Python中爬虫后建立知识图谱的示例代码

以下是基于 Python 实现的爬虫后建立知识图谱的示例代码：

import requests
from bs4 import BeautifulSoup
from py2neo import Graph, Node, Relationship

# 爬取知乎一些关于 Python 的问题的页面
response = requests.get('https://www.zhihu.com/search?type=content&q=python')
soup = BeautifulSoup(response.content, 'html.parser')
question_tags = soup.find_all('div', class_='ContentItem-head')

# 获取问题标题和问题链接
questions = []
for tag in question_tags:
    question = {}
    a_tag = tag.find('a')
    question['title'] = a_tag.get_text()
    question['link'] = 'https://www.zhihu.com' + a_tag['href']
    questions.append(question)

# 建立知识图谱
graph = Graph('http://localhost:7474/db/data/', username='neo4j', password='password')

for question in questions:
    # 创建节点
    question_node = Node('Question', title=question['title'], link=question['link'])
    graph.create(question_node)
    
    # 爬取问题页面并获取问题描述和回答
    response = requests.get(question['link'])
    soup = BeautifulSoup(response.content, 'html.parser')
    description_tag = soup.find('div', class_='QuestionDetail-main')
    if description_tag:
        description = description_tag.get_text().strip()
        if description:
            description_node = Node('Description', content=description)
            graph.create(description_node)
            graph.create(Relationship(question_node, 'HAS_DESCRIPTION', description_node))
    
    answer_tags = soup.find_all('div', class_='ContentItem AnswerItem')
    for tag in answer_tags:
        answer_node = Node('Answer', content=tag.find('div', class_='RichContent-inner').get_text().strip())
        graph.create(answer_node)
        graph.create(Relationship(question_node, 'HAS_ANSWER', answer_node))

注：此示例代码基于知乎问题爬取，需要安装 py2neo 库和 BeautifulSoup 库。另外，需要安装并运行 Neo4j 数据库，并且在代码中修改数据库的连接信息。