def __init__(self,
user="******",
password="******",
zuhe="ZH1008383"):
self.user = easytrader.use('xq')
self.user.prepare(user=user, password=password, portfolio_code=zuhe)
self.buylist = []
self.selllist = []
self.limitnum = 20
self.m = MongoDB()
def __init__(self, startdate=(2011, 1, 1), enddate=[]):
self.startdate = datetime.datetime(*startdate, 0, 0, 0, 0)
self.enddate = enddate
self.m = MongoDB(DB_SERVER, DB_PORT, USER, PWD, AUTHDBNAME)
self.formatlist = [
"date", "volume", "close", "high", "low", "open", "pre_close"
]
self.savevols = [
"stock", "buy_date", "sell_date", "holddays", "profit", "features"
]
self.looplist = []
self.trading_records = []
self.holding_records = []
self.datalst = []
self.collection = None
self.tempstatus = []
self.lateststatus = []
def connetdb(self):
self.m = MongoDB(DB_SERVER, DB_PORT, USER, PWD, AUTHDBNAME)
return self.m
def __init__(self, stock="600455.SH"):
self.m = MongoDB(DB_SERVER, DB_PORT, USER, PWD, AUTHDBNAME)
def __init__(self):
self.db = MongoDB(DB_SERVER, DB_PORT, USER, PWD, AUTHDBNAME)
self.looplist = []
def __init__(self):
self.m = MongoDB(DB_SERVER, DB_PORT, USER, PWD, AUTHDBNAME)
self.formatlist = [
"date", "volume", "close", "high", "low", "open", "pre_close"
]
return
def __init__(self, stock="600455.SH"):
self.m = MongoDB()
c_preclose = line[6]
if c_preclose != close:
reh = [[i[0], i[1] * c_preclose / close] for i in reh]
reh.append([c, c_preclose / close])
close = line[2]
c += 1
result = []
sc = 0
ec = 0
for idx in range(len(reh)):
weight = reh[idx][1]
ec = reh[idx][0]
piece = self.recount(lst, sc, ec, weight)
result.extend(piece)
sc = ec
result.extend(lst[sc:])
return result
def recount(self, lst, sc, ec, weight):
rst = []
for line in lst[sc:ec]:
rst.append([line[0], line[1], *[i * weight for i in line[2:]]])
return rst
if __name__ == '__main__':
db = MongoDB(DB_SERVER, DB_PORT, USER, PWD, AUTHDBNAME)
s = StockIndicator(mdb=db)
s.setlooplist()
s.updateallstocks2db()
def import_data(self,stock, start, end ):
query = MongoDB()
df = query.format2dataframe(query.read_data("ml_fund_table",stock))
df['change'] = (df['close'] - df['close'].shift(1))/df['close'].shift(1)
df['code'] = stock
return df
