Beispiel #1
0
 def get_inf(self):
     self.stock_symbol = self.symbol.get()
     self.target_date_db = self.date1.get() + '-' + self.date2.get(
     ) + '-' + self.date3.get()
     self.num_stock = 'all'  #########################################
     stockh = Stockholm(self)
     inf_dict = stockh.select_mongo(self.stock_symbol, self.target_date_db)
     if (inf_dict == 0):
         self.open_v.set("")
         self.close_v.set("")
         self.high_v.set("")
         self.low_v.set("")
         self.change_v.set("")
         self.volume_v.set("")
         self.vol_change_v.set("")
         self.Turnover_v.set("")
         self.TurnoverRate_v.set("")
         self.Chg_v.set("")
         self.KDJ_K_v.set("")
         self.KDJ_D_v.set("")
         self.KDJ_J_v.set("")
     else:
         self.open_v.set(inf_dict['Open'])
         self.close_v.set(inf_dict['Close'])
         self.high_v.set(inf_dict['High'])
         self.low_v.set(inf_dict['Low'])
         self.change_v.set(inf_dict['Change'])
         self.volume_v.set(inf_dict['Volume'])
         self.vol_change_v.set(inf_dict['Vol_Change'])
         self.Turnover_v.set(inf_dict['Turnover'])
         self.TurnoverRate_v.set(inf_dict['TurnoverRate'])
         self.Chg_v.set(inf_dict['Chg'])
         self.KDJ_K_v.set(inf_dict['KDJ_K'])
         self.KDJ_D_v.set(inf_dict['KDJ_D'])
         self.KDJ_J_v.set(inf_dict['KDJ_J'])
Beispiel #2
0
    def get_stockholm_run1(self):
        self.store_path = self.store_pathv.get()
        if (self.v_num.get() == 1):
            self.num_stock = 'all'
        else:
            self.num_stock = self.num.get()

        if (self.v.get() == 1):
            self.output_type = 'json'
        elif (self.v.get() == 2):
            self.output_type = 'csv'
        else:
            self.output_type = 'all'

        if (self.v2.get() == 1):
            self.charset = 'utf-8'
        else:
            self.charset = 'gbk'
        self.start_date = self.start_date1.get() + self.start_date2.get(
        ) + self.start_date3.get()
        self.end_date = self.end_date1.get() + self.end_date2.get(
        ) + self.end_date3.get()
        self.export_file_name = self.export_en.get()
        self.stock_en.set('正在获取数据')
        stockh = Stockholm(self)
        stockh.run1()
        self.stock_en.set('获取数据完成')
Beispiel #3
0
 def get_stockholm_run2(self):
     self.target_date = self.target_date1.get() + self.target_date2.get(
     ) + self.target_date3.get()
     self.test_date_range = int(self.target_length.get())
     self.pick_en.set('正在获取选股结果')
     stockh = Stockholm(self)
     stockh.run2()
     self.pick_en.set('获取选股结果完成')
Beispiel #4
0
def main():
    args = option.parser.parse_args()
    if not checkFoldPermission(args.store_path):  #检测是否具有读写存储文件的权限
        print(u'\n没有文件读写权限: %s' % args.store_path)
    else:
        print(u'股票数据爬虫和预测启动...\n')
        stockh = Stockholm(args)  #初始化参数
        stockh.runmin()  #启动
Beispiel #5
0
def main():
    args = option.parser.parse_args()
    if not checkFoldPermission(args.store_path):
        print('\nPermission denied: %s' % args.store_path)
        print('Please make sure you have the permission to save the data!\n')
    else:
        print('Stockholm is starting...\n')
        stockh = Stockholm(args)
        stockh.run()
        print('Stockholm is done...\n')
Beispiel #6
0
def main():
    args = option.parser.parse_args()
    if not checkFoldPermission(args.store_path):
        print('\nPermission denied: %s' % args.store_path)
        print('Please make sure you have the permission to save the data!\n')
    else:
        print('Stockholm is starting...\n')
        stockh = Stockholm(args)
        stockh.run()
        print('Stockholm is done...\n')
Beispiel #7
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 def get_learning_test(self):
     if (self.store_path == 'USER_HOME/tmp/stockholm_export'):
         self.export_folder = os.path.expanduser(
             '~') + '/tmp/stockholm_export'
     else:
         self.export_folder = self.store_path
     self.learning_date = self.learning_date1.get(
     ) + self.learning_date2.get() + self.learning_date3.get()
     self.num_stock = self.learning_symbol.get()
     #print(self.num_stock)
     self.export_file_name = 'learning1'
     self.start_date = '20110101'
     self.end_date = self.learning_date
     stockh = Stockholm(self)
     stockh.run1()
     self.export_file_name = 'learning2'
     ld = datetime.datetime(int(self.learning_date1.get()),
                            int(self.learning_date2.get()),
                            int(self.learning_date3.get()))
     self.start_date = (ld + datetime.timedelta(days=1)).strftime("%Y%m%d")
     self.end_date = get_date_str(None)
     stockh2 = Stockholm(self)
     stockh2.run1()
     self.variance = learningtest.stock_predection_test(
         self.export_folder + '/' + "learning1.csv",
         self.export_folder + '/' + "learning2.csv", 60)
Beispiel #8
0
 def get_plot(self):
     self.stock_symbol = self.symbol.get()
     self.end_date_db = self.end_date1_db.get(
     ) + '-' + self.end_date2_db.get() + '-' + self.end_date3_db.get()
     self.num_stock = 'all'  ######################################
     if (self.pic_v.get() == 1):
         self.pic_name = 'KDJ_K'
     elif (self.pic_v.get() == 2):
         self.pic_name = 'KDJ_D'
     elif (self.pic_v.get() == 3):
         self.pic_name = 'KDJ_J'
     else:
         self.pic_name = 'Close'
     stockh = Stockholm(self)
     stockh.draw_choice(self.num_stock, self.pic_name, self.end_date_db)
Beispiel #9
0
 def get_learning(self):
     if (self.store_path == 'USER_HOME/tmp/stockholm_export'):
         self.export_folder = os.path.expanduser(
             '~') + '/tmp/stockholm_export'
     else:
         self.export_folder = self.store_path
     self.learning_date = self.learning_date1.get(
     ) + self.learning_date2.get() + self.learning_date3.get()
     self.num_stock = self.learning_symbol.get()
     #print(self.num_stock)
     self.export_file_name = 'learning'
     self.start_date = '20120101'
     self.end_date = get_date_str(None)
     stockh3 = Stockholm(self)
     stockh3.run1()
     self.predicted_price = learning.stock_predection(self.export_folder +
                                                      '/' + "learning.csv")