def _get_bar_from_dataframe(symbol, time_frame, data):
bar = Bar(symbol)
bar.time_frame = time_frame
for field in ['open', 'high', 'low', 'close', 'volume']:
setattr(bar, field, data[field])
bar.timestamp = get_datetime(data.name).timestamp()
return bar
def _get_bar_from_dict(symbol, time_frame, data):
bar = Bar(symbol)
bar.time_frame = time_frame
for field in ['open', 'high', 'low', 'close', 'volume']:
setattr(bar, field, data[field])
bar.timestamp = data['ctime']
return bar
def _get_bar_from_dict(symbol, time_frame, data):
bar = Bar(symbol)
bar.time_frame = time_frame
for field in