python爬虫安装requests(python爬虫requests库)

requests是Python用于网络(http)请求的第三库，也是爬虫获取网络数据的重要工具，使用的时候需要导入

import requests

语法:

requests.get(url,*,headers, proxies, timeout)   -  以指定的方式给地址发送网络请求，返回值是服务器返回的响应对象

参数说明:

url - 字符串；请求的网络地址，可能是目标网站的网址也可能是数据接口headers - 字典；请求头，用于伪装浏览器设置user-agent、完成自动登录设置cookieproxies - 字典；设置代理ip(ip地址被封的时候使用)timeout - 数字；设置超时时间

url = 'https://search.51job.com/list/000000,000000,0000,00,9,99,数据分析,2,1.html?lang=c&postchannel=0000&workyear=99&cotype=99°reefrom=99&jobterm=99&companysize=99&ord_field=0&dibiaoid=0&line=&welfare='
headers = {
    'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.51 Safari/537.36'
}
response = requests.get(url, headers=headers)

print(response.headers)

response.encoding = 'gbk'

获取字符串格式的结果(爬网页)

print(response.text)

获取二进制格式的结果(爬图片、视频、音频)

print(response.content)

获取json解析的结果(爬接口数据)

print(response.json())

import requests

url = 'https://cd.zu.ke.com/zufang'
response = requests.get(url)
print(response.text)

import requests

# 1. 对图片地址发送请求
url = 'https://www.baidu.com/img/PCtm_d9c8750bed0b3c7d089fa7d55720d6cf.png'
response = requests.get(url)

# 2. 保存图片数据到本地
open('files/a.png', 'wb').write(response.content)

import requests
import os

url = 'https://game.gtimg.cn/images/lol/act/img/js/heroList/hero_list.js'
response = requests.get(url)

count = 0
for hero in response.json()['hero']:
    print(hero['name'])
    a_url = hero['selectAudio']
    res = requests.get(a_url)
    open(f'files/{os.path.basename(a_url)}', 'bw').write(res.content)
    count += 1
    if count == 10:
        break

注意：安装第三方库的时候安装beautifulSoup4而不是bs4

from bs4 import BeautifulSoup

BeautifulSoup(html代码, 'lxml')   -  返回网页对象

基于整个网页获取标签

BeautifulSoup对象.select(css选择器)   -   返回css选择器在整个网页中选中的所有标签；返回值是列表，列表中元素是标签对象
BeautifulSoup对象.select_one(css选择器)  -  返回css选择器在整个网页中选中的第一个标签，返回值是标签对象

result = soup.select('p')
print(result)

result = soup.select('.c1')
print(result)

result = soup.select('div>p')
print(result)

result = soup.select_one('p')
print(result)

result = soup.select_one('div>p')
print(result)

基于指定标签获取标签

标签对象.select(css选择器)   -   在指定标签中按照选择器选中相关标签
标签对象.select_one(css选择器)

div1 = soup.select_one('#box')
result = div1.select('p')
print(result)

获取标签内容

标签对象.text

result = soup.select_one('#p2').text
print(result)   # 我是段落2

result = soup.select_one('#p2').string
print(result)

result = soup.select_one('#p2').contents
print(result)

# 获取所有p标签的标签内容
for p in soup.select('p'):
    print(p.text)

获取标签属性

标签对象.attrs[属性名]

result = soup.select_one('#a1').attrs
print(result)       # {'id': 'a1', 'href': 'https://www.baidu.com'}
result = soup.select_one('#a1').attrs['href']
print(result)       # 'https://www.baidu.com'

result = soup.select_one('img').attrs['src']
print(result)

result = soup.select_one('img').attrs['alt']
print(result)

import requests
from bs4 import BeautifulSoup
from re import search, findall
import csv

# 1. 获取网页数据
url = 'https://movie.douban.com/top250'
headers = {
    'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.51 Safari/537.36'
}
response = requests.get(url, headers=headers)

# 2. 解析数据
soup = BeautifulSoup(response.text, 'lxml')
all_li = soup.select('.grid_view>li')
all_data = []
for li in all_li:
    # 电影名
    name = li.select_one('.title').text
    result = li.select_one('.bd>p').text.strip().replace(' ', '')
    # 导演
    director = search(r'导演:(.+?)s', result).group(1)
    # 主演
    actor = search(r'主演:(.+?)s', result).group(1)
    # 上映时间
    time = search(r'n(d+)s*/', result).group(1)
    # 国家
    country = search(r'/s*(.+?)s*/', result).group(1)
    # 类型
    type = search(r'/.+?/s*(.+?)$', result).group(1)
    # 评分
    score = li.select_one('.rating_num').text
    # 人数
    comment_num = li.select('.star>span')[-1].text
    comment_num = search(r'd+', comment_num).group()
    # 图片地址
    img_url = li.select_one('.pic img').attrs['src']

    # 保存数据
    all_data.append([name, director, actor, time, country, type, score, comment_num, img_url])

writer = csv.writer(open('files/电影.csv', 'w', encoding='utf-8', newline=''))
writer.writerow(['电影名称', '导演', '主演', '上映时间', '国家', '类型','评分', '评论人数', '封面地址'])
writer.writerows(all_data)