app.py

import json
from urllib import request
import flask
import pandas as pd
import io
import requests
from fake_useragent import UserAgent
import time
import random
import plotly
import plotly.express as px

app1 = flask.Flask(__name__)


@app1.route("/")
def hello():
    return flask.render_template("home_page.html")


@app1.route("/tellYouPopStock")
def tellYouPopStock():
    data_name_dict = {"Number": "股票數量",
                      "Code": "股票代碼", "Name": "股票名稱", "Date": "日期"}
    opendata_url = "https://openapi.twse.com.tw/v1/Announcement/BFZFZU_T"
    with request.urlopen(opendata_url) as response:
        data = json.load(response)
        print(data)
        print(type(data))
        for row in data:
            for key, value in data_name_dict.items():
                print(value, ": ", row[key])

    return flask.render_template("tell_you_pop_stock.html", data=data, data_name_dict=data_name_dict.items())


@app1.route("/stockPrice")
def stockPrice():
    data_name_dict = {"Code": "股票代號", "Name": "股票名稱",
                      "ClosingPrice": "日收盤價", "MonthlyAveragePrice": "月平均價"}
    opendata_url = "https://openapi.twse.com.tw/v1/exchangeReport/STOCK_DAY_AVG_ALL"
    with request.urlopen(opendata_url) as response:
        data = json.load(response)
        # for individualStock in data:
        #     for key,value in individualStock.items():
        #         print(key,": ",value)
        #     print("-----------------------")
    return flask.render_template("stocks_price.html", data=data, data_name_dict=data_name_dict)


@app1.route("/individualStock", methods=['GET'])
def individualStock():
    # "stat":"查詢日期小於99年1月4日，請重新查詢!"
    stackNo = flask.request.args.get("stockNo")
    # stackNo = "0050"
    date = 202201001  # 起始年月份(都是只要1日)
    date_max = 20221101  # 現在最新年月份
    ua = UserAgent()
    data = pd.DataFrame()
    while date <= date_max:
        time.sleep(1.5+1*random.random())
        data_url = "https://www.twse.com.tw/exchangeReport/STOCK_DAY?response=csv&date=" + \
            str(date)+"&stockNo="+str(stackNo)
        headers = {'User-Agent': ua.random}
        try:
            s = requests.get(data_url, headers=headers).content
            data_new = pd.read_csv(io.StringIO(s.decode('big5')), encoding='big5', skiprows=1, usecols=[
                                   "日期", "成交股數", "成交金額", "開盤價", "最高價", "最低價", "收盤價", "漲跌價差", "成交筆數"])

            # 刪除最後4-5行說明文字，判斷 成交股數==nan 就刪除
            for index, row in data_new.iterrows():
                # print(row, " type", type(row))
                # print(row.成交股數)
                if (pd.isna(row.成交股數)):
                    data_new.drop(labels=None, axis=0, index=index,
                                  columns=None, level=None, inplace=True, errors='raise')
                    # axis – Default 0 -> 0 drop rows 1 drop columns.

            data = data.append(data_new, ignore_index=True)
            # print(data_new)
        except:
            print("Connection error!")
        if int(int(date/100) % 100) == 12:
            date += 8900
        else:
            date += 100

    # print('='*20)
    # print(data)
    # data.to_csv("data/"+str(stackNo)+'.csv')

    # K線圖
    fig1 = plotly.graph_objects.Figure(data=[plotly.graph_objects.Candlestick(x=data['日期'],  # type: ignore
                                                                              open=data['開盤價'],
                                                                              high=data['最高價'],
                                                                              low=data['最低價'],
                                                                              close=data['收盤價'])])
    graphJSON1 = json.dumps(fig1, cls=plotly.utils.PlotlyJSONEncoder)

    # 漲跌價差
    clrred = True
    clrgrn = False
    clrs = []
    for row in data.itertuples():
        # print(row.漲跌價差, type(row.漲跌價差))
        try:
            ups_downs = float(row.漲跌價差)
        except:
            # row.漲跌價差 = X0.00
            ups_downs = float(row.漲跌價差.replace('X', '', 1))  # 從左邊屬過來第一個X刪除

        # 漲跌價差<0 綠色 反之 紅色
        if (ups_downs < 0):
            clrs.append(clrgrn)
        else:
            clrs.append(clrred)
    data['ups_downs_category'] = clrs

    fig2 = px.bar(data, x='日期', y='漲跌價差', color='ups_downs_category',  # type: ignore
                              color_discrete_sequence=['rgb(255,0,0)', 'rgb(0,255,0)'])
    graphJSON2 = json.dumps(fig2, cls=plotly.utils.PlotlyJSONEncoder)

    # 成交股數
    data.成交股數 = data.成交股數.str.replace(',', '').astype('int64')
    fig3 = px.bar(data, x='日期', y='成交股數')  # type: ignore
    graphJSON3 = json.dumps(fig3, cls=plotly.utils.PlotlyJSONEncoder)

    return flask.render_template("individual_stock.html", tables=[data.to_html(classes=['table', 'table-striped', 'table-bordered', 'table-hover', 'hover-primary'])], titles=data.columns.values, graphJSON1=graphJSON1, graphJSON2=graphJSON2, graphJSON3=graphJSON3)


if __name__ == "__main__":
    app1.run()