Python新型冠状病毒疫情数据自动爬取+统计+发送报告+数据屏幕（一）爬虫篇

项目功能设计：

1. 定时爬取疫情数据存入Mysql
2. 进行数据分析制作疫情报告
3. 使用itchat给亲人朋友发送分析报告
4. 基于Django做数据屏幕
5. 使用Tableau做数据分析

来看看最终的效果

目前已经完成80% 完成后第一时间分享给大家

接下来我们来介绍爬取疫情数据

目标网址：丁香医生

import re
import time
import json
import datetime
import requests
import pymysql
import pandas as pd


class VirusSupervise(object):
    def __init__(self):
        self.url = 'https://3g.dxy.cn/newh5/view/pneumonia?scene=2&clicktime=1579582238&enterid=1579582238&from=timeline&isappinstalled=0'
        self.all_data = list()
        self.host_ip = "127.0.0.1"  # 你的mysql服务器地址
        self.host_user = "root"
        self.password = 123456  # 你的mysql密码

    def request_page(self):
        """
        请求页面数据
        """
        res = requests.get(self.url)
        res.encoding = 'utf - 8'
        pat0 = re.compile('window.getAreaStat = ([\s\S]*?)')
        data_list = pat0.findall(res.text)
        data = data_list[0].replace('}catch(e){}', '')
        data = eval(data)
        return data

    def deep_spider(self, data, province_name):
        """
        深度提取出标签里详细的数据
        :param data:
        :param province_name:
        :return:
        """
        for temp_data in data:
            self.all_data.append([temp_data["cityName"], temp_data["confirmedCount"], temp_data["curedCount"],
                                  temp_data["deadCount"], province_name, datetime.date.today(),
                                  datetime.datetime.now().strftime('%H:%M:%S')])

    def filtration_data(self):
        """
        过滤数据
        """
        temp_data = self.request_page()
        province_short_names, confirmed_counts, cured_counts, dead_counts = list(), list(), list(), list()
        for i in temp_data:
            province_short_names.append(i['provinceShortName'])  # 省份
            confirmed_counts.append(i['confirmedCount'])  # 确诊
            cured_counts.append(i['curedCount'])  # 治愈
            dead_counts.append(i['deadCount'])  # 死亡
            self.deep_spider(i['cities'], i["provinceShortName"])  # 深度解析数据添加到实例属性中

        data_all = pd.DataFrame(self.all_data, columns=["城市", "确诊", "治愈", "死亡", "省份", "日期", "时间"])
        # print(data_all[data_all["省份"] == "陕西"])
        df = pd.DataFrame()
        df['省份'] = province_short_names
        df['确诊'] = confirmed_counts
        df['治愈'] = cured_counts
        df['死亡'] = dead_counts
        print(df)
        # data_all.to_csv("疫情数据_1.csv", encoding="utf_8_sig")
        return data_all

    def insert_wis_sql(self):
        data = self.filtration_data()

        coon = pymysql.connect(host=self.host_ip, user=self.host_user, password=self.password, database="epidemic_data",
                                    charset="utf8")
        number = int(pd.read_sql("select cycle from all_data order by id DESC limit 1", coon)["cycle"].to_list()[0]) + 1
        print("正在向阿里云服务器插入数据: ", number)
        cursor = coon.cursor()  # 创建事务
        sql = "insert into all_data(cityName, confirmedCount, curedCount, deadCount, province_name, " \
              "date_info, detail_time, cycle) values(%s, %s, %s, %s, %s, %s, %s, %s)"

        print("正在插入数据...")
        for cityName, confirmedCount, curedCount, deadCount, province_name, date_info, detail_time in zip(data["城市"],
                        data["确诊"], data["治愈"], data["死亡"], data["省份"], data["日期"], data["时间"]):
            cursor.execute(sql, (cityName, confirmedCount, curedCount, deadCount, province_name, date_info, detail_time, number))
            coon.commit()
        print("数据插入完成...")
        cursor.close()
        coon.close()


if __name__ == '__main__':
    sup = VirusSupervise()
    sup.insert_wis_sql()

如果没有mysql服务器直接运行 sup.filtration_data() 然后使用pandas直接to_csv即可完成数据收集， 如果想定时爬去，给程序加上循环睡眠

效果展示：

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