首页 > Python资料 博客日记
Python商业数据挖掘实战——爬取网页并将其转为Markdown
2024-02-27 18:00:07Python资料围观248次
前言
前些天发现了一个巨牛的人工智能学习网站,通俗易懂,风趣幽默,忍不住分享一下给大家:https://www.captainbed.cn/z
ChatGPT体验地址
前言
在信息爆炸的时代,互联网上的海量文字信息如同无尽的沙滩。然而,其中真正有价值的信息往往埋在各种网页中,需要经过筛选和整理才能被有效利用。幸运的是,Python这个强大的编程语言可以帮助我们完成这项任务。
本文将介绍如何使用Python将网页文字转换为Markdown格式,这将使得我们能够更加方便地阅读和处理网页内容。无论是将文章保存为本地文件还是转化为其他格式,Markdown都能够提供清晰简洁的排版和格式,让我们更加专注于内容本身。
正则表达式
我们将页面进行Maekdown的转换为了保证准确度,我们可以使用正则表达式去修改,如下
import re
__all__ = ['Tomd', 'convert']
MARKDOWN = {
'h1': ('\n# ', '\n'),
'h2': ('\n## ', '\n'),
'h3': ('\n### ', '\n'),
'h4': ('\n#### ', '\n'),
'h5': ('\n##### ', '\n'),
'h6': ('\n###### ', '\n'),
'code': ('`', '`'),
'ul': ('', ''),
'ol': ('', ''),
'li': ('- ', ''),
'blockquote': ('\n> ', '\n'),
'em': ('**', '**'),
'strong': ('**', '**'),
'block_code': ('\n```\n', '\n```\n'),
'span': ('', ''),
'p': ('\n', '\n'),
'p_with_out_class': ('\n', '\n'),
'inline_p': ('', ''),
'inline_p_with_out_class': ('', ''),
'b': ('**', '**'),
'i': ('*', '*'),
'del': ('~~', '~~'),
'hr': ('\n---', '\n\n'),
'thead': ('\n', '|------\n'),
'tbody': ('\n', '\n'),
'td': ('|', ''),
'th': ('|', ''),
'tr': ('', '\n')
}
BlOCK_ELEMENTS = {
'h1': '<h1.*?>(.*?)</h1>',
'h2': '<h2.*?>(.*?)</h2>',
'h3': '<h3.*?>(.*?)</h3>',
'h4': '<h4.*?>(.*?)</h4>',
'h5': '<h5.*?>(.*?)</h5>',
'h6': '<h6.*?>(.*?)</h6>',
'hr': '<hr/>',
'blockquote': '<blockquote.*?>(.*?)</blockquote>',
'ul': '<ul.*?>(.*?)</ul>',
'ol': '<ol.*?>(.*?)</ol>',
'block_code': '<pre.*?><code.*?>(.*?)</code></pre>',
'p': '<p\s.*?>(.*?)</p>',
'p_with_out_class': '<p>(.*?)</p>',
'thead': '<thead.*?>(.*?)</thead>',
'tr': '<tr>(.*?)</tr>'
}
INLINE_ELEMENTS = {
'td': '<td>(.*?)</td>',
'tr': '<tr>(.*?)</tr>',
'th': '<th>(.*?)</th>',
'b': '<b>(.*?)</b>',
'i': '<i>(.*?)</i>',
'del': '<del>(.*?)</del>',
'inline_p': '<p\s.*?>(.*?)</p>',
'inline_p_with_out_class': '<p>(.*?)</p>',
'code': '<code.*?>(.*?)</code>',
'span': '<span.*?>(.*?)</span>',
'ul': '<ul.*?>(.*?)</ul>',
'ol': '<ol.*?>(.*?)</ol>',
'li': '<li.*?>(.*?)</li>',
'img': '<img.*?src="(.*?)".*?>(.*?)</img>',
'a': '<a.*?href="(.*?)".*?>(.*?)</a>',
'em': '<em.*?>(.*?)</em>',
'strong': '<strong.*?>(.*?)</strong>'
}
DELETE_ELEMENTS = ['<span.*?>', '</span>', '<div.*?>', '</div>']
class Element:
def __init__(self, start_pos, end_pos, content, tag, is_block=False):
self.start_pos = start_pos
self.end_pos = end_pos
self.content = content
self._elements = []
self.is_block = is_block
self.tag = tag
self._result = None
if self.is_block:
self.parse_inline()
def __str__(self):
wrapper = MARKDOWN.get(self.tag)
self._result = '{}{}{}'.format(wrapper[0], self.content, wrapper[1])
return self._result
def parse_inline(self):
for tag, pattern in INLINE_ELEMENTS.items():
if tag == 'a':
self.content = re.sub(pattern, '[\g<2>](\g<1>)', self.content)
elif tag == 'img':
self.content = re.sub(pattern, '![\g<2>](\g<1>)', self.content)
elif self.tag == 'ul' and tag == 'li':
self.content = re.sub(pattern, '- \g<1>', self.content)
elif self.tag == 'ol' and tag == 'li':
self.content = re.sub(pattern, '1. \g<1>', self.content)
elif self.tag == 'thead' and tag == 'tr':
self.content = re.sub(pattern, '\g<1>\n', self.content.replace('\n', ''))
elif self.tag == 'tr' and tag == 'th':
self.content = re.sub(pattern, '|\g<1>', self.content.replace('\n', ''))
elif self.tag == 'tr' and tag == 'td':
self.content = re.sub(pattern, '|\g<1>', self.content.replace('\n', ''))
else:
wrapper = MARKDOWN.get(tag)
self.content = re.sub(pattern, '{}\g<1>{}'.format(wrapper[0], wrapper[1]), self.content)
class Tomd:
def __init__(self, html='', options=None):
self.html = html
self.options = options
self._markdown = ''
def convert(self, html, options=None):
elements = []
for tag, pattern in BlOCK_ELEMENTS.items():
for m in re.finditer(pattern, html, re.I | re.S | re.M):
element = Element(start_pos=m.start(),
end_pos=m.end(),
content=''.join(m.groups()),
tag=tag,
is_block=True)
can_append = True
for e in elements:
if e.start_pos < m.start() and e.end_pos > m.end():
can_append = False
elif e.start_pos > m.start() and e.end_pos < m.end():
elements.remove(e)
if can_append:
elements.append(element)
elements.sort(key=lambda element: element.start_pos)
self._markdown = ''.join([str(e) for e in elements])
for index, element in enumerate(DELETE_ELEMENTS):
self._markdown = re.sub(element, '', self._markdown)
return self._markdown
@property
def markdown(self):
self.convert(self.html, self.options)
return self._markdown
_inst = Tomd()
convert = _inst.convert
这段代码是一个用于将HTML转换为Markdown的工具类。它使用了正则表达式来解析HTML标签,并根据预定义的转换规则将其转换为对应的Markdown格式。
代码中定义了一个Element
类,用于表示HTML中的各个元素。Element
类包含了标签的起始位置、结束位置、内容、标签类型等信息。它还提供了一个parse_inline
方法,用于解析内联元素,并将其转换为Markdown格式。
Tomd
类是主要的转换类,它接受HTML字符串并提供了convert
方法来执行转换操作。convert
方法遍历预定义的HTML标签模式,并使用正则表达式匹配HTML字符串中对应的部分。然后创建相应的Element
对象并进行转换操作。最后,将转换后的Markdown字符串返回。
在模块顶部,MARKDOWN
字典定义了各个HTML标签对应的Markdown格式。BlOCK_ELEMENTS
和INLINE_ELEMENTS
字典定义了正则表达式模式,用于匹配HTML字符串中的块级元素和内联元素。DELETE_ELEMENTS
列表定义了需要删除的HTML元素。
那么既然有了转markdown的工具,我们就可以对网页进行转换
进行转换
首先,
result_file
函数用于创建一个保存结果文件的路径。它接受文件夹的用户名、文件名和文件夹名作为参数,并在指定的文件夹路径下创建一个新的文件,并返回该文件的路径。
get_headers
函数用于从一个文本文件中读取Cookie,并将它们保存为字典形式。它接受包含Cookie的文本文件路径作为参数。
delete_ele
函数用于删除BeautifulSoup
对象中指定的标签。它接受一个BeautifulSoup对象和待删除的标签列表作为参数,并通过使用该对象的select方法来选择要删除的标签,然后使用decompose
方法进行删除。
delete_ele_attr
函数用于删除BeautifulSoup对象中指定标签的指定属性。它接受一个BeautifulSoup对象和待删除的属性列表作为参数,并使用find_all
方法来选取所有标签,然后使用Python的del语句删除指定的属性。
delete_blank_ele
函数用于删除BeautifulSoup对象中的空白标签。它接受一个BeautifulSoup对象和一个例外列表,对于不在例外列表中且内容为空的标签,使用decompose方法进行删除。
TaskQueue
类是一个简单的任务队列,用于存储已访问的和未访问的URL。它提供了一系列方法来操作这些列表。
def result_file(folder_username, file_name, folder_name):
folder = os.path.join(os.path.dirname(os.path.realpath(__file__)), "..", folder_name, folder_username)
if not os.path.exists(folder):
try:
os.makedirs(folder)
except Exception:
pass
path = os.path.join(folder, file_name)
file = open(path,"w")
file.close()
else:
path = os.path.join(folder, file_name)
return path
def get_headers(cookie_path:str):
cookies = {}
with open(cookie_path, "r", encoding="utf-8") as f:
cookie_list = f.readlines()
for line in cookie_list:
cookie = line.split(":")
cookies[cookie[0]] = str(cookie[1]).strip()
