# 整体实现思路：
#（1）调用tushare包
#（2）确定累积涨幅的期间
import tushare as ts
import pandas as pd
from functools import reduce
from datetime import datetime
now=datetime.now()
date_str=now.strftime('%Y-%m-%d')
d=pd.DataFrame()
pro=ts.pro_api("a52bfa14a84e6bde9f309d723a782b4cc49324b46da5df396d03eb70")
df = pro.daily(trade_date='20230612')
#first_close=df['close']
df=df.drop(columns=['open','low','high','pre_close','change','pct_chg','vol','amount'])
#code_list=df['ts_code']
df1 = pro.daily(trade_date='20230616')
df1=df1.drop(columns=['open','low','high','pre_close','change','pct_chg','vol','amount'])
#last_close=df1['close']
#print(last_close)
df2=[df,df1]
df0=reduce(lambda left,right:pd.merge(left,right,on=['ts_code']),df2)
rank_data=(df0['close_y']-df0['close_x'])/df0['close_x']
df0['rank']=rank_data
df0=df0.sort_values(by='rank',ascending=False,axis=0)
#print(df0)
ts_code=df0['ts_code']
data = pro.stock_basic(exchange='', list_status='L', fields='ts_code,name,area,industry')
df3=[df0,data]
df0=reduce(lambda left,right:pd.merge(left,right,on=['ts_code']),df3)
#df0=df0.drop(columns=['股票简称','行业'])
#df0['股票简称']=data['name']
#df0['行业']=data['industry']
df0.to_excel('D:/投资拾贝纪/python代码/累计涨幅排名/2023.06.12-06.16累积涨幅排名'+date_str+'.xlsx',header=True, index=False,encoding='GBK')
