#!/usr/bin/python
# coding:utf-8
import os

from bs4 import BeautifulSoup
import requests
import json


nds = []
for yar in range(2018,2023):

    url = 'https://money.finance.sina.com.cn/corp/go.php/vFD_ProfitStatement/stockid/002279/ctrl/'+str(yar)+'/displaytype/4.phtml'

    page = requests.get(url)
    soup = BeautifulSoup(page.content, 'html.parser')
    title = soup.title.text
    #print(title)


    all_products = []
    products = soup.select('div.tagmain')
    print(products)
    print('----------------↓抓取数据表格------------')

    pythontable = soup.find('table',{'id':'ProfitStatementNewTable0'})
    print(pythontable)

    print('---------------↓抓取tbody-------------')

    pythontable1 = soup.find('table',{'id':'ProfitStatementNewTable0'}).find('tbody')
    print(pythontable1)


    print('---------------↓抓取每一行-------------')
    array = []
    rows = pythontable1.findAll('tr')
    for row in rows:
        cols = row.findAll('td')
        hang1 = []
        hang = []
        for i, col in enumerate(cols):
            hang1.append(col.text)
            if i == 0:
                print(col.text)
            if i > 0:
                hang.append(col.text)
            if i == 4:
                print(hang)
                array.append(hang1)

    print('---------------↓打印这个table-------------')
    print(array)



    print('---------------↓table转为python类型JSON-------------')
    nd = []
    for i in range(4):
        jdObj = {}
        jd = {}
        for j, row in enumerate(array):
            if j>0:
                cols = row
                # 替换字符，字符串直接调用replace方法
                msg = cols[i+1].replace(',', '')
                jd[cols[0]] = msg
                if len(jd)== len(array)-1:
                    jdObj['季度'] = array[0][1+i]
                    jdObj['value'] = jd
                    nd.append(jdObj)
    #print(nd)
    ndObj = {}
    ndObj['年度'] = yar
    ndObj['value'] = nd
    nds.append(ndObj)

    print('---------------↓输出年度JSON-------------')
    en_json = json.dumps(nd, ensure_ascii=False)
    print(en_json)



print('---------------↓输出全部JSON-------------')
en_json1 = json.dumps(nds, ensure_ascii=False)
print(en_json1)

# os.remove('/Users/sujiewei/Desktop/mysql.txt')
with open('/Users/sujiewei/Desktop/mysql.txt', 'w') as f:
    f.write(en_json1)

from pyecharts.charts import Bar,Line
import pyecharts.options as opts
import json

x_data = []

print('----------------↓读取json文件------------')
with open("/Users/sujiewei/Desktop/mysql.txt", "r", encoding="utf-8") as f:
    content = json.load(f)
print(content)

print('----------------↓整合营业总收入和营业总成本data------------')
zcbData = []
zsrData = []


#总
for j, col in enumerate(content):
    zcb = 0.00
    zsr = 0.00
    x_data.append(str(col.get("年度"))+'年')
    yar = col.get("value")
    #年
    for i, data in enumerate(yar):
        print(data)
        #季度
        mo = data.get("value")
        print(mo)
        zsr += float(mo["一、营业总收入"])
        zcb += float(mo["二、营业总成本"])

    zcbData.append(zcb)
    zsrData.append(zsr)

#qu 净利润
v = list(map(lambda x: x[0]-x[1], zip(zsrData, zcbData)))


print(zsrData)
print(zcbData)
print(v)

print('----------------↓生成统计图------------')
bar = (
    Bar()
    .add_xaxis(xaxis_data=x_data)
    .add_yaxis(
        series_name="营业总成本",
        y_axis=zcbData,
        label_opts=opts.LabelOpts(is_show=False),
    )
    .add_yaxis(
        series_name="营业总收入",
        y_axis=zsrData,
        label_opts=opts.LabelOpts(is_show=False),
    )
    .extend_axis(
        yaxis=opts.AxisOpts(
            name="净利润",
            type_="value",
            min_=min(v),
            max_=max(v),
            # interval=5,
            axislabel_opts=opts.LabelOpts(formatter="{value} 万元"),
        )
    )
    .set_global_opts(
        tooltip_opts=opts.TooltipOpts(
            is_show=True, trigger="axis", axis_pointer_type="cross"
             #鼠标移至该点时，横向虚线显示
        ),
        xaxis_opts=opts.AxisOpts(
            type_="category",
            axispointer_opts=opts.AxisPointerOpts(is_show=True, type_="shadow"),
            #鼠标移至某点时，竖趟阴影显示。
        ),
        yaxis_opts=opts.AxisOpts(
            name="金额",
            type_="value",
            min_=0,       #y轴最小值
            # max_=250,     #y轴最大值
            # interval=50,   #y轴刻度
            axislabel_opts=opts.LabelOpts(formatter="{value} 万元"), # y轴坐标显示
            axistick_opts=opts.AxisTickOpts(is_show=True),
            splitline_opts=opts.SplitLineOpts(is_show=True),
        ),
    )
)
# print(zsrData)


line = (
    Line()
        .add_xaxis(x_data)
        .add_yaxis(
        series_name="营业总收入",
        yaxis_index=0,    #y轴索引，即折线图用哪一个y轴， y轴从左至右的索引值为0,1,2……，即水量y轴索引为0，温度y轴索引为1
        y_axis=zsrData,
        # 折线图上点的附近否显示数据
        label_opts=opts.LabelOpts(is_show=False),
        )
        .add_yaxis(
        series_name="营业总成本",
        yaxis_index=0,    #y轴索引，即折线图用哪一个y轴， y轴从左至右的索引值为0,1,2……，即水量y轴索引为0，温度y轴索引为1
        y_axis=zcbData,
        # 折线图上点的附近否显示数据
        label_opts=opts.LabelOpts(is_show=False),
        )
        .add_yaxis(
        series_name="净利润",
        yaxis_index=1,    #y轴索引，即折线图用哪一个y轴， y轴从左至右的索引值为0,1,2……，即水量y轴索引为0，温度y轴索引为1
        y_axis=v,
        # 折线图上点的附近否显示数据
        label_opts=opts.LabelOpts(is_show=False),
        )
)

bar.overlap(line).render("test1.html")
bar.overlap(line).render_notebook()
print("http://localhost:63343/ocr-service/test1.html")