print ("A:%s N:%s K:%s %s G:%s" % (
df_count, now_count, len(top_all[top_all['buy'] > 0]),
len(top_now[top_now['volume'] <= 0]), len(top_dif))),
# print "Rt:%0.3f" % (float(time.time() - time_Rt))
print "Rt:%0.1f dT:%s" % (float(time.time() - time_Rt),cct.get_time_to_date(time_s))
if 'counts' in top_dif.columns.values:
top_dif = top_dif.sort_values(by=['diff', 'volume', 'percent', 'counts', 'ratio'],
ascending=[0, 0, 0, 1, 1])
else:
# print "Good Morning!!!"
top_dif = top_dif.sort_values(by=['diff', 'percent', 'ratio'], ascending=[0, 0, 1])
# top_all=top_all.sort_values(by=['percent','diff','counts','ratio'],ascending=[0,0,1,1])
# print rl.format_for_print(top_dif[:10])
print rl.format_for_print(top_dif[:10])
# print top_all.loc['000025',:]
# print "staus",status
if status:
for code in top_dif[: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:
# print "\t No RealTime Data"
else:
print "\tNo Data"
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 = pd.concat([top_temp[:10], top_end], axis=0)
top_dd = top_dd.drop_duplicates()
top_dd = top_dd.loc[:, ct.Duration_format_buy]
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 = pd.concat([top_temp[:10], top_end], axis=0)
top_dd = top_dd.drop_duplicates()
top_dd = top_dd.loc[:, ct.Duration_format_trade]
print rl.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 rl.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:
# top_all = top_all[top_all.prev_p >= top_all.lhigh]
top_all = top_all.loc[
:, ["name", "percent", "diff", "counts", "volume", "trade", "prev_p", "ratio"]
]
print "G:%s dt:%s" % (len(top_all), cct.get_time_to_date(time_s))
top_all = top_all.sort_values(by=["diff", "counts", "volume", "ratio"], ascending=[0, 0, 0, 1])
# top_all=top_all.sort_values(by=['percent','diff','counts','ratio'],ascending=[0,0,1,1])
# print top_all
# print pt.PrettyTable([''] + list(top_all.columns))
# print tbl.tabulate(top_all,headers='keys', tablefmt='psql')
# print tbl.tabulate(top_all,headers='keys', tablefmt='orgtbl')
# print rl.format_for_print(top_all)
# print top_all[:10]
print rl.format_for_print(top_all[:10])
# print "staus",status
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)
top_all = top_bak
del top_bak
gc.collect()
else:
print "no data"
int_time = cct.get_now_time_int()
if cct.get_work_time():
if duration_date > ct.duration_date_sort:
top_temp = top_temp.sort_values(
by=eval(market_sort_value),
ascending=market_sort_value_key)
else:
top_temp = top_temp.sort_values(
by=eval(market_sort_value),
ascending=market_sort_value_key)
# 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']) ]
# top_temp = top_temp.loc[:,ct.MonitorMarket_format_buy]
# else:
# # top_temp = top_temp[ (top_temp['ma5d'] > top_temp['ma10d']) & (top_temp['buy'] > top_temp['ma10d']) ]
# top_temp = top_temp.loc[:,ct.MonitorMarket_format_buy]
print rl.format_for_print(
top_temp.loc[:, ct.MonitorMarket_format_buy][:10])
# print rl.format_for_print(top_dif[:10])
# print top_all.loc['000025',:]
# print "staus",status
if status:
for code in top_dif[: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:
# print "\t No RealTime Data"
else:
top_dif = top_dif.sort_values(by=["diff", "percent", "ratio"], ascending=[1, 0, 1])
# top_all=top_all.sort_values(by=['percent','diff','counts','ratio'],ascending=[0,0,1,1])
# print rl.format_for_print(top_dif[:10])
# top_dd = pd.concat([top_dif[:5],top_temp[:3],top_dif[-3:],top_temp[-3:]], axis=0)
top_dd = pd.concat([top_dif[:10], top_dif[-5:]], axis=0)
if cct.get_now_time_int() < 930:
top_dd = top_dd.loc[
:, ["name", "buy", "diff", "volume", "percent", "ratio", "counts", "high", "lastp", "date"]
]
else:
top_dd = top_dd.loc[
:, ["name", "trade", "diff", "volume", "percent", "ratio", "counts", "high", "lastp", "date"]
]
print rl.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 rl.format_for_print(top_dif[-10:])
# print top_all.loc['000025',:]
# print "staus",status
if status:
for code in top_dif[: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:
# print "\t No RealTime Data"
# top_temp = top_temp.sort_values(by=['dff', 'op', 'ra', 'percent', 'ratio'],
# top_temp = top_temp.sort_values(by=ct.Monitor_sort_op,
# ascending=ct.Monitor_sort_op_key)
# top_temp = top_temp.sort_values(by=ct.Duration_percentdn_ra,
# ascending=ct.Duration_percentdn_ra_key)
# top_temp = top_temp.sort_values(by=ct.Duration_percent_op,
# ascending=ct.Duration_percent_op_key)
top_temp = top_temp.sort_values(
by=eval(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]
print rl.format_for_print(
top_temp.loc[:, ct.Monitor_format_trade][:10])
# print rl.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: