if cct.get_now_time_int() > 915 and cct.get_now_time_int() < 935: # top_temp = top_temp[ (top_temp['ma5d'] > top_temp['ma10d']) & (top_temp['buy'] > top_temp['ma10d']) ][:10] top_dd = cct.combine_dataFrame(top_temp[:10], top_end,append=True, clean=True) # top_dd = top_dd.drop_duplicates() ct_Duration_format_Values = ct.get_Duration_format_Values(ct.Duration_format_buy, market_sort_value[:]) top_dd = top_dd.loc[:, ct_Duration_format_Values] else: # top_temp = top_temp[ (top_temp['ma5d'] > top_temp['ma10d']) & (top_temp['trade'] > top_temp['ma10d']) ][:10] # top_temp = top_temp[top_temp['trade'] > top_temp['ma10d']] top_dd = cct.combine_dataFrame(top_temp[:10], top_end,append=True, clean=True) # top_dd = top_dd.drop_duplicates() ct_Duration_format_Values = ct.get_Duration_format_Values(ct.Duration_format_trade, market_sort_value[:]) top_dd = top_dd.loc[:, ct_Duration_format_Values] print cct.format_for_print(top_dd) # dfgui.show(top_dif) # if cct.get_now_time_int() < 930 or cct.get_now_time_int() > 1505 or (cct.get_now_time_int() > 1125 and cct.get_now_time_int() < 1505): # print cct.format_for_print(top_dif[-10:]) # print top_all.loc['000025',:] # print "staus",status if status: for code in top_dd[:10].index: code = re.findall('(\d+)', code) if len(code) > 0: code = code[0] kind = sl.get_multiday_ave_compare_silent(code) # print top_all[top_all.low.values==0] # else:
if 'nhigh' in top_all.columns: ct_Duration_format_Values = ct.get_Duration_format_Values( ct_Duration_format_Values, replace='df2', dest='nhigh') # ct_MonitorMarket_Values2 = ct.get_Duration_format_Values( # ct_MonitorMarket_Values2, replace='df2', dest='nhigh') else: ct_Duration_format_Values = ct.get_Duration_format_Values( ct_Duration_format_Values, replace='df2', dest='high') top_dd = top_dd.loc[:, ct_Duration_format_Values] # ct_Duration_format_Values = ct.get_Duration_format_Values(ct_Duration_format_Values,replace='op',dest='upper') # top_dd[col for col in top_dd.index if col in top_temp[:10].index] table,widths = cct.format_for_print(top_dd.loc[[col for col in top_dd[:9].index if col in top_temp[:10].index]],widths=True) print(table) # cct.counterCategory(top_temp) print(cct.format_for_print(top_dd[-4:],header=False,widths=widths)) # print cct.format_for_print(top_dd) # if cct.get_now_time_int() < 930 or cct.get_now_time_int() > 1505 or (cct.get_now_time_int() > 1125 and cct.get_now_time_int() < 1505): # print cct.format_for_print(top_dif[-10:]) # print top_all.loc['000025',:] # print "staus",status if status: for code in top_dd[:10].index: code = re.findall('(\d+)', code) if len(code) > 0: code = code[0] kind = sl.get_multiday_ave_compare_silent(code)
ct_Duration_format_Values, replace='df2', dest='nhigh') # ct_MonitorMarket_Values2 = ct.get_Duration_format_Values( # ct_MonitorMarket_Values2, replace='df2', dest='nhigh') else: ct_Duration_format_Values = ct.get_Duration_format_Values( ct_Duration_format_Values, replace='df2', dest='high') top_dd = top_dd.loc[:, ct_Duration_format_Values] # df[df.columns[(df.columns >= 'per1d') & (df.columns <= 'per9d')]][:100] # table,widths = cct.format_for_print(top_dd[:10],widths=True) table, widths = cct.format_for_print(top_dd.loc[[col for col in top_dd[:10].index if col in top_temp[:10].index]], widths=True) # pylint: disable=C0103,C0103,C0103,C0103,C0103,C0103,C0103,C0103,C0103,C0103,C0103,C0103,C0103,C0103,C0103,C0103,C0103,C0103 print table cct.counterCategory(top_temp) print cct.format_for_print(top_dd[-4:], header=False, widths=widths) # pylint: disable=C0326,C0326,C0326,C0326,C0326,C0326,C0326,C0326,C0326,C0326,C0326,C0326,C0326,C0326,C0326,C0326,C0326 # print (cct.format_for_print(top_dd)) # if cct.get_now_time_int() < 930 or cct.get_now_time_int() > 1505 or (cct.get_now_time_int() > 1125 and cct.get_now_time_int() < 1505): # print cct.format_for_print(top_dif[-10:]) # print top_all.loc['000025',:] # print "staus",status if status: for code in top_dd[:10].index: code = re.findall('(\d+)', code) if len(code) > 0: code = code[0]
# ascending=ct.Duration_percent_op_key) top_temp = top_temp.sort_values( by=(market_sort_value), ascending=market_sort_value_key) # top_temp = top_temp.sort_values(by=['op','ra','dff', 'percent', 'ratio'], ascending=[0,0,0, 0, 1]) # if cct.get_now_time_int() > 915 and cct.get_now_time_int() < 935: # top_temp = top_temp.loc[:,ct.Monitor_format_trade] # else: # top_temp = top_temp.loc[:,ct.Monitor_format_trade] if st_key_sort.split()[0] == 'x': top_temp = top_temp[top_temp.topR != 0] ct_MonitorMarket_Values = ct.get_Duration_format_Values( ct.Monitor_format_trade, market_sort_value[:2]) print cct.format_for_print( top_temp.loc[:, ct_MonitorMarket_Values][:10]) # print cct.format_for_print(top_all[:10]) if status: for code in top_all[:10].index: code = re.findall('(\d+)', code) if len(code) > 0: code = code[0] kind = sl.get_multiday_ave_compare_silent(code) else: # print top_now[:10] print "\tNo data" int_time = cct.get_now_time_int() if cct.get_work_time(): if int_time < 930: while 1:
if cct.get_now_time_int() > 915 and cct.get_now_time_int() < 935: # top_temp = top_temp[ (top_temp['ma5d'] > top_temp['ma10d']) & (top_temp['buy'] > top_temp['ma10d']) ][:10] top_dd = cct.combine_dataFrame(top_temp[:10], top_end,append=True, clean=True) # top_dd = top_dd.drop_duplicates() ct_Duration_format_Values = ct.get_Duration_format_Values(ct.Duration_format_buy, market_sort_value[:]) top_dd = top_dd.loc[:, ct_Duration_format_Values] else: # top_temp = top_temp[ (top_temp['ma5d'] > top_temp['ma10d']) & (top_temp['trade'] > top_temp['ma10d']) ][:10] # top_temp = top_temp[top_temp['trade'] > top_temp['ma10d']] top_dd = cct.combine_dataFrame(top_temp[:10], top_end,append=True, clean=True) # top_dd = top_dd.drop_duplicates() ct_Duration_format_Values = ct.get_Duration_format_Values(ct.Duration_format_trade, market_sort_value[:]) top_dd = top_dd.loc[:, ct_Duration_format_Values] print(cct.format_for_print(top_dd)) # dfgui.show(top_dif) # if cct.get_now_time_int() < 930 or cct.get_now_time_int() > 1505 or (cct.get_now_time_int() > 1125 and cct.get_now_time_int() < 1505): # print cct.format_for_print(top_dif[-10:]) # print top_all.loc['000025',:] # print "staus",status if status: for code in top_dd[:10].index: code = re.findall('(\d+)', code) if len(code) > 0: code = code[0] kind = sl.get_multiday_ave_compare_silent(code) # print top_all[top_all.low.values==0] # else: