基于医疗知识图谱的项目构建学习总结（一）—项目构建环境搭建及爬取数据部分
由于工作需要，这里学习了中科院软件所刘焕勇老师在github上的开源项目，基于知识图谱的医药领域问答项目QABasedOnMedicaKnowledgeGraph。
原项目地址：https://github.com/liuhuanyong/QASystemOnMedicalKG
自己动手实现了环境的搭建，目前实践到爬虫部分，在此记录，欢迎大家提出意见。
首先是安装mongodb
参考博客mongodb安装及创建用户
按照文中的说明下载和配置mongodb，并启动服务，打开网址，出现如下语句说明启动成功：
It looks like you are trying to access MongoDB over HTTP on the native driver port.
为了便于验证数据库是否建立成功，这里给出了几个常用的数据库语法：
show dbs 查看已有的数据库
use db_name 如果该数据库存在则进入，若不存在则创建名称为db_name的数据库
db.dropDatabase() 删除该数据库
db.jc.find() 查看数据库中jc表中的数据
然后是爬取数据部分
在对症状的解析函数中，源代码对有的网页解析得到的结果是人名，因此我对其进行了修改，详见代码。运行之后就在数据库中建立该数据库，并存入了爬取的数据。
# -*- coding: utf-8 -*-
import urllib.request
import urllib.parse
from lxml import etree
import pymongo
# 创建数据库连接，开启Mongodb服务之后，不存在该数据库的话会自动创建该数据库
conn = pymongo.MongoClient()
db = conn['medical']
col = db['data']
# 爬取数据并解析
def get_html(url):
headers = {'User-Agent':'Mozilla/5.0(Window Nt 10.0; WOW64) AppleWebKit/537.36 (KHTML, LIKE Gecko)'}
req = urllib.request.Request(url=url, headers=headers)
res = urllib.request.urlopen(req)
html = res.read().decode('gbk')
return html
def spider_main():
for page in range(1, 11000):
try:
basic_url = 'http://jib.xywy.com/il_sii/gaishu/%s.htm'% page
cause_url = 'http://jib.xywy.com/il_sii/cause/%s.htm' % page # 病因
prevent_url = 'http://jib.xywy.com/il_sii/prevent/%s.htm' % page # 预防
symptom_url = 'http://jib.xywy.com/il_sii/symptom/%s.htm' % page # 症状
inspect_url = 'http://jib.xywy.com/il_sii/inspect/%s.htm' % page # 检查方法
treat_url = 'http://jib.xywy.com/il_sii/treat/%s.htm' % page # 治疗
food_url = 'http://jib.xywy.com/il_sii/food/%s.htm' % page # 饮食保健
drug_url = 'http://jib.xywy.com/il_sii/drug/%s.htm' % page # 好评药品
data = {}
data['url'] = basic_url
data['basic_info'] = basicinfo_spider(basic_url)
data['cause_info'] = common_spider(cause_url)
data['prevent_info'] = common_spider(prevent_url)
data['symptom'] = symptom_spider(symptom_url)
data['inspect_info'] = inspect_spider(inspect_url)
data['treat_info'] = treat_sipder(treat_url)
data['food_info'] = food_spider(food_url)
data['drug_info'] = drug_spider(drug_url)
print(page, basic_url)
col.insert(data)
except:
print('error')
return
'''基本信息解析'''
def basicinfo_spider(url):
html = get_html(url)
selector = etree.HTML(html)
title = selector.xpath('//title/text()')[0]
category = selector.xpath('//div[@class="wrap mt10 nav-bar"]/a/text()')
desc = selector.xpath('//div[@class="jib-articl-con jib-lh-articl"]/p/text()')
ps = selector.xpath('//div[@class="mt20 articl-know"]/p')
infobox = []
for p in ps:
info = p.xpath('string(.)').replace('\r','').replace('\n','').replace('\xa0', '').replace(' ', '').replace('\t','')
infobox.append(info)
basic_data = {}
basic_data['category'] = category
basic_data['name'] = title.split('的简介')[0]
basic_data['desc'] = desc
basic_data['attributes'] = infobox
return basic_data
# 对网页分别进行解析
def treat_sipder(url):
html = get_html(url)
selector = etree.HTML(html)
ps = selector.xpath('//div[starts-with(@class, "mt20 articl-know")]/p')
infobox = []
for p in ps:
info = p.xpath('string(.)').replace('\r','').replace('\n','').replace('\xa0','').replace(' ','').replace('\t','')
infobox.append(info)
# print(infobox)
return infobox
def drug_spider(url):
html = get_html(url)
selector = etree.HTML(html)
drugs = [i.replace('\n','').replace('\t', '').replace(' ','') for i in
selector.xpath('//div[@class="fl drug-pic-rec mr30"]/p/a/text()')]
# print(drugs)
return drugs
'''food治疗解析'''
def food_spider(url):
html = get_html(url)
selector = etree.HTML(html)
divs = selector.xpath('//div[@class="diet-img clearfix mt20"]')
try:
food_data = {}
food_data['good'] = divs[0].xpath('./div/p/text()')
food_data['bad'] = divs[1].xpath('./div/p/text()')
food_data['recommand'] = divs[2].xpath('./div/p/text()')
except:
return {}
return food_data
'''症状信息解析'''
def symptom_spider(url):
html = get_html(url)
selector = etree.HTML(html)
# 源代码中的结果是人名，因此对其进行了修改。
symptoms = selector.xpath('//span[@class="db f12 lh240 mb15 "]/a/text()')
ps = selector.xpath('//p')
detail = []
for p in ps:
info = p.xpath('string(.)').replace('\r','').replace('\n','').replace('\xa0', '').replace(' ', '').replace('\t','')
detail.append(info)
symptoms_data = {}
symptoms_data['symptoms'] = symptoms
symptoms_data['symptoms_detail'] = detail
# print(symptoms_data)
return symptoms, detail
def inspect_spider(url):
'''对检查项目的链接进行获取，有的网页时有检查链接的，有的是没有的'''
html = get_html(url)
selector = etree.HTML(html)
inspects = selector.xpath('//li[@class="check-item"]/a/@href')
return inspects
'''通用解析模块'''
def common_spider(url):
html = get_html(url)
selector = etree.HTML(html)
ps = selector.xpath('//p')
infobox = []
for p in ps:
info = p.xpath('string(.)').replace('\r', '').replace('\n', '').replace('\xa0', '').replace(' ','').replace('\t', '')
if info:
infobox.append(info)
return '\n'.join(infobox)
'''检查项抓取模块'''
def inspect_crawl():
for page in range(1, 3685):
try:
url = 'http://jck.xywy.com/jc_%s.html'%page
html = get_html(url)
data = {}
data['url'] = url
data['html'] = html
db['jc'].insert(data)
# print(data)
except Exception as e:
print(e)
spider_main()
inspect_crawl()
接着将解析的数据存入数据库中
- 在这一部分代码中，需要将max_cut中的disease.txt位置进行修改为…/dict/disease.txt，还需要在这个打开文件的时候加入encoding=‘utf-8’，即open(dict_path, encoding=‘utf-8’)，不然会报错。
- 在下边的导入代码中有first_name.txt文件，在源文件中并没有给出，我猜想应该是这个症状描述不包含疾病名称，因此我使用了disease.txt文件代替的。
- 执行程序的时候，必须要先执行这个函数modify_jc()，更新jc表的值，这样在执行函数collect_medical()的时候才不会报name错误。
#!/usr/bin/env python3
# coding: utf-8
# File: build_data.py
# Author: lhy<lhy_in_blcu@126.com,https://huangyong.github.io>
# Date: 18-10-3
import pymongo
from lxml import etree
import os
from max_cut import *
class MedicalGraph:
def __init__(self):
self.conn = pymongo.MongoClient()
# cur_dir = '/'.join(os.path.abspath(__file__).split('/')[:-1])
self.db = self.conn['test']
self.col = self.db['data']
first_words = [i.strip() for i in open('../dict/disease.txt', encoding='utf-8')]
alphabets = ['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y', 'z']
nums = ['1','2','3','4','5','6','7','8','9','0']
self.stop_words = first_words + alphabets + nums
self.key_dict = {
'医保疾病' : 'yibao_status',
"患病比例" : "get_prob",
"易感人群" : "easy_get",
"传染方式" : "get_way",
"就诊科室" : "cure_department",
"治疗方式" : "cure_way",
"治疗周期" : "cure_lasttime",
"治愈率" : "cured_prob",
'药品明细': 'drug_detail',
'药品推荐': 'recommand_drug',
'推荐': 'recommand_eat',
'忌食': 'not_eat',
'宜食': 'do_eat',
'症状': 'symptom',
'检查': 'check',
'成因': 'cause',
'预防措施': 'prevent',
'所属类别': 'category',
'简介': 'desc',
'名称': 'name',
'常用药品' : 'common_drug',
'治疗费用': 'cost_money',
'并发症': 'acompany'
}
self.cuter = CutWords()
def collect_medical(self):
cates = []
inspects = []
count = 0
for item in self.col.find():
data = {}
basic_info = item['basic_info']
name = basic_info['name']
if not name:
continue
# 基本信息
data['名称'] = name
data['简介'] = '\n'.join(basic_info['desc']).replace('\r\n\t', '').replace('\r\n\n\n','').replace(' ','').replace('\r\n','\n')
category = basic_info['category']
data['所属类别'] = category
cates += category
inspect = item['inspect_info']
inspects += inspect
attributes = basic_info['attributes']
# 成因及预防
data['预防措施'] = item['prevent_info']
data['成因'] = item['cause_info']
# 并发症
data['症状'] = list(set([i for i in item["symptom_info"][0] if i[0] not in self.stop_words]))
for attr in attributes:
attr_pair = attr.split('：')
if len(attr_pair) == 2:
key = attr_pair[0]
value = attr_pair[1]
data[key] = value
# 检查
inspects = item['inspect_info']
jcs = []
for inspect in inspects:
jc_name = self.get_inspect(inspect)
if jc_name:
jcs.append(jc_name)
data['检查'] = jcs
# 食物
food_info = item['food_info']
if food_info:
data['宜食'] = food_info['good']
data['忌食'] = food_info['bad']
data['推荐'] = food_info['recommand']
# 药品
drug_info = item['drug_info']
data['药品推荐'] = list(set([i.split('(')[-1].replace(')','') for i in drug_info]))
data['药品明细'] = drug_info
data_modify = {}
for attr, value in data.items():
attr_en = self.key_dict.get(attr)
if attr_en:
data_modify[attr_en] = value
if attr_en in ['yibao_status', 'get_prob', 'easy_get', 'get_way', "cure_lasttime", "cured_prob"]:
data_modify[attr_en] = value.replace(' ','').replace('\t','')
elif attr_en in ['cure_department', 'cure_way', 'common_drug']:
data_modify[attr_en] = [i for i in value.split(' ') if i]
elif attr_en in ['acompany']:
acompany = [i for i in self.cuter.max_biward_cut(data_modify[attr_en]) if len(i) > 1]
data_modify[attr_en] = acompany
try:
self.db['medical'].insert(data_modify)
count += 1
print(count)
except Exception as e:
print(e)
return
def get_inspect(self, url):
res = self.db['jc'].find_one({'url':url})
if not res:
return ''
else:
return res['name']
def modify_jc(self):
for item in self.db['jc'].find():
url = item['url']
content = item['html']
selector = etree.HTML(content)
name = selector.xpath('//title/text()')[0].split('结果分析')[0]
desc = selector.xpath('//meta[@name="description"]/@content')[0].replace('\r\n\t','')
self.db['jc'].update({'url':url}, {'$set':{'name':name, 'desc':desc}})
if __name__ == '__main__':
handler = MedicalGraph()
handler.modify_jc()
handler.collect_medical()
完成之后，使用如下命令可以导出数据
mongoexport -d test -c medical -o medical.json
其中，-d test 是指明数据库,
-c medical 是指明要导出的列表
-o medical.json 是指明导出的文件名，可以在前边指定位置