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'