()')[0] + page.xpath(
'//span[@class="price-unit"]/text()')[0]
detail_page = etree.HTML(self.get_html(i + 'xiangqing'))
item['type'] = detail_page.xpath('//ul[@class="x-box"]/li[1]/span[2]/text()')[0]
item['address'] = detail_page.xpath('//ul[@class="x-box"]/li[5]/span[2]/text()')[0]
item['shop_address'] = detail_page.xpath('//ul[@class="x-box"]/li[6]/span[2]/text()')[0]
print(item)
def run(self):
# 1、获取所有的城市的拼音
# city = self.get_city_url()
# 2、根据拼音去拼接url，获取所有的数据。
while True:
if self.q.empty():
break
self.get_detail(self.q.get())
if __name__ == '__main__':
# 1.先获取区列表
house = House()
city_list = house.get_city_url()
# 2.将去加入队列
q = Queue()
for i in city_list:
q.put(i)
# 3.创建线程任务
a = [1, 2, 3, 4]
for i in a:
p = House(q)
p.start()