初始爬虫

什么是爬虫：通过编写程序模拟浏览器上网，然后让其去互联网上爬取数据的过程

- 爬虫的分类：
    - 通用爬虫：
        - 抓取互联网中的一整张页面数据
    - 聚焦爬虫：
        - 抓取页面中的局部数据
    - 增量式爬虫：
        - 用来监测网站数据更新的情况，以便爬取到网站最新更新出来的数据

request模块的使用

#爬取搜狗首页的页面源码数据
import requests
#1.指定url
url = 'https://www.sogou.com/'
#2.请求发送get:get返回值是一个响应对象
response = requests.get(url=url)
#3.获取响应数据 
page_text = response.text #返回的是字符串形式的响应数据
#4.持久化存储
with open('sogou.html','w',encoding='utf-8') as fp:
    fp.write(page_text)

#实现一个简易的网页采集器
#需要让url携带的参数动态化
url = 'https://www.sogou.com/web'
#实现参数动态化
wd = input('enter a key:')
params = {
    'query':wd
}
#在请求中需要将请求参数对应的字典作用到params这个get方法的参数中
response = requests.get(url=url,params=params)

page_text = response.text
fileName = wd+'.html'
with open(fileName,'w',encoding='utf-8') as fp:
    fp.write(page_text)

上述代码执行后发现：

1.出现了乱码
2.数据量级不对

#解决乱码

url = 'https://www.sogou.com/web'
#实现参数动态化
wd = input('enter a key:')
params = {
    'query':wd
}
#在请求中需要将请求参数对应的字典作用到params这个get方法的参数中
response = requests.get(url=url,params=params)
response.encoding = 'utf-8' #修改响应数据的编码格式
page_text = response.text
fileName = wd+'.html'
with open(fileName,'w',encoding='utf-8') as fp:
    fp.write(page_text)

UA检测：门户网站通过检测请求载体的身份标识判定改请求是否为爬虫发起的请求
UA伪装：Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.132 Safari/537.36

#解决UA检测
url = 'https://www.sogou.com/web'
#实现参数动态化
wd = input('enter a key:')
params = {
    'query':wd
}
headers = {
    'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.132 Safari/537.36'
}
#在请求中需要将请求参数对应的字典作用到params这个get方法的参数中
response = requests.get(url=url,params=params,headers=headers)
response.encoding = 'utf-8' #修改响应数据的编码格式
page_text = response.text
fileName = wd+'.html'
with open(fileName,'w',encoding='utf-8') as fp:
    fp.write(page_text)

动态加载的页面数据

是通过另一个单独的请求请求到的数据

# 爬取豆瓣排行
url = 'https://movie.douban.com/j/chart/top_list'
start = input('您想从第几部电影开始获取:')
limit = input('您想获取多少电影数据:')
dic = {
    'type': '13',
    'interval_id': '100:90',
    'action': '',
    'start': start,
    'limit': limit,
}
response = requests.get(url=url,params=dic,headers=headers)
page_text = response.json() #json()返回的是序列化好的实例对象
for dic in page_text:
    print(dic['title']+':'+dic['score'])

#肯德基餐厅查询http://www.kfc.com.cn/kfccda/storelist/index.aspx
url = 'http://www.kfc.com.cn/kfccda/ashx/GetStoreList.ashx?op=keyword'

adderss = input('请输入查询的关键字')
for i in range(1,5):
    dic = {
        'cname': '',
        'pid': '',
        'keyword': adderss,
        'pageIndex': str(i),
        'pageSize': '10',
    }
    response = requests.post(url=url, headers=headers, data=dic)
    page_text = response.json()

    for a in page_text['Table1']:
        print('餐厅名称:',a['storeName']+'餐厅','---- 餐厅地址:',a['addressDetail'])

练习爬取药监总局中相关企业的详情信息http://125.35.6.84:81/xk/

# 国家药品监督管理局

import requests
url = 'http://125.35.6.84:81/xk/itownet/portalAction.do?method=getXkzsList'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.132 Safari/537.36'
}
dic = {
    'on': 'true',
    'page': '1',
    'pageSize': '15',
    'productName':'',
    'conditionType': '1',
    'applyname': '',
    'applysn':'',
}
response = requests.post(url=url, headers=headers, data=dic)
page_text = response.json()
for page in page_text['list']:
    # print(page['EPS_NAME'],page['ID'])
    _url = 'http://125.35.6.84:81/xk/itownet/portalAction.do?method=getXkzsById'
    _dic = {
        'id': page['ID']
    }
    _response = requests.get(url=_url, headers=headers, params=_dic)
    _page_text = _response.json()
    print(_page_text['epsName'],'-----',_page_text['legalPerson'])

python爬虫：初始爬虫一

初始爬虫

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