import requests
import json
import re
import pandas as pd
import time
from pyecharts.components import Table
from pyecharts import options as opts
from pyecharts.charts import Bar, Page,Pie,Line,Timeline,Map
from pyecharts.commons.utils import JsCode
from pyecharts.options import DataZoomOpts,ComponentTitleOpts





def Get_HTML():
    headers = {'User-Agent': 'Mozilla/5.0'}
    url = 'https://m.look.360.cn/events/feiyan?sv=&version=&market=&device=2&net=4&stype=&scene=&sub_scene=&refer_scene=&refer_subscene=&f=jsonp&location=true&sort=2&_=1649252949072&callback=jsonp2'
    try:
        r = requests.get(url, headers=headers)
        r.raise_for_status()
        r.encoding = r.apparent_encoding
        re = r.text[7:-2]
        response = json.loads(re)
        return response
    except:
        print("error!")
def China_data_Total():
    url='http://m.look.360.cn/subject/400?sign=360_6aa05217'
    headers={'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:99.0) Gecko/20100101 Firefox/99.0'}
    html = requests.get(url, headers=headers).text
    pattern=re.compile('"qcmsint1":"0"},"feiyanTrend":(.*),"local":',re.S)
    item=re.findall(pattern,html)
    response=json.loads(item[0])
    data = {
        "截止日期":response['total']['modifyTime'],
        "现存确诊":response['total']['currentConfirmed'],
        "境外输入":response['total']['overseasInput'],
        "现存无症状":response['total']['asymptom'],
        "累计确诊":response['total']['diagnosed'],
        "累计治愈":response['total']['cured'],
        "累计死亡":response['total']['died'],
        "现存_较昨日":response['newDiff']['currentConfirmed'],
        "境外输入_较昨日":response['newDiff']['overseasInput'],
        "无症状_较昨日":response['newDiff']['asymptom'],
        "累计_较昨日":response['newDiff']['diagnosed'],
        "治愈_较昨日":response['newDiff']['cured'],
        "死亡_较昨日":response['newDiff']['died']
    }
    return data
# 国内数据
def China_data(response):
    P_name, P_Ljqz, P_Cured, P_Died, P_Xcqz, P_Xzqz = [], [], [], [], [], []    #省数据
    C_name, C_Ljqz, C_Cured, C_Died, C_Xcqz, C_Xzqz = [], [], [], [], [], []    #市数据
    for i in range(34):
        P_name.append(response['data'][i]['cityShortName'])  # 城市名称
        P_Ljqz.append(response['data'][i]['diagnosed'])  # 累计确诊
        P_Cured.append(response['data'][i]['cured'])  # 治愈
        P_Died.append(response['data'][i]['died'])  # 死亡
        P_Xcqz.append(response['data'][i]['currentConfirmed'])  # 现存确诊
        P_Xzqz.append(response['data'][i]['diffDiagnosed'])  # 新增确诊
    data = {
        "地区": P_name,
        "新增确诊": P_Xzqz,
        "现存确诊": P_Xcqz,
        "累计确诊": P_Ljqz,
        "治愈人数": P_Cured,
        "死亡人数": P_Died,
    }
    return data

#河南省数据
def Henan_data():
    url = 'https://m.look.360.cn/events/feiyanCityInfo?sv=&version=&market=&device=2&net=4&stype=&scene=&sub_scene=&refer_scene=&refer_subscene=&f=jsonp&ename=henan&_=1650426134574&callback=jsonp4'
    headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:99.0) Gecko/20100101 Firefox/99.0'}
    html = requests.get(url, headers=headers).text[7:-2]
    response=json.loads(html)
    # print(response['data']['cityInfo'])
    C_name, C_Ljqz, C_Cured, C_Died, C_Xcqz, C_Xzqz = [], [], [], [], [], []  # 市数据
    for i in range(len(response['data']['cityInfo'])):
        C_name.append(response['data']['cityInfo'][i]['cityName'])   #名称
        C_Ljqz.append(response['data']['cityInfo'][i]['diagnosed'])  # 累计确诊
        C_Cured.append(response['data']['cityInfo'][i]['cured'])  # 治愈
        C_Died.append(response['data']['cityInfo'][i]['died'])  # 死亡
        C_Xzqz.append(response['data']['cityInfo'][i]['diffDiagnosed'])  # 新增确诊
    data = {
        "地区": C_name,
        "新增确诊": C_Xzqz,
        "累计确诊": C_Ljqz,
        "治愈人数": C_Cured,
        "死亡人数": C_Died
    }
    return data