return cookies
def delete_ele(soup:BeautifulSoup, tags:list):
for ele in tags:
for useless_tag in soup.select(ele):
useless_tag.decompose()
def delete_ele_attr(soup:BeautifulSoup, attrs:list):
for attr in attrs:
for useless_attr in soup.find_all():
del useless_attr[attr]
def delete_blank_ele(soup:BeautifulSoup, eles_except:list):
for useless_attr in soup.find_all():
try:
if useless_attr.name not in eles_except and useless_attr.text == "":
useless_attr.decompose()
except Exception:
pass
class TaskQueue(object):
def __init__(self):
self.VisitedList = []
self.UnVisitedList = []
def getVisitedList(self):
return self.VisitedList
def getUnVisitedList(self):
return self.UnVisitedList
def InsertVisitedList(self, url):
if url not in self.VisitedList:
self.VisitedList.append(url)
def InsertUnVisitedList(self, url):
if url not in self.UnVisitedList:
self.UnVisitedList.append(url)
def RemoveVisitedList(self, url):
self.VisitedList.remove(url)
def PopUnVisitedList(self,index=0):
url = []
if index and self.UnVisitedList:
url = self.UnVisitedList[index]
del self.UnVisitedList[:index]
elif self.UnVisitedList:
url = self.UnVisitedList.pop()
return url
def getUnVisitedListLength(self):
return len(self.UnVisitedList)
class CSDN(object):
def __init__(self, username, folder_name, cookie_path):
# self.headers = {
# "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36"
# }
self.headers = get_headers(cookie_path)
self.s = requests.Session()
self.username = username
self.TaskQueue = TaskQueue()
self.folder_name = folder_name
self.url_num = 1
def start(self):
num = 0
articles = [None]
while len(articles) > 0:
num += 1
url = u'https://blog.csdn.net/' + self.username + '/article/list/' + str(num)
response = self.s.get(url=url, headers=self.headers)
html = response.text
soup = BeautifulSoup(html, "html.parser")
articles = soup.find_all('div', attrs={"class":"article-item-box csdn-tracking-statistics"})
for article in articles:
article_title = article.a.text.strip().replace(' ',':')
article_href = article.a['href']
with ensure_memory(sys.getsizeof(self.TaskQueue.UnVisitedList)):
self.TaskQueue.InsertUnVisitedList([article_title, article_href])
def get_md(self, url):
response = self.s.get(url=url, headers=self.headers)
html = response.text
soup = BeautifulSoup(html, 'lxml')
content = soup.select_one("#content_views")
# 删除注释
for useless_tag in content(text=lambda text: isinstance(text, Comment)):
useless_tag.extract()
# 删除无用标签
tags = ["svg", "ul", ".hljs-button.signin"]
delete_ele(content, tags)
# 删除标签属性
attrs = ["class", "name", "id", "onclick", "style", "data-token", "rel"]
delete_ele_attr(content,attrs)
# 删除空白标签
eles_except = ["img", "br", "hr"]
delete_blank_ele(content, eles_except)
# 转换为markdown
md = Tomd(str(content)).markdown
return md
def write_readme(self):
print("+"*100)
print("[++] 开始爬取 {} 的博文 ......".format(self.username))
print("+"*100)
reademe_path = result_file(self.username,file_name="README.md",folder_name=self.folder_name)
with open(reademe_path,'w', encoding='utf-8') as reademe_file:
readme_head = "# " + self.username + " 的博文\n"
reademe_file.write(readme_head)
for [article_title,article_href] in self.TaskQueue.UnVisitedList[::-1]:
text = str(self.url_num) + '. [' + article_title + ']('+ article_href +')\n'
reademe_file.write(text)
self.url_num += 1
self.url_num = 1
def get_all_articles(self):
try:
while True:
[article_title,article_href] = self.TaskQueue.PopUnVisitedList()
try:
file_name = re.sub(r'[\/::*?"<>|]','-', article_title) + ".md"
artical_path = result_file(folder_username=self.username, file_name=file_name, folder_name=self.folder_name)
md_head = "# " + article_title + "\n"
md = md_head + self.get_md(article_href)
print("[++++] 正在处理URL:{}".format(article_href))
with open(artical_path, "w", encoding="utf-8") as artical_file:
artical_file.write(md)
except Exception:
print("[----] 处理URL异常:{}".format(article_href))
self.url_num += 1
except Exception:
pass
def muti_spider(self, thread_num):
while self.TaskQueue.getUnVisitedListLength() > 0:
thread_list = []
for i in range(thread_num):
th = threading.Thread(target=self.get_all_articles)
thread_list.append(th)
for th in thread_list:
th.start()
lock = threading.Lock()
total_mem= 1024 * 1024 * 500 #500MB spare memory
@contextlib.contextmanager
def ensure_memory(size):
global total_mem
while 1:
with lock:
if total_mem > size:
total_mem-= size
break
time.sleep(5)
yield
with lock:
total_mem += size
def spider_user(username: str, cookie_path:str, thread_num: int = 10, folder_name: str = "articles"):
if not os.path.exists(folder_name):
os.makedirs(folder_name)
csdn = CSDN(username, folder_name, cookie_path)
csdn.start()
th1 = threading.Thread(target=csdn.write_readme)
th1.start()
th2 = threading.Thread(target=csdn.muti_spider, args=(thread_num,))
th2.start()
def spider(usernames: list, cookie_path:str, thread_num: int = 10, folder_name: str = "articles"):
for username in usernames:
try:
user_thread = threading.Thread(target=spider_user,args=(username, cookie_path, thread_num, folder_name))
user_thread.start()
print("[++] 开启爬取 {} 博文进程成功 ......".format(username))
except Exception:
print("[--] 开启爬取 {} 博文进程出现异常 ......".format(username))
我们可以自定义一个测试类运行一下,在本地文件位置会生成一个文件夹,并将markdown文件输出出来
需要完整源码的小伙伴可以加文末底部微信私信获取哦,公众号内有联系方式
送书活动
- 🎁本次送书1~3本【取决于阅读量,阅读量越多,送的越多】👈
- ⌛️活动时间:截止到2023-12月27号
- ✳️参与方式:关注博主+三连(点赞、收藏、评论)
标签:
相关文章
最新发布
- 【Python】selenium安装+Microsoft Edge驱动器下载配置流程
- Python 中自动打开网页并点击[自动化脚本],Selenium
- Anaconda基础使用
- 【Python】成功解决 TypeError: ‘<‘ not supported between instances of ‘str’ and ‘int’
- manim边学边做--三维的点和线
- CPython是最常用的Python解释器之一,也是Python官方实现。它是用C语言编写的,旨在提供一个高效且易于使用的Python解释器。
- Anaconda安装配置Jupyter(2024最新版)
- Python中读取Excel最快的几种方法!
- Python某城市美食商家爬虫数据可视化分析和推荐查询系统毕业设计论文开题报告
- 如何使用 Python 批量检测和转换 JSONL 文件编码为 UTF-8
点击排行
- 版本匹配指南:Numpy版本和Python版本的对应关系
- 版本匹配指南:PyTorch版本、torchvision 版本和Python版本的对应关系
- Python 可视化 web 神器:streamlit、Gradio、dash、nicegui;低代码 Python Web 框架:PyWebIO
- 相关性分析——Pearson相关系数+热力图(附data和Python完整代码)
- Python与PyTorch的版本对应
- Anaconda版本和Python版本对应关系(持续更新...)
- Python pyinstaller打包exe最完整教程
- Could not build wheels for llama-cpp-python, which is required to install pyproject.toml-based proj