Skip to content

聚焦爬虫

过滤爬取到的数据，取出想要的部分

聚焦爬虫：爬取页面中指定的页面内容

  • 编码流程

    1. 指定url
    2. 发起请求
    3. 获取响应数据
    4. 数据解析
    5. 持久化存储

  • 数据解析分类

    1. 正则表达式
    2. bs4
    3. xpath (*)

数据解析原理 - 解析的局部文本内容都会在标签之间或标签的属性中存储 - 1. 进行标签的定位 - 2. 标签或者标签对应的属性中存储的数据值进行提取（即解析~~）

正则表达式爬取

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
import os
import requests
import re

# UA伪装
UA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.89 Safari/537.36 Edg/84.0.522.44'
header = {'User-Agent': UA}

# 存储目录
folder = './qiushi'
if not os.path.exists(folder):
    os.mkdir(folder)


def main():
    # 分页处理
    for i in range(1, 3):
        url = f"https://www.qiushibaike.com/imgrank/page/{i}/"
        # 1. 爬取整张页面
        page_text = requests.get(url=url, headers=header).text
        # 2. 使用聚焦爬虫进行数据解析
        images = data_parse(page_text)

        length = len(images)  # 进度条所需

        for index, image in enumerate(images):
            # 3. 发起请求并获得数据
            image_content = requests.get(url=image, headers=header).content
            # 4. 持久化存储
            image_name = image.split('/')[-1]
            image_path = os.path.join(folder, image_name)
            with open(image_path, 'wb') as f:
                f.write(image_content)
                # 进度打印
                print(image_name + ' 下载成功！')
                print(f'{index} / {length}', end='\r')

        print(str(i) + "/ 2 page")


def data_parse(page_text):
    """ 解析出每张图片的url """

    # 分析网页后整理出正则表达式
    ex = r'<div class="thumb">.*?<img src="(.*?)" alt.*?></div>'
    images = re.findall(ex, page_text, re.S)
    images = ['https:' + x for x in images]  # 解析出来没有协议头，给增加上

    return images


if __name__ == "__main__":
    main()

--------------------------------------------------

# Output:

K7EUFEUIV3QY37P1.jpg 下载成功！
DFIAAL32X5J35JP2.jpg 下载成功！
...
NXUA4X1CMQP22UPP.jpg 下载成功！
FQILIKXCVMUIRXL8.jpg 下载成功！
1/ 2 page
95GRCYEUZANQ361J.jpg 下载成功！
2SXBFKSSK3JD3G2M.jpg 下载成功！
...
5YTNS4JH0PLZAO58.jpg 下载成功！
59CN77YAL198SM6M.jpg 下载成功！
2/ 2 page

示例网页

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>测试bs4</title>
</head>
<body>
    <div>
        <p>百里守约</p>
    </div>
    <div class="song">
        <p>李清照</p>
        <p>王安石</p>
        <p>苏轼</p>
        <p>柳宗元</p>
        <a href="https://www.song.com" title="赵匡胤" target="_self">
            <span>this is span</span>
            宋朝是最强大的王朝，不是军队的强大，而是经济很强大，国民都很有钱
        </a>
        <a href="" class="du">总为浮云能避日，长安不见使人愁</a>
        <img src="https://www.baidu.com/meinv.jpg" alt="">
    </div>
    <div class="tang">
        <ul>
            <li><a href="https://www.baidu.com" title="qing">清明时节雨纷纷，路上行人欲断魂。借问酒家何处有，牧童遥指杏花村。</a></li>
            <li><a href="https://www.163.com" title="qin">秦时明月汉时光，万里长征人未还。但使龙城飞将在，不教胡马度阴山。</a></li>
            <li><a href="https://www.126.com" alt="qi">岐王宅里寻常见，崔久堂前几度闻。正是江南好风景，落花时节又逢君。</a></li>
            <li><a href="https://www.sina.com" class="du">杜甫</a></li>
            <li><a href="https://www.dudu.com" class="du">杜牧</a></li>
            <li><b>杜小月</b></li>
            <li><i>度蜜月</i></li>
            <li><a href="https://www.haha.com" id="feng">凤凰台上凤凰游，凤去台空江自流。吴宫花草埋幽径，晋代衣冠成古丘。</a></li>
        </ul>
    </div>