def Abroad_data(response):  # 国外数据
    C_name, Ljqz, Cured, Died, Xcqz, Xzqz = [], [], [], [], [], []
    for i in range(196):
        c_name = response['country'][i]['provinceName']  # 城市名称
        ljqz = response['country'][i]['diagnosed']  # 累计确诊
        cured = response['country'][i]['cured']  # 治愈
        died = response['country'][i]['died']  # 死亡
        xzqz = response['country'][i]['diffDiagnosed']  # 新增确诊
        C_name.append(c_name)
        Ljqz.append(ljqz)
        Cured.append(cured)
        Died.append(died)
        Xzqz.append(xzqz)
    data = {
        "地区": C_name,
        "新增确诊": Xzqz,
        "累计确诊": Ljqz,
        "治愈人数": Cured,
        "死亡人数": Died
    }
    return data

def TimeLine():
    headers = {'User-Agent': 'Mozilla/5.0'}
    url = 'https://api.look.360.cn/events/feiyanHomeMulTrend?sv=&version=&market=&device=2&net=4&stype=&scene=&sub_scene=&refer_scene=&refer_subscene=&f=jsonp&_=1650032782170&callback=jsonp3'
    try:
        r = requests.get(url, headers=headers)
        r.raise_for_status()
        r.encoding = r.apparent_encoding
        re = r.text[7:-2]
        response = json.loads(re)
    except:
        print("error!")
    time,Ljqz, Cured, Died, Xcqz, Xzqz, Xz_Died, Xz_Cured= [], [], [], [], [], [], [], []
    for i in range(len(response['data']['timeline_n1'])):
        time.append(response['data']['timeline_n1'][i]['time'])         #时间
        Xzqz.append(response['data']['timeline_n1'][i]['diagnosed'])    #新增确诊
        Xcqz.append(response['data']['timeline_n2'][i]['total_currentConfirmed']) #现存确诊
        Ljqz.append(response['data']['timeline_n2'][i]['total_diagnosed'])   #累计确诊
        Cured.append(response['data']['timeline_n3'][i]['total_cured'])      #累计治愈
        Died.append(response['data']['timeline_n3'][i]['total_died'])      #累计死亡
        Xz_Died.append(response['data']['timeline_n4'][i]['died'])        #新增死亡
        Xz_Cured.append(response['data']['timeline_n4'][i]['cured'])      #新增治愈
    data={
        "时间":time,
        "新增确诊":Xzqz,
        "现存确诊":Xcqz,
        "累计确诊":Ljqz,
        "累计治愈":Cured,
        "累计死亡":Died,
        "新增死亡":Xz_Died,
        "新增治愈":Xz_Cured
    }
    return data

def View(data_1,data_2,data_3,data_4):
    #柱状图
    c_1 = Timeline(init_opts=opts.InitOpts(chart_id='1'))
    c_1.add_schema(play_interval=1000,
                   label_opts=opts.series_options.LabelOpts(color='#cfe2f3'),is_auto_play = True)
    for i in range(3):
        #全国累计详情柱状图
        C_1 = (
            Bar()
                .add_xaxis(data_1['地区'][i*11:(i+1)*11])
                .add_yaxis("累计确诊", data_1['累计确诊'][i*11:(i+1)*11],stack='stack1',label_opts=opts.LabelOpts(is_show=False))
                .add_yaxis("新增确诊", data_1['新增确诊'][i*11:(i+1)*11],stack='stack1',label_opts=opts.LabelOpts(is_show=False))
                .add_yaxis("死亡人数", data_1['死亡人数'][i * 11:(i + 1) * 11],stack='stack1',label_opts=opts.LabelOpts(is_show=False))
                .add_yaxis("治愈人数", data_1['治愈人数'][i * 11:(i + 1) * 11],stack='stack1',label_opts=opts.LabelOpts(is_show=False))
                .add_yaxis("现存确诊", data_1['现存确诊'][i * 11:(i + 1) * 11],stack='stack1',label_opts=opts.LabelOpts(is_show=False))
                .reversal_axis()
                # .set_global_opts(legend_opts=opts.LegendOpts(selected_mode='single'))  # 单选模式
            .set_global_opts(xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(color='white')),#调整x轴字体颜色
                                yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(color='white')),
                             legend_opts=opts.LegendOpts(selected_mode='single'),
                             title_opts=opts.TitleOpts("国内疫情详情",pos_right=0,pos_top=20,title_textstyle_opts=opts.TextStyleOpts(font_size=13,color="#cfe2f3")))
        )
        c_1.add(C_1, "第{}页".format(i+1))
        # 全国地图
    c_2 = (
            Map(init_opts=opts.InitOpts(chart_id='2'))
                # .add("死亡人数", [list(z) for z in zip(data_1['地区'], data_1['死亡人数'])], "china",is_selected=False)        #默认关闭该标签
                .add("累计确诊",[list(z) for z in zip(data_1['地区'], data_1['累计确诊'])], "china")
                .add("死亡人数", [list(z) for z in zip(data_1['地区'], data_1['死亡人数'])], "china")
                .add("治愈人数", [list(z) for z in zip(data_1['地区'], data_1['治愈人数'])], "china")
                .add("新增确诊", [list(z) for z in zip(data_1['地区'], data_1['新增确诊'])], "china")
                .add("现存确诊", [list(z) for z in zip(data_1['地区'], data_1['现存确诊'])], "china")
                .set_global_opts(
                title_opts=opts.TitleOpts(""),
                visualmap_opts=opts.VisualMapOpts(max_=10000),
                legend_opts=opts.LegendOpts(selected_mode='single')    #单选模式
            )
        )
        #时间线折线图
    c_3 = (
            Line(init_opts=opts.InitOpts(chart_id='3'))
                .add_xaxis(data_3['时间'])
                .add_yaxis("新增确诊",data_3['新增确诊'],label_opts=opts.LabelOpts(is_show=False),linestyle_opts=opts.LabelOpts(color='#DC143C'))
                .add_yaxis("现存确诊",data_3['现存确诊'],label_opts=opts.LabelOpts(is_show=False),linestyle_opts=opts.LabelOpts(color='#a98175'))
                .add_yaxis("累计确诊",data_3['累计确诊'], label_opts=opts.LabelOpts(is_show=False),linestyle_opts=opts.LabelOpts(color='#60281e'))
                .add_yaxis("累计治愈",data_3['累计治愈'], label_opts=opts.LabelOpts(is_show=False),linestyle_opts=opts.LabelOpts(color='#2add9c'))
                .add_yaxis("累计死亡",data_3['累计死亡'], label_opts=opts.LabelOpts(is_show=False),linestyle_opts=opts.LabelOpts(color='black'))
                .add_yaxis("新增死亡",data_3['新增死亡'], label_opts=opts.LabelOpts(is_show=False),linestyle_opts=opts.LabelOpts(color='#758a99'))
                .add_yaxis("新增治愈",data_3['新增治愈'], label_opts=opts.LabelOpts(is_show=False),linestyle_opts=opts.LabelOpts(color='#1bd1a5'))
                .set_global_opts(
                title_opts=opts.TitleOpts(title="疫情汇总时间线",pos_top=20,title_textstyle_opts=opts.TextStyleOpts(font_size=13,color="#cfe2f3")),
                tooltip_opts=opts.TooltipOpts(trigger="axis"),
                xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(color='white')),  # 调整x轴字体颜色
                yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(color='white')),
                legend_opts=opts.LegendOpts(selected_mode='single')
            )
        )
        #河南省地图
    c_4 = (
            Map(init_opts=opts.InitOpts(chart_id='4'))
                # .add("死亡人数", [list(z) for z in zip(data_1['地区'], data_1['死亡人数'])], "china",is_selected=False)        #默认关闭该标签
                .add("累计确诊", [list(z) for z in zip(data_4['地区'], data_4['累计确诊'])], "河南")
                .add("死亡人数", [list(z) for z in zip(data_4['地区'], data_4['死亡人数'])], "河南")
                .add("治愈人数", [list(z) for z in zip(data_4['地区'], data_4['治愈人数'])], "河南")
                .add("新增确诊", [list(z) for z in zip(data_4['地区'], data_4['新增确诊'])], "河南")

                .set_global_opts(
                title_opts=opts.TitleOpts(title='省内详细信息',pos_top=30,title_textstyle_opts=opts.TextStyleOpts(font_size=13, color="#cfe2f3")),
                visualmap_opts=opts.VisualMapOpts(max_=500),
                legend_opts=opts.LegendOpts(selected_mode='single')  # 单选模式
            )
        )
        #省内死亡详情饼图
    c_5 = (
            Pie(init_opts=opts.InitOpts(chart_id='5'))
                .add("死亡人数", [list(z) for z in zip(data_4['地区'], data_4['死亡人数'])])
                .set_global_opts(title_opts=opts.TitleOpts('市死亡人数',title_textstyle_opts=opts.TextStyleOpts(font_size=13, color="gray"),),
                                 legend_opts=opts.LegendOpts(is_show=False))
                # .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"),)
        )
    # 汇总数据与昨日相比
    data = China_data_Total()
    c_7 = (
        Pie(init_opts=opts.InitOpts(chart_id='7'))
        .set_global_opts(
                    title_opts=opts.TitleOpts(
                        title="现存确诊" + " " * 17 + "境外输入" + " " * 17 + "现存无症状", title_textstyle_opts=opts.TextStyleOpts(font_size=10, color="white"), ))
        )
    c_8 = (
        Pie(init_opts=opts.InitOpts(chart_id='8'))
        .set_global_opts(
                    title_opts=opts.TitleOpts(
                        title="累计确诊"+ " " * 17 + "累计治愈"+ " " * 17 + "累计死亡", title_textstyle_opts=opts.TextStyleOpts(font_size=10, color="white"), ))
        )
    c_9 = (
        Pie(init_opts=opts.InitOpts(chart_id='9'))
        .set_global_opts(
                    title_opts=opts.TitleOpts(
                        title=str(data['现存_较昨日']) + " " * 25 + str(data['境外输入_较昨日']) + " " * 25  + str(data['无症状_较昨日']), title_textstyle_opts=opts.TextStyleOpts(font_size=10, color="#e9e7ef"), ))
        )
    c_10 = (
        Pie(init_opts=opts.InitOpts(chart_id='10'))
        .set_global_opts(
                    title_opts=opts.TitleOpts(
                        title=str(data['累计_较昨日']) + " " * 25 + str(data['治愈_较昨日']) + " " * 25+ str(data['死亡_较昨日']), title_textstyle_opts=opts.TextStyleOpts(font_size=10, color="#e9e7ef")))
        )
    #数字
    c_11 = (
        Pie(init_opts=opts.InitOpts(chart_id='16'))
            .set_global_opts(
            title_opts=opts.TitleOpts(
                title=str(data['现存确诊']) + " " * 3 + str(data['境外输入']) + " " * 3 + str(data['现存无症状']),
                title_textstyle_opts=opts.TextStyleOpts(font_size=23, color="#CD3700")))
    )
    c_12 = (
        Pie(init_opts=opts.InitOpts(chart_id='17'))
            .set_global_opts(
            title_opts=opts.TitleOpts(
                title=str(data['累计确诊']) + " " * 3 + str(data['累计治愈']) + " " * 3 + str(data['累计死亡']),
                title_textstyle_opts=opts.TextStyleOpts(font_size=23, color="#7F7F7F")))
    )

    tu_1 = (
        Line(init_opts=opts.InitOpts(width="1500px",
                                     height="850px",
                                     bg_color={"type": "pattern", "image": JsCode("img"), "repeat": "no-repeat"},
                                     chart_id='11'))
            .add_xaxis([None])
            .add_yaxis("", [None])
            .set_global_opts(
            title_opts=opts.TitleOpts(),
            yaxis_opts=opts.AxisOpts(is_show=False),
            xaxis_opts=opts.AxisOpts(is_show=False))
    )

    tu_1.add_js_funcs(
        """
        var img = new Image(); img.src = './images/bg_body.jpg';

        """
    )
    tu_2 = (
        Line(init_opts=opts.InitOpts(
                                     bg_color={"type": "pattern", "image": JsCode("img"), "repeat": "no-repeat"},
                                     chart_id='12'))
            .add_xaxis([None])
            .add_yaxis("", [None])
            .set_global_opts(
            yaxis_opts=opts.AxisOpts(is_show=False),
            xaxis_opts=opts.AxisOpts(is_show=False))
    )
    tu_2.add_js_funcs(
        """
        var img = new Image(); img.src = './images/bg_box5.png';

        """
    )
    tu_3 = (
        Line(init_opts=opts.InitOpts(chart_id='13',
            bg_color={"type": "pattern", "image": JsCode("img"), "repeat": "no-repeat"},
        ))
            .add_xaxis([None])
            .add_yaxis("", [None])
            .set_global_opts(
            yaxis_opts=opts.AxisOpts(is_show=False),
            xaxis_opts=opts.AxisOpts(is_show=False))
    )
    tu_3.add_js_funcs(
        """
        var img = new Image(); img.src = './images/bg_box5.png';

        """
    )
    tu_4 = (
        Line(init_opts=opts.InitOpts(chart_id='14',
            bg_color={"type": "pattern", "image": JsCode("img"), "repeat": "no-repeat"},
        ))
            .add_xaxis([None])
            .add_yaxis("", [None])
            .set_global_opts(
            yaxis_opts=opts.AxisOpts(is_show=False),
            xaxis_opts=opts.AxisOpts(is_show=False))
    )
    tu_4.add_js_funcs(
        """
        var img = new Image(); img.src = './images/bg_box4.png';

        """
    )
    tu_5 = (
        Line(init_opts=opts.InitOpts(width="1500px",
                                     height="200px",
                                     bg_color={"type": "pattern", "image": JsCode("img"), "repeat": "no-repeat"},
                                     chart_id='15'))
            .add_xaxis([None])
            .add_yaxis("", [None])
            .set_global_opts(
            title_opts=opts.TitleOpts(title="全球疫情信息 截至" + data['截止日期'],
                                      pos_left='center',
                                      title_textstyle_opts=opts.TextStyleOpts(font_size=21, color='#51c2d5'),
                                      pos_top='23%'),
            yaxis_opts=opts.AxisOpts(is_show=False),
            xaxis_opts=opts.AxisOpts(is_show=False))
    )
    tu_5.add_js_funcs(
        """
        var img = new Image(); img.src = './images/bg_title.png';

        """
    )
    page = Page(layout=Page.DraggablePageLayout, page_title="可视化大屏")
    page.add(tu_1,tu_2,tu_3,tu_4,c_1,c_2,c_3,c_4,c_5,c_7,c_8,c_9,c_10,tu_5,c_11,c_12)
    page.render('国内疫情信息.html')

def Style():
    # 固定样式
    Page.save_resize_html(source="./国内疫情信息.html",  # 上面的HTML文件名称
                          cfg_file="chart_config_3.json",  # 保存的json配置文件
                          dest="new_国内疫情信息可视化大屏.html"  # 新HTML文件名称，可以空缺，默认resize_render.html
                          )
def main():
    a=0
    while True:
        data_1 = China_data(Get_HTML())
        data_2 = Abroad_data(Get_HTML())
        data_3 = TimeLine()
        data_4=Henan_data()
        date=China_data_Total()['截止日期']
        if date!=a:
            View(data_1, data_2, data_3,data_4)
            Style()
            a=date

main()

from pyecharts import options as opts
from pyecharts.charts import Bar, Grid, Line, Liquid, Page, Pie
from pyecharts.faker import Faker
from pyecharts.globals import SymbolType

#饼状图
def pie():
    c = (
        Pie()
        .add("", [['跳水', 12], ['射击', 11], ['举重', 8], ['竞技体操', 8], ['乒乓球', 7], ['游泳', 6], ['羽毛球', 6], ['田径', 5], ['静水皮划艇', 3], ['蹦床体操', 3], ['自由式摔跤', 3], ['赛艇', 3], ['空手道', 2], ['拳击', 2], ['帆船', 2], ['花样游泳', 2], ['跆拳道', 1], ['场地自行车赛', 1], ['古典式摔跤', 1], ['击剑', 1], ['三人篮球', 1]],center=["50%", "60%"],)
        .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
#         .render("饼图.html")
        )
    return c
#     return c.render_notebook()

#水滴图
def wb():
    c = (
        Liquid()
        .add("", [0.3, 0.7], is_outline_show=False, shape=SymbolType.DIAMOND)
        .set_global_opts(title_opts=opts.TitleOpts(title="Liquid-Shape-Diamond"))
#         .render("liquid_shape_diamond.html")
        )
    return c
#     return c.render_notebook()

#柱状图
def bar():
    c = (
        Bar()
        .add_xaxis(Faker.choose())
        .add_yaxis("商家A", Faker.values(), stack="stack1")
        .add_yaxis("商家B", Faker.values(), stack="stack1")
        .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
        .set_global_opts(title_opts=opts.TitleOpts(title="Bar-堆叠数据（全部）"))
#         .render("bar_stack0.html")
        )
    return c
#     return c.render_notebook()
page = Page(layout=Page.DraggablePageLayout, page_title="2020东京奥运会奖牌榜")

# 在页面中添加图表
page.add(
    pie(),
    wb(),
    bar())
page.render('test.html')