Python【Crawler】2-聚焦爬虫
文章目录
-
- 正则表达式爬取
- 示例网页
- bs4爬取
-
- 安装
- 导入
- 使用
-
- 定位数据
-
- bs.tagName
- bs.find()
- bs.select()
- 解析数据
-
- 获取文本
- 获取属性
- 案例
- xpath爬取
-
- 解析步骤
- 安装
- 导入
- 使用
- 案例
聚焦爬虫：爬取页面中指定的页面内容
-
编码流程
- 指定url
- 发起请求
- 获取响应数据
- 数据解析
- 持久化存储
-
数据解析分类
- 正则表达式
- bs4
- 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
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'.*?)
'
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
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>测试bs4title>
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 spanspan>
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>
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
- 传入待解析对象为本地文件
from bs4 import BeautifulSoup with open('./bs_test.html', 'r', encoding='utf-8') as f: bs = BeautifulSoup(f, 'lxml') # 创建bs对象 - 传入待解析对象为网络请求
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
- 传入待解析对象为本地文件
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
bs.tagName：返回文档中第一次出现tagName对应的标签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)) #-------------------------------------------------- # 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()
bs.find()：find('tagName')：等同于 bs.tagNamewith 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)) #-------------------------------------------------- # Output: <div> <p>百里守约</p> </div> <class 'bs4.element.Tag'> find('tagName', class_/is/attrName='value')：通过限定属性来定位标签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)) #-------------------------------------------------- # Output: <a class="du" href="">总为浮云能避日，长安不见使人愁</a> <class 'bs4.element.Tag'> bs.find_all('tagName')：返回复合要求的所有标签（集合）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)) #-------------------------------------------------- # 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()
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)) #-------------------------------------------------- # 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'> 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)) #-------------------------------------------------- # 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'> 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)) #-------------------------------------------------- # 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
bs.tagName.text/string/get_text()：获取标签之间的*所有文本**text/get_text()：可以获取标签下直系和非直系的所有文本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)) #-------------------------------------------------- # 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'> 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)) #-------------------------------------------------- # 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'> string：只能获取标签下直系的文本，没有返回 Nonewith 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)) #-------------------------------------------------- # 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
bs.tagName['attrName']：获取标签中的属性内容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)) #-------------------------------------------------- # Output: https://www.song.com <class 'str'>
案例
从诗词名句网下载一整部《论语》
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
- 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。
- 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
- 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
- 传入待解析对象为本地文件
tree = etree.parse(filePath) - 传入待解析对象为网络请求
tree = etree.HTML('page_text')
- 传入待解析对象为本地文件
-
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。<html> 为文档节点 <li>小米li> 为元素节点 class='blank' 为属性节点 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 -
/：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
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'> -
//：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
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'> -
@：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'> -
[]：表示通过索引定位tag[index]
这里是索引是从1开始的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'> -
/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'> -
/@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'> -
/@*：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
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()