2021.3.17

20210317

陰天+10攝氏度，完美的天氣

今天忙着寫代碼呢，沒空寫日記，代碼還差個數據分析的部分

等明天去圖書館借點書看看就知道了

明天重要的事情：

• 早上起來洗內褲
• 圖書館裏複習數學！！！重要！！！

困了，想睡覺了

# conding=utf-8
import time

import tushare as ts
import pandas as pd
import numpy as np
import csv
import re
import datetime


def maintask():
    # 接口
    pro = ts.pro_api('1ac31a21fca91ccbbb438f1896eab5804d29552193c9fdb7b0e689d5')
    # 獲取全部股票
    pool = pro.stock_basic(exchange='',
                           list_status='L',
                           adj='qfq',
                           fields='ts_code,name')
    print('得到上市股票總數：', len(pool) - 1)

    # 經過遍歷pool的股票代碼索引ts_code得到每隻股票的三天交易數據：
    j = 1
    for i in pool.ts_code:
        # 進度
        num = int(len(pool) - 1)
        p = round(float(j / num * 100), 2)
        print('正在獲取第%d家，股票代碼%s' % (j, i) + ",進度" + str(p) + "%")
        # 延時
        time.sleep(0.301)
        # 接口,數據導入
        j += 1
        df1 = pro.daily(ts_code=i,
                        start_date=startdate,
                        end_date=enddate,
                        fields='ts_code, trade_date, open,  close,  change, pct_chg')
        df2 = pro.daily(ts_code=i,
                        start_date=str(int(startdate) - 1),
                        end_date=str(int(startdate) - 1),
                        fields='ts_code, trade_date, open,  close,  change, pct_chg')
        df3 = pro.daily(ts_code=i,
                        start_date=str(int(startdate) - 2),
                        end_date=str(int(startdate) - 2),
                        fields='ts_code, trade_date, open,  close,  change, pct_chg')

        dataCSV1 = pd.DataFrame(df1)
        path = 'D://PycharmProjects D//'
        filename = path + startdate + "StockData" + re.sub(r'[^0-9]', '',
                                                           datetime.datetime.now().strftime("%Y%m%d")) + '.csv'
        dataCSV1.to_csv(filename, index=False, mode="a", header=True, encoding="GBK")

        dataCSV2 = pd.DataFrame(df2)
        path = 'D://PycharmProjects D//'
        filename = path + str(int(startdate) - 1) + "StockData" + re.sub(r'[^0-9]', '',
                                                                         datetime.datetime.now().strftime(
                                                                             "%Y%m%d")) + '.csv'
        dataCSV2.to_csv(filename, index=False, mode="a", header=True, encoding="GBK")

        dataCSV3 = pd.DataFrame(df3)
        path = 'D://PycharmProjects D//'
        filename = path + str(int(startdate) - 2) + "StockData" + re.sub(r'[^0-9]', '',
                                                                         datetime.datetime.now().strftime(
                                                                             "%Y%m%d")) + '.csv'
        dataCSV3.to_csv(filename, index=False, mode="a", header=True, encoding="GBK")
    # 處理csv


if __name__ == '__main__':
    startdate = "20210316"
    enddate = startdate
    maintask()

看上去多實際上沒啥東西