【Python网络爬虫】39健康网急诊科疾病爬取

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39健康网

https://jbk.39.net/bw/jizhenke/

Python源码

from bs4 import BeautifulSoup
import xlwt
import requests
import re

def ask_url(url):
    head = {    
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.67 Safari/537.36 Edg/87.0.664.47"
        # "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.183 Safari/537.36 Edg/86.0.622.63"
    }
    try:
        r = requests.get(url, headers=head, timeout=30)
        r.raise_for_status()
        r.encoding = 'utf-8'
        return r.text
    except:
        return ""

def get_data(base_url):
    data_list = []
    
    # 遍历每一页
    for i in range(0, 40):
        url = base_url + str(i + 1)
        html = ask_url(url)
        if html == "":
            continue
        soup = BeautifulSoup(html, 'html.parser')
    
        # 遍历每一种疾病
        for item in soup.find_all('div', class_="result_item"):
            data = {}
            
            if item.div.p.span.string == "疾病":
                # diseaseName
                data['diseaseName'] = item.div.p.a.string
                
                # diseaseAlias
                # data.append(item.div.p.span.string.strip('（）'))
                
                # symptom
                symptoms = []
                p = item.find('p', class_='result_item_content_label')
                for symptom in p.find_all('a'):
                    symptoms.append(symptom.string)
                
                # https://jbk.39.net/zs/
                sub_url = item.div.p.a.attrs["href"]
                sub_html = ask_url(sub_url)
                if sub_html == "":
                    continue
                sub_soup = BeautifulSoup(sub_html, 'html.parser')
                
                information_ul = sub_soup.find('ul', class_="information_ul")
                for detail in information_ul.find_all('li'):
                    if detail.i.string == '别名：':
                        data['diseaseAlias'] = detail.span.string
                    elif detail.i.string == '发病部位：':
                        data['siteOfOnset'] = []
                        for site in detail.span.find_all('a'):
                            data['siteOfOnset'].append(site.string)
                    elif detail.i.string == '传染性：':
                        data['infectivity'] = detail.span.string
                    elif detail.i.string == '多发人群：':
                        data['multiplePopulation'] = detail.span.string
                    elif detail.i.string == '并发症：':
                        data['complication'] = []
                        for complication in detail.span.find_all('a'):
                            data['complication'].append(complication.string)
                    elif detail.i.string == '挂号科室：':
                        data['registrationDepartment'] = []
                        for department in detail.span.find_all('a'):
                            data['registrationDepartment'].append(department.string)
                    elif detail.i.string == '临床检查：':
                        data['clinicalExamination'] = []
                        for examination in detail.span.find_all('a'):
                            data['clinicalExamination'].append(examination.string)
                    elif detail.i.string == '典型症状：':
                        for symptom in detail.span.find_all('a'):
                            symptoms.append(symptom.string)
                        data['commonDrugs'] = symptoms
                
                information_ul1 = sub_soup.find('ul', class_="information_ul information_ul_bottom")
                for detail in information_ul1.find_all('li'):
                    if detail.i.string == '常用药品：':
                        data['commonDrugs'] = []
                        for drug in detail.span.find_all('a'):
                            data['commonDrugs'].append(drug.string)

            data_list.append(data)
            
    return data_list


def save_data(data_list, save_path):
    book = xlwt.Workbook(encoding='utf-8', style_compression=0)
    sheet = book.add_sheet("智能诊断数据集", cell_overwrite_ok=True)
    col = ("diseaseName", "diseaseAlias", "siteOfOnset", "infectivity", "multiplePopulation", "earlySymptom", "advancedSymptom", "complication", "registrationDepartment", "clinicalExamination", "commonDrugs")
    length = len(data_list)
    for i in range(0, 11):
        sheet.write(0, i, col[i])
    for i in range(0, length):
        print("\r当前进度：{:.2f}%".format((i + 1) * 100 / length), end="")
        data = data_list[i]
        for j in range(0, 11):
            if col[j] in data:
                sheet.write(i + 1, j, data[col[j]])
    book.save(save_path)
    return ""

if __name__ == "__main__":
    base_url = "https://jbk.39.net/bw/jizhenke_p"
    save_path = ".\\智能诊断数据集.xls"
    # html = ask_url(base_url)
    
    data_list = get_data(base_url)
    save_data(data_list, save_path)

实验结果

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