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:
