def loadData(self, dbName):
"""加载数据"""
for vtSymbol in self.vtSymbolList:
df = get_stk_hfq(dss, vtSymbol)
df = df.sort_values(['date'])
for i, d in df.iterrows():
#print(d)
#set_trace()
bar = VtBarData()
bar.vtSymbol = vtSymbol
bar.symbol = vtSymbol
bar.open = float(d['open'])
bar.high = float(d['high'])
bar.low = float(d['low'])
bar.close = float(d['close'])
date = d['date'].split('-')
date = ''.join(date)
bar.date = date
bar.time = '00:00:00'
bar.datetime = datetime.strptime(bar.date + ' ' + bar.time,
'%Y%m%d %H:%M:%S')
bar.volume = d['volume']
barDict = self.dataDict.setdefault(bar.datetime, OrderedDict())
barDict[bar.vtSymbol] = bar
self.output(u'全部数据加载完成')
def signal_k_pattern(dss, codes, _date):
r = []
for code in codes:
df = get_stk_hfq(dss, code, None, _date)
item_list = k_pattern(df)
r += [x + code for x in item_list]
return r
def _bc_loadInitBar(self, vtSymbol, initBars):
"""读取Bar数据，"""
r = []
#df = get_stk_hfq(self.dss, vtSymbol, begin_date=None, end_date='2019-07-18')
df = get_stk_hfq(self.dss, vtSymbol, begin_date=None, end_date=None)
if df is not None:
df = df.iloc[:initBars]
df = df.sort_values('date')
for i, row in df.iterrows():
d = dict(row)
#print(d)
bar = VtBarData()
bar.vtSymbol = vtSymbol
bar.symbol = vtSymbol
bar.open = float(d['open'])
bar.high = float(d['high'])
bar.low = float(d['low'])
bar.close = float(d['close'])
date = d['date'].split('-') #去掉字符串中间的'-'
date = ''.join(date)
bar.date = date
bar.time = '00:00:00'
bar.datetime = datetime.strptime(bar.date + ' ' + bar.time,
'%Y%m%d %H:%M:%S')
bar.volume = float(d['volume'])
r.append(bar)
return r
def hit_ma(dss,date):
r = []
codes = get_stk_codes(dss)
for code in codes:
df = get_stk_hfq(dss,code,'2018-01-08')
if df is None:
continue
df1 = df[df.date==date]
if df1.empty:
continue
df = df[df.date<=date]
df = df.sort_values(by=['date'])
if len(df) < 60: # 新股，数据长度不够
continue
df['10d'] = df['close'].rolling(10).mean()
#df['20d'] = df['close'].rolling(20).mean()
df['30d'] = df['close'].rolling(30).mean()
df['60d'] = df['close'].rolling(60).mean()
df = df.loc[:,['date','close','10d','30d','60d']]
df = df.sort_values(by=['date'], ascending=False)
#print(df.head())
# 10日线高于30日线，30日线高于60日线
# 长均线已转向上趋势
if df.iat[0,1] > df.iat[0,2] and df.iat[0,2] > df.iat[0,3] and df.iat[0,3] > df.iat[0,4]:
if df.iat[0,4] > df.iat[3,4]:
#if df.iat[5,4] > df.iat[5,3] :
r.append(code)
return r
def be_bottom(code, day):
df = get_stk_hfq(get_dss(), code, end_date=day)
if df is None:
return False
if len(df) <= 360:
return False
df30 = df.loc[:30]
df360 = df.loc[:360]
if df30.low.min() <= df360.low.min():
return True
else:
return False
def signal_k_pattern(dss, codes, begin_date, end_date):
r = []
for code in codes:
df = get_stk_hfq(dss, code, None, end_date)
if df is not None:
dates = list(df['date'])
#print(dates)
for date in dates:
if date >= begin_date:
df1 = df[df.date <= date]
if k_pattern(df1):
expire_date = (datetime.now() +
timedelta(days=3)).strftime('%Y-%m-%d')
r.append([date, code, 'up_overlap_up', expire_date])
else:
break
#print(r)
return r
def init_signal_macd(dss, codes):
df_signal = pd.DataFrame(
columns=['code', 'date', 'close', 'MACD', 'DIFF', 'DEA'])
for code in codes:
df1 = df_signal[df_signal.code == code]
if len(df1) == 0:
df1 = get_stk_hfq(dss, code)
df1 = df1[['date', 'close']]
df1 = df1.sort_values(by='date')
#print(df1)
if len(df1) >= 30:
df1 = MACD(df1)
#print(df1)
df1['code'] = code
df_signal = df_signal.append(df1, sort=False)
#print(df_signal)
#ipdb.set_trace()
return df_signal