if not 'couts' in top_all.columns.values:
top_all['couts'] = 0
top_all['prev_p'] = 0
# for symbol in top_now.index:
# if 'couts' in top_now.columns.values:
# top_all.loc[symbol, ct.columns_now] = top_now.loc[symbol, ct.columns_now]
# else:
# # top_now.loc[symbol, 'dff'] = round(
# # ((float(top_now.loc[symbol, 'buy']) - float(
# # top_all.loc[symbol, 'lastp'])) / float(top_all.loc[symbol, 'lastp']) * 100),
# # 1)
# top_all.loc[symbol, ct.columns_now] = top_now.loc[symbol, ct.columns_now]
top_all = cct.combine_dataFrame(top_all, top_now, col=None)
top_dif = top_all.copy()
market_sort_value, market_sort_value_key = ct.get_market_sort_value_key(st_key_sort, top_all=top_all)
log.debug('top_dif:%s' % (len(top_dif)))
if 'trade' in top_dif.columns:
top_dif['buy'] = (
map(lambda x, y: y if int(x) == 0 else x, top_dif['buy'].values, top_dif['trade'].values))
# log.debug('top_dif:%s'%(len(top_dif)))
if ct.checkfilter and cct.get_now_time_int() > 915 and cct.get_now_time_int() < ct.checkfilter_end_timeDu:
top_dif = top_dif[top_dif.low > top_dif.llow * ct.changeRatio]
# top_dif = top_dif[top_dif.buy >= top_dif.lhigh * ct.changeRatio]
log.debug('top_dif:%s' % (len(top_dif)))
if cct.get_now_time_int() > 915:
top_dif = top_dif[top_dif.buy > 0]
if cct.get_today_duration(du_date) <= 3:
duration_date = 5
print("duaration: %s duration_date:%s" %
(cct.get_today_duration(du_date), duration_date))
log.info("duaration: %s duration_date:%s" %
(cct.get_today_duration(du_date), duration_date))
set_duration_console(du_date)
# all_diffpath = tdd.get_tdx_dir_blocknew() + '062.blk'
parser = cct.MoniterArgmain()
parserDuraton = cct.DurationArgmain()
# market_sort_value, market_sort_value_key = ct.get_market_sort_value_key('x1 d f')
# market_sort_value, market_sort_value_key = ct.get_market_sort_value_key('3 2')
# market_sort_value, market_sort_value_key = ct.get_market_sort_value_key('1')
# st_key_sort = '2'
st_key_sort = ct.sort_value_key_perd23
market_sort_value, market_sort_value_key = ct.get_market_sort_value_key(
ct.sort_value_key_perd23)
st = None
top_list = []
while 1:
try:
# df = sina_data.Sina().all
time_Rt = time.time()
if st is None:
st_key_sort = '%s %s' % (st_key_sort.split()[0],
cct.get_index_fibl())
# top_now = tdd.getSinaAlldf(market='060.blk', vol=ct.json_countVol, vtype=ct.json_countType)
# market_blk = '次新股'
market_blk = 'all'
# market_blk = 'cyb'
# market_blk = '060'
