def __init__(self, dbinfo=ct.DB_INFO, redis_host=None):
self.dbinfo = dbinfo
self.logger = getLogger(__name__)
self.index_objs = dict()
self.stock_objs = dict()
self.updating_date = None
self.combination_objs = dict()
self.cal_client = CCalendar(dbinfo, redis_host)
self.index_info_client = IndexInfo()
self.cvaluation_client = CValuation()
self.reviewer = CReivew(dbinfo, redis_host)
self.comb_info_client = CombinationInfo(dbinfo, redis_host)
self.stock_info_client = CStockInfo(dbinfo, redis_host)
self.rindex_stock_data_client = RIndexStock(dbinfo, redis_host)
self.industry_info_client = IndustryInfo(dbinfo, redis_host)
self.rindustry_info_client = RIndexIndustryInfo(dbinfo, redis_host)
self.animation_client = CAnimation(dbinfo, redis_host)
self.subscriber = Subscriber()
self.quote_handler = StockQuoteHandler()
self.ticker_handler = TickerHandler()
self.connect_client = StockConnect(market_from=ct.SH_MARKET_SYMBOL,
market_to=ct.HK_MARKET_SYMBOL,
dbinfo=dbinfo,
redis_host=redis_host)
self.margin_client = Margin(dbinfo=dbinfo, redis_host=redis_host)
self.emotion_client = Emotion(dbinfo=dbinfo, redis_host=redis_host)
self.sh_exchange_client = StockExchange(ct.SH_MARKET_SYMBOL)
self.sz_exchange_client = StockExchange(ct.SZ_MARKET_SYMBOL)
import sys
from os.path import abspath, dirname
sys.path.insert(0, dirname(dirname(dirname(abspath(__file__)))))
import traceback
import const as ct
import pandas as pd
from rstock import RIndexStock
from cstock_info import CStockInfo
from industry_info import IndustryInfo
if __name__ == '__main__':
try:
mdate = '2019-08-02'
cobj = CStockInfo()
robj = RIndexStock()
iobj = IndustryInfo()
black_list = list(ct.BLACK_DICT.keys())
bdf = cobj.get()
stock_info = robj.get_data(mdate)
idf = iobj.get_csi_industry_data(mdate)
df = pd.merge(bdf, idf, how='left', on=['code'])
df = pd.merge(stock_info, df, how='inner', on=['code'])
df = df[~df.code.isin(black_list)]
df = df[(df.profit > 1) & (df.profit < 3) & (df.pday > 30) &
(df.timeToMarket < 20150101)]
df = df.reset_index(drop=True)
#df = df[['code', 'name', 'industry', 'profit', 'pday', 'pind_name', 'sind_name', 'tind_name', 'find_name']]
df = df[['code', 'name', 'profit', 'pday', 'find_name']]
for name, contains in df.groupby('find_name'):
if len(contains) > 2: