153 lines
7.0 KiB
Python
153 lines
7.0 KiB
Python
import time
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from bs4 import BeautifulSoup
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import logging
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import json
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import os
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from tqdm import tqdm
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import re
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from .DocTokenizer import DocTokenizer
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logging.basicConfig(level=logging.INFO)
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class Html2Text():
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'''从html中提取text文本内容。
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'''
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def __init__(self):
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pass
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def html2text(self,
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target_content_tag={},
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target_tag_list=[],
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html_dir=None,
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text_dir=None,
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mode="w",
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is_get_all_text=False
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):
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'''
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从html中提取text文本内容，需要指定提取html中的tag标签。输入为地址，html文件保存在jsonl文件中，输出也需要指定地址。
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:param target_content_tag: html中正文content所在tag，字典格式限制长度为1，key为选中便签类型name/class/id，vaule为标签取值如div/title/article等
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:param target_tag_list: 指定提取html对应的tag文本，列表，每个元素都与target_content_tag格式相同
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:param is_get_all_text: True则将html页面所有text内容保存到all_text字典中；False不保存all_text
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:param html_dir: html数据地址，注意需要时jsonl格式，一行为一个json字典，有text/url/host_url三个字段
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:param text_dir: 将提取的text内容保存的地址，同样是jsonl格式。
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:return: None
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'''
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assert isinstance(target_content_tag,dict), "target_content_tag请输入字典格式！"
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assert len(target_content_tag.keys()) <= 1,"target_content_tag属性字典只能指定唯一元素！"
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for _ in target_tag_list:
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assert isinstance(_, dict), "target_tag_list列表元素需要字典格式！"
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assert len(_.keys()) <= 1, "target_tag_list列表中的属性字典只能指定唯一元素！"
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# 创建保存目录
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os.makedirs(os.path.dirname(text_dir), exist_ok=True)
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# 读取文件
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logging.info("读取文件中……")
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html_dict_list = self.read_html_jsonl(html_dir)
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url_nums = len(html_dict_list)
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logging.info("共{url_nums}个html网址".format(url_nums=url_nums))
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# 循环处理每行html数据：html提取content正文、指定tag内容
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text_dict_list = []
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for html_dict in tqdm(html_dict_list, mininterval=1):
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# 是否获取全部text内容
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text_dict = self.get_text_dict(
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html_dict=html_dict,
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target_content_tag=target_content_tag,
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target_tag_list=target_tag_list,
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is_get_all_text=is_get_all_text
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)
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text_dict_list.append(text_dict)
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logging.info("保存html提取的text内容……")
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self.save_text_jsonl(json_list=text_dict_list,
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file_path=text_dir,
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mode=mode)
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logging.info("保存成功！地址：%s" % text_dir)
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def get_text_dict(self,
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html_dict={},
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target_content_tag={},
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target_tag_list=[],
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is_get_all_text=True
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):
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'''{"name":"div"}
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提取html网页字符中的纯文本内容，采用BeautifulSoup.get_text()获取全部text文本，target_tag_list指定要提取文本的标签。
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:param html_dict: 网页返回的全部文本内容response.text和url
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:param target_content_tag: html中正文content所在tag，字典格式限制长度为1，key为选中便签类型name/class/id，vaule为标签取值如div/title/article等
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:param target_tag_list: 指定提取html对应的tag文本，列表，每个元素都与target_content_tag格式相同
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:return: text_content:{} 提取的text文本内容
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'''
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# 格式定义
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assert isinstance(target_content_tag,dict), "target_content_tag请输入字典格式！"
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assert len(target_content_tag.keys()) <= 1,"target_content_tag属性字典只能指定唯一元素！"
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for _ in target_tag_list:
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assert isinstance(_, dict), "target_tag_list列表元素需要字典格式！"
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assert len(_.keys()) <= 1, "target_tag_list列表中的属性字典只能指定唯一元素！"
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# 提取html的内容
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html_content = html_dict['text']
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url = html_dict['url']
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host_url = html_dict['host_url']
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# 创建BeautifulSoup对象
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soup = BeautifulSoup(html_content, 'html.parser')
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# 处理pre引用代码块，添```引用
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pre_tags = soup.find_all('code')
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for pre_tag in pre_tags:
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pre_tag.string = '\n```code\n' + pre_tag.get_text() + '\n```\n'
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# 提取HTML中的文本内容
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doc_tokenizer = DocTokenizer()
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text_dict = {}
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text_dict['url'] = url
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text_dict['host_url'] = host_url
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# 提取网页的title，不存在则置空
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try:
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text_dict['title'] = soup.title.text
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except:
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text_dict['title'] = None
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# 是否提取全部text，不区分标签
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if is_get_all_text:
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all_text = soup.get_text(separator="", strip=False)
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text_dict['all_text'] = doc_tokenizer.doc_process(all_text)
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# 提取正文tag，可以按照标签的class提取，或按照tag名提取
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if target_content_tag:
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text_dict["content"] = self.soup_find_all_text(soup=soup,doc_tokenizer=doc_tokenizer,attrs=target_content_tag)
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# 提取html中tag内容，每个tag独立作为字段保存
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for target_tag in target_tag_list:
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if target_tag:
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# 提取目标tag名
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tag_ = list(target_tag.values())[0]
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# 提取目标tag内容
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text_dict[tag_] = self.soup_find_all_text(soup,doc_tokenizer,attrs=target_tag)
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return text_dict
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def soup_find_all_text(self,soup,doc_tokenizer,attrs):
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assert isinstance(attrs,dict), "attrs请输入字典格式！"
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assert len(attrs.keys()) == 1,"attrs属性字典只能指定唯一元素！"
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if list(attrs.keys())[0]=="name":
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_tags = soup.find_all(name=attrs["name"])
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else:
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_tags = soup.find_all(attrs=attrs)
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tags_text = ""
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for _tag in _tags:
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tag_text = _tag.get_text(separator="", strip=False)
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tag_text = doc_tokenizer.doc_process(tag_text)
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tags_text += tag_text.strip() + "\n\n"
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return tags_text
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def read_html_jsonl(self, file_name=None):
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'''
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读取html的josnl文件
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'''
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html_dict_list = []
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with open(file_name, "r", encoding="utf-8") as f:
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for k, line in enumerate(f):
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line = json.loads(line)
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html_dict_list.append(line)
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return html_dict_list
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def save_text_jsonl(self, json_list=[], file_path=None, mode="w"):
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'''
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将json_list保存成jsonl格式文件
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'''
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with open(file_path, mode, encoding="utf-8") as f:
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for line in json_list:
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f.write(json.dumps(line, ensure_ascii=False) + "\n")
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