</body>
</html>

1 以下爬虫示例均以此网页示例为基础 有点丑，将就一下。

bs4爬取

安装

win 下： >_ pip install bs4 >_ pip install lxml

Linux 下： >_ pip install Beautifulsoup4

导入

from bs4 import BeautifulSoup

使用

  • 创建bs对象并传入待解析对象
    1. 传入待解析对象为本地文件 
      1
2
3
4
      from bs4 import BeautifulSoup

with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')    # 创建bs对象
    2. 传入待解析对象为网络请求 
      1
2
3
4
5
6
      from bs4 import BeautifulSoup
import requests

url = "https://www.baidu.com"
page_text = requests.get(url=url).text
bs = BeautifulSoup(page_text, 'lxml')    # 创建bs对象

定位数据

方法 用 返值
tagName 返回首tagName标签 bs4.element.Tag
find('tagName') 返回首tagName标签 bs4.element.Tag
find('tagName', class_/id/attrName='value') 返回首属性为value的tagName标签 bs4.element.Tag
find_all('tagName') 返回所符合要求的标签 bs4.element.ResultSet
select(['selector' + ]'tagName') 通过CS选择器+标签名定位标签,返回多个 bs4.element.ResultSet
select_one(['selector' + ]'tagName') 通过CS选择器+标签名定位标签,返回一个 bs4.element.Tag
bs.tagName
  1. bs.tagName：返回文档中**第一次**出现tagName对应的标签 
     1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
    with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')    # 创建bs对象

    tag_a = bs.a        # 定位数据

    print(tag_a)
    print(type(tag_a))  # <class 'bs4.element.Tag'>
--------------------------------------------------
# Output:
<a href="https://www.song.com" target="_self" title="赵匡胤">
<span>this is span</span>
    宋朝是最强大的王朝，不是军队的强大，而是经济很强大，国民都很有钱
</a>
<class 'bs4.element.Tag'>
bs.find()
  1. bs.find()：
    1. find('tagName')：等同于 bs.tagName 
       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
      with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')    # 创建bs对象

    tag_div = bs.find('div')         # 定位数据

    print(tag_div)
    print(type(tag_div))  # <class 'bs4.element.Tag'>
--------------------------------------------------
# Output:
<div>
<p>百里守约</p>
</div>
<class 'bs4.element.Tag'>
    2. find('tagName', class_/is/attrName='value')：通过限定属性来定位标签 
       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
      with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')                  # 创建bs对象

    tag_a = bs.find('a', class_='du')        # 定位数据

    print(tag_a)
    print(type(tag_a))  # <class 'bs4.element.Tag'>
--------------------------------------------------
# Output:
<a class="du" href="">总为浮云能避日，长安不见使人愁</a>
<class 'bs4.element.Tag'>
    3. bs.find_all('tagName')：返回复合要求的所有标签（集合） 
       1
 2
 3
 4
 5
 6
 7
 8
 9
10
      with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')       # 创建bs对象

    tag_p = bs.find_all('p')        # 定位数据

    print(tag_p)
    print(type(tag_p))  # <class 'bs4.element.ResultSet'>
--------------------------------------------------
# Output:
[<p>百里守约</p>, <p>李清照</p>, <p>王安石</p>, <p>苏轼</p>, <p>柳宗元</p>]
bs.select()
  1. bs.select('selector' + 'tagName')：可以通过**CSS择器+标签名**定位，包括层级选择器、标签选择器等 
     1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
    with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')       # 创建bs对象

    tag_div = bs.select('#feng')        # 定位数据

    print(tag_div)
    print(type(tag_div))  # <class 'bs4.element.ResultSet'>
--------------------------------------------------
# Output:
[<a href="https://www.haha.com" id="feng">凤凰台上凤凰游，凤去台空江自流。吴宫花草埋幽径，晋代衣冠成古丘。</a>]
<class 'bs4.element.ResultSet'>

     1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
    with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')               # 创建bs对象

    tag1_a = bs.select('.tang > ul > li > a')  # 定位数据
    tag2_a = bs.select('.tang >ul a')          # 定位数据

    print(tag1_a)
    print(tag2_a)
    print(type(tag1_a))  # <class 'bs4.element.ResultSet'>

--------------------------------------------------
# Output:
[<a href="https://www.baidu.com" title="qing">清明时节雨纷纷，路上行人欲断魂。借问酒家何处有，牧童遥指杏花村。</a>, <a href="https://www.163.com" title="qin">秦时明月汉时光，万里长征人未还。但使龙城飞将在，不教胡马度阴山。</a>, <a alt="qi" href="https://www.126.com">岐王宅里寻常见，崔久堂前几度闻。正是江南好风景，落花时节又逢君。</a>, <a class="du" href="https://www.sina.com">杜甫</a>, <a class="du" href="https://www.dudu.com">杜牧</a>, <a href="https://www.haha.com" id="feng">凤凰台上凤凰游，凤去台空江自流。吴宫花草埋幽径，晋代衣冠成古丘。</a>]
[<a href="https://www.baidu.com" title="qing">清明时节雨纷纷，路上行人欲断魂。借问酒家何处有，牧童遥指杏花村。</a>, <a href="https://www.163.com" title="qin">秦时明月汉时光，万里长征人未还。但使龙城飞将在，不教胡马度阴山。</a>, <a alt="qi" href="https://www.126.com">岐王宅里寻常见，崔久堂前几度闻。正是江南好风景，落花时节又逢君。</a>, <a class="du" href="https://www.sina.com">杜甫</a>, <a class="du" href="https://www.dudu.com">杜牧</a>, <a href="https://www.haha.com" id="feng">凤凰台上凤凰游，凤去台空江自流。吴宫花草埋幽径，晋代衣冠成古丘。</a>]
<class 'bs4.element.ResultSet'>

     1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
     with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')       # 创建bs对象

    tag_div = bs.select_one('.du')    # 定位数据

    print(tag_div)
    print(type(tag_div))  # <class 'bs4.element.Tag'>

--------------------------------------------------
# Output:
<a class="du" href="">总为浮云能避日，长安不见使人愁</a>
<class 'bs4.element.Tag'>

解析数据

方法 用 返值
.text 返回标签下所有**直系和非直系标签**的所有本 str
.get_text() 返回标签下所有**直系和非直系标签**的所有本 str
.string 返回标签下所有**直系标签**的所有本 bs4.element.NavigableString
获取文本
  1. bs.tagName.text/string/get_text()：获取标签之间的*所有文本**
    1. text/get_text()：可以获取标签下**直系和非直系**的所有文本 
       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
      with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')       # 创建bs对象

    txt_li = bs.find('li').text

    print(txt_li)
    print(type(txt_li))    # <class 'str'>

--------------------------------------------------
# Output:
清明时节雨纷纷，路上行人欲断魂。借问酒家何处有，牧童遥指杏花村。
<class 'str'>

       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
      with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')       # 创建bs对象

    txt_li = bs.find('li').get_text()

    print(txt_li)
    print(type(txt_li))    # <class 'str'>

--------------------------------------------------
# Output:
清明时节雨纷纷，路上行人欲断魂。借问酒家何处有，牧童遥指杏花村。
<class 'str'>
    2. string：只能获取标签下**直系**的文本，没有返回 None 
       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
      with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')       # 创建bs对象

    txt_li = bs.find('li').string

    print(txt_li)
    print(type(txt_li))    # <class 'bs4.element.NavigableString'>

--------------------------------------------------
# Output:
清明时节雨纷纷，路上行人欲断魂。借问酒家何处有，牧童遥指杏花村。
<class 'bs4.element.NavigableString'>
获取属性
  1. bs.tagName['attrName']：获取标签中的**属性内容** 
     1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
    with open('./bs_test.html', 'r', encoding='utf-8') as f:
    bs = BeautifulSoup(f, 'lxml')       # 创建bs对象

    txt_href = bs.find('a')['href']

    print(txt_href)
    print(type(txt_href))    # <class 'str'>

--------------------------------------------------
# Output:
https://www.song.com
<class 'str'>

案例

从诗词名句网下载一整部《论语》

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
import time
import requests
import os
from bs4 import BeautifulSoup

UA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.89 Safari/537.36 Edg/84.0.522.44'
header = {'User-Agent': UA}

folder = '.\\爬虫\\论语'
if not os.path.exists(folder):
    os.mkdir(folder)


def req_catalog(url):
    """ 请求目录列表 """
    return requests.get(url=url, headers=header).text


def catalog_parse(res_text):
    """ 解析目录列表 """
    bs = BeautifulSoup(res_text, 'lxml')
    links = bs.select('.book-mulu > ul > li > a')
    catalog_list = [[x.string, x['href']] for x in links]

    return catalog_list


def download_content(catalog_list):
    """ 请求内容页 """
    url = 'https://www.shicimingju.com'
    length = len(catalog_list)

    for index, elem in enumerate(catalog_list):
        # 请求数据
        content_text = requests.get(url=url + elem[1], headers=header).text
        # 解析数据
        content = contents_parse(content_text)
        # 持久化存储
        filename = str(index + 1) + '-' + elem[0] + '.txt'
        filepath = os.path.join(folder, filename)
        with open(filepath, 'w', encoding='utf-8') as f:
            f.write(content)
            print("已下载：" + str(index + 1) + " / " + str(length), end="\r")
    return 1


def contents_parse(page_text):
    """ 解析内容 """
    bs = BeautifulSoup(page_text, 'lxml')
    contents = bs.select('.chapter_content > p')  # 取出所有p标签
    texts = [x.string for x in contents]          # 取出内容，过滤掉P标签
    content = ''
    for i in texts:
        content += str(i)
    return content


def main():
    url = "https://www.shicimingju.com/book/lunyu.html"

    catalog_list = list()
    try:
        catalog_text = req_catalog(url)
        catalog_list = catalog_parse(catalog_text)
        print("下载成功！") if download_content(catalog_list) else print("下载失败")
    except TimeoutError:
        print("TimeoutError\n")
        time.sleep(2)
        print("下载成功！") if download_content(catalog_list) else print("下载失败")
    except Exception:
        print("Exception\n")


if __name__ == '__main__':
    main()

xpath爬取

最常用、通用性最强的，最便捷高效的一种解析方式。

解析步骤

  1. 实例化一个etree对象，并且需要将被解析的页面源码数据加载到该对象中。
  2. 通过调用etree对象中的xpath方法结合着xpath表达式实现标签的定位和内容的捕获
  3. xpath定位到数据后返回的不是数据的内容，而已一个列表，里面放置了解析出来的**Element对象**

安装

>_: pip install lxml

导入

from lxml import etree

使用

  • 创建etree对象并传入待解析对象
    1. 传入待解析对象为本地文件 tree = etree.parse(filePath)
    2. 传入待解析对象为网络请求 tree = etree.HTML('page_text')

  • 定位数据：tree.xpath(xpath表达式) 在XPath中有7种节点：元素、属性、文本、文档、命名空间、处理指令、注释。 元素、属性、文本 为常用节点。 

    1
2
3
4
    <html> 为文档节点
<li>小米</li> 为元素节点
class='blank' 为属性节点
<!-- 这里是注释 --> 为注释节点

    expression description
    nodeName 选择nodeName节点的所有子节点
    / 从根节点或/前的节点开始，不跨层级匹配
    // 从//前的节点开始，跨层级匹配
    . 选择当前节点
    .. 选择当前节点的父节点
    @ 匹配元素属性
    * 匹配所有节点
    @* 匹配节点所有属性
    [] 按索引定位

    1. /：表示从根节点开始定位 > / 放在最前面的时候表示根节点，不是放在最前面的时候表示

       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
      from lxml import etree

with open('./test.html', 'r', encoding='utf-8') as f:
    f_content = f.read()
    tree = etree.HTML(f_content)
    r = tree.xpath('/html/body/div/p')
    print(r)
    print(type(r))

--------------------------------------------------
xpath 在匹配的时候是贪婪的，示例中有两个 div 下都有 p，所以匹配到了5个
# Output:
[<Element p at 0x252e2de8780>,
 <Element p at 0x252e2de87c0>,
 <Element p at 0x252e2de8800>,
 <Element p at 0x252e2de8840>,
 <Element p at 0x252e2de8880>]
<class 'list'>
      2. //：表示匹配多级

      /a/b//c，就表示匹配 a 标签下的 b 标签下所有c标签

       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
      from lxml import etree

with open('./test.html', 'r', encoding='utf-8') as f:
    f_content = f.read()
    tree = etree.HTML(f_content)
    r = tree.xpath('/html//a')        # 等价于 r = tree.xpath('//a')
    print(r)
    print(type(r))

--------------------------------------------------
html节点下总共有8个a标签，所以匹配到8个element对象
# Output:
[<Element a at 0x1e5f55e9680>,
 <Element a at 0x1e5f55e96c0>,
 <Element a at 0x1e5f55e9700>,
 <Element a at 0x1e5f55e9740>,
 <Element a at 0x1e5f55e9780>,
 <Element a at 0x1e5f55e9800>,
 <Element a at 0x1e5f55e9840>,
 <Element a at 0x1e5f55e9880>]
<class 'list'>
      3. @：表示通过属性定位

      tag[@attrName="attrValue"] @后面加上属性名，比如class、id、href、src等等

       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
      from lxml import etree

with open('./test.html', 'r', encoding='utf-8') as f:
    f_content = f.read()
    tree = etree.HTML(f_content)
    r = tree.xpath('/html//div[@class="song"]')
    print(r)
    print(type(r))

--------------------------------------------------
html节点下总共有8个a标签，所以匹配到8个element对象
# Output:
[<Element div at 0x24d64839640>]
<class 'list'>
      4. []：表示通过索引定位

      tag[index] 这里是索引是**从1开始的**

       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
      from lxml import etree

with open('./test.html', 'r', encoding='utf-8') as f:
    f_content = f.read()
    tree = etree.HTML(f_content)

    print(tree.xpath('/html//div[@class="song"]/p[1]'))
    print(tree.xpath('/html//div[@class="song"]/p[1]/text()'))
    print(tree.xpath('/html//div[@class="song"]/p[2]'))
    print(tree.xpath('/html//div[@class="song"]/p[3]'))

--------------------------------------------------
这里的下标是从1开始的
# Output:
[<Element p at 0x1df3d4395c0>]
['李清照']
[<Element p at 0x1df3d439580>]
[<Element p at 0x1df3d439600>]
<class 'list'>
      5. /text()：返回标签之间的文本，取文本

      tag/text()：获取tag下**直系**的文本 tag//text()：获取tag下**直系和非直系**的文本

       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
      from lxml import etree

with open('./test.html', 'r', encoding='utf-8') as f:
    f_content = f.read()
    tree = etree.HTML(f_content)
    r1 = tree.xpath('/html//div[@class="song"]/p[3]')
    r2 = tree.xpath('/html//div[@class="song"]/p[3]/text()')
    r3 = tree.xpath('/html//div[@class="song"]/p[3]/text()')[0]
    print(r1)
    print(r2)
    print(r3)

--------------------------------------------------

# Output:
[<Element p at 0x1d4e4c29540>]
['苏轼']
苏轼
<class 'list'>
      5. /@attrName：返回标签的attrName属性的值

      tag/@attrName：获取tag标签中的attrName属性的值

       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
      from lxml import etree

with open('./test.html', 'r', encoding='utf-8') as f:
    f_content = f.read()
    tree = etree.HTML(f_content)
    r1 = tree.xpath('//div[@class="song"]/a/@href')
    print(r1)

    r2 = tree.xpath('//div[@class="song"]/img/@src')
    print(r2)

--------------------------------------------------

# Output:
['https://www.song.com', '']
['https://www.baidu.com/meinv.jpg']
<class 'list'>
      5. /@*：返回标签的所有属性的值

      tag/@*：获取tag标签中的所有属性的值

       1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
      from lxml import etree

with open('./test.html', 'r', encoding='utf-8') as f:
    f_content = f.read()
    tree = etree.HTML(f_content)
    r1 = tree.xpath('//div[@class="song"]/a[@target="_self"]/@*')
    print(r1)

--------------------------------------------------

# Output:
['https://www.song.com', '赵匡胤', '_self']
<class 'list'>

案例

从彼岸图网下载4K图保存至本地

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
import os
from lxml import etree
import requests

UA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.89 Safari/537.36 Edg/84.0.522.44'
header = {'User-Agent': UA}

path = './爬虫/4k'
if not os.path.exists(path):
    os.mkdir(path)


def get_url():
    """ 获取所有图片地址 """
    url = 'http://pic.netbian.com/4kmeinv/'
    index_text = requests.get(url=url, headers=header).text

    tree = etree.HTML(index_text)
    a_list = tree.xpath('//div[@id="main"]/div[3]/ul/li/a')
    # response.encoding = 'utf-8'   # 处理中文乱码方式1，不一定有效

    img_list = list()
    for a in a_list:
        src: str = 'http://pic.netbian.com' + a.xpath('./@href')[0]
        title: str = a.xpath('./b/text()')[0] + '.jpg'
        title = title.encode('iso-8859-1').decode('gbk')  # 处理中文乱码方式2
        img_list.append((title, src))

    return img_list


def download_img(img_info):
    """ 下载图片 """

    img_content = requests.get(url=img_info[1], headers=header).content
    filepath = os.path.join(path, img_info[0])
    with open(filepath, 'wb') as f:
        f.write(img_content)


def main():
    img_list = get_url()
    for img_info in img_list:
        download_img(img_info)


if __name__ == '__main__':
    main()