tkinter学习

导报： 

import alpha
import akshare as ak
import sql
import time
import pandas as pd
import PySimpleGUI as sg
import tkinter as tk
import matplotlib.pyplot as plt
plt.rcParams['font.family']='SimHei'
plt.rcParams['axes.unicode_minus']=False

创建tkinter

root=tk.Tk()
root.title('alpha1到200计算')
root.geometry('500x200')

按键功能：

def culu_all_alpha_to_sql():
    '''
    计算全部的alpha alpha1到alpha191
    '''
    stock=sg.popup_get_text('输入股票代码比如sh600111')
    start_date=sg.popup_get_text('输入开始人气比如20210101')
    table_name=stock+'alpha'
    #连接数据库
    sql.learn_mysql().concnet_mysql()
    #删除数据表
    sql.learn_mysql().drop_table(table_name=table_name)
    #建立数据表
    sql.learn_mysql().create_table(table_name=table_name)
    #添加标题
    sql.learn_mysql().add_table_columns_name(table_name=table_name,columns='date',endcode='varchar(225)')
    sql.learn_mysql().add_table_columns_name(table_name=table_name,columns='alpha',endcode='varchar(225)')
    sql.learn_mysql().add_table_columns_name(table_name=table_name,columns='value',endcode='varchar(225)')
    sql.learn_mysql().drop_table_columns_name(table_name=table_name,columns='id')
    #sql.learn_mysql().desc_table(table_name=table_name)
    #获取股票数据
    df=ak.stock_zh_a_daily(symbol=stock,start_date=start_date)
    #该名称
    loc=time.localtime()
    #周末不计算
    if loc.tm_wday<7:
        year=loc.tm_year
        mo=loc.tm_mon
        daily=loc.tm_mday
        if mo<=9:
            mo='0'+str(mo)
        if daily<=9:
            daily='0'+str(daily)
        date='{}-{}-{}'.format(year,mo,daily)
        df.rename(columns={'data':'data','open':'openPrice','close':'closePrice','low':'lowestPrice','high':'highestPrice','volume':'turnoverVol'},inplace=True)
        for i in range(1,192):
            if i<=9:
                i='00'+str(i)
            elif i<=99 and int(i)>9:
                i='0'+str(i)
            else:
                pass
            try:
                alpha_value=eval('alpha.alpha{}'.format(i))(data=df)
                bj=i
                sql.learn_mysql().insert_alpha(table_name=table_name,value=[date,str(bj),str(alpha_value)])
            except:
                print('计算失败')  
        sql.learn_mysql().show_table_context(table_name=table_name)  
    else:
        print('周末不计算') 
def culu_all_alpha_to_excel():
    '''
    计算全部的alpha alpha1到alpha191
    保持到本地excel
    '''
    stock=sg.popup_get_text('输入股票代码比如sh600111')
    start_date=sg.popup_get_text('输入开始人气比如20210101')
    df=ak.stock_zh_a_daily(symbol=stock,start_date=start_date)
    #该名称
    loc=time.localtime()
    #周末不计算
    if loc.tm_wday<6:
        year=loc.tm_year
        mo=loc.tm_mon
        daily=loc.tm_mday
        if mo<=9:
            mo='0'+str(mo)
        if daily<=9:
            daily='0'+str(daily)
        date='{}-{}-{}'.format(year,mo,daily)
        df.rename(columns={'data':'data','open':'openPrice','close':'closePrice','low':'lowestPrice','high':'highestPrice','volume':'turnoverVol'},inplace=True)
        date_list=[]
        type_list=[]
        alpha_value_list=[]
        for i in range(1,192):
            if i<=9:
                i='00'+str(i)
            elif i<=99 and int(i)>9:
                i='0'+str(i)
            else:
                pass
            try:
                alpha_value=eval('alpha.alpha{}'.format(i))(data=df)
                date_list.append(date)
                type_list.append(i)
                alpha_value_list.append(alpha_value)
            except:
                print('计算失败')
        data=pd.DataFrame({'时间':date_list,'alpha':type_list,'值':alpha_value_list})
        data.to_excel(r'C:\Users\Administrator\Desktop\alpha因子\{}.xlsx'.format(stock))
        print(data)
#计算保持到csv
def culu_all_alpha_to_csv():
    '''
    计算全部的alpha alpha1到alpha191
    保持到本地csv
    '''
    stock=sg.popup_get_text('输入股票代码比如sh600111')
    start_date=sg.popup_get_text('输入开始人气比如20210101')
    df=ak.stock_zh_a_daily(symbol=stock,start_date=start_date)
    #该名称
    loc=time.localtime()
    #周末不计算
    if loc.tm_wday<6:
        year=loc.tm_year
        mo=loc.tm_mon
        daily=loc.tm_mday
        if mo<=9:
            mo='0'+str(mo)
        if daily<=9:
            daily='0'+str(daily)
        date='{}-{}-{}'.format(year,mo,daily)
        df.rename(columns={'data':'data','open':'openPrice','close':'closePrice','low':'lowestPrice','high':'highestPrice','volume':'turnoverVol'},inplace=True)
        date_list=[]
        type_list=[]
        alpha_value_list=[]
        for i in range(1,192):
            if i<=9:
                i='00'+str(i)
            elif i<=99 and int(i)>9:
                i='0'+str(i)
            else:
                pass
            try:
                alpha_value=eval('alpha.alpha{}'.format(i))(data=df)
                date_list.append(date)
                type_list.append(i)
                alpha_value_list.append(alpha_value)
            except:
                print('计算失败')
        data=pd.DataFrame({'时间':date_list,'alpha':type_list,'值':alpha_value_list})
        data.to_csv(r'C:\Users\Administrator\Desktop\alpha因子\{}.csv'.format(stock))
        print(data)
#滚动的alpha计算
def culu_roll_alpha():
    '''
    只需要输入股票代码
    滚动的alpha计算1到191
    i选择alpha及，比如1是alpha1
    '''
    stock=sg.popup_get_text('输入股票代码比如sh600111')
    start_date=sg.popup_get_text('输入开始人气比如20210101')
    i=int(sg.popup_get_text('选择alpha几，比如1'))
    import time
    loc=time.localtime()
    year=loc.tm_year
    mo=loc.tm_mon
    daily=loc.tm_mday
    if mo<=9:
        mo='0'+str(mo)
    if daily<=9:
        daily='0'+str(daily)
    end_date='{}{}{}'.format(year,mo,daily)
    list_date=pd.date_range(start=start_date,end=end_date)
    #获取数据
    df=ak.stock_zh_a_daily(symbol=stock,start_date=start_date)
    df.rename(columns={'date':'date','open':'openPrice','close':'closePrice','low':'lowestPrice','high':'highestPrice','volume':'turnoverVol'},inplace=True)
    df.index=pd.to_datetime(df['date'])
    result_list=[]
    lx_list=[]
    date_list=[]
    #进行滚动计算，自己也可用该
    if i<=9:
        i='00'+str(i)
    elif i<=99 and int(i)>9:
        i='0'+str(i)
    else:
        pass
    for m in list_date:
        df1=df[start_date:m]
        try:
            result=eval('alpha.alpha{}'.format(i))(data=df1)
            result_list.append(result)
            lx_list.append(i)
            date_list.append(m)
        except:
            print('计算失败')
    data=pd.DataFrame({'时间':date_list,'值':result_list,'alpha类型':lx_list})
    print(data)
    data.to_excel(r'C:\Users\Administrator\Desktop\alpha因子\滚动{}alpha_{}.xlsx'.format(stock,i))
    return data,df
def plot_alpha():
    '''
    '''
    df,stock=culu_roll_alpha()
    plt.subplot(212)
    plt.title('alpha绘制')
    plt.plot(df['时间'],df['值'],label='alpha历史滚动',color='m')
    plt.grid()
    plt.subplot(211)
    plt.plot(stock['date'],stock['closePrice'],label='收盘价走势',color='g')
    plt.title('收盘价')
    plt.xlabel('时间')
    plt.ylabel('值')
    plt.legend()
    plt.grid()
    plt.show()

tkinter按键功能绑定：

button1=tk.Button(root,text='计算当日全部的量化因子alpha，1到200因子保持到数据库',command=culu_all_alpha_to_sql,fg='red',font=18)
button2=tk.Button(root,text='计算当日全部的量化因子alpha，1到200因子保持到excel表',command=culu_all_alpha_to_excel,fg='red',font=18)
button3=tk.Button(root,text='计算当日全部的量化因子alpha，1到200因子保持到csv表',command=culu_all_alpha_to_csv,fg='red',font=18)
button4=tk.Button(root,text='计算历史滚动量化因子alpha，1到200因子保持到excel表',command=culu_roll_alpha,fg='red',font=18)
button5=tk.Button(root,text='alpha历史滚动图绘制',command=plot_alpha,fg='red',font=18)
button1.pack()
button2.pack()
button3.pack()
button4.pack()
button5.pack()
root.mainloop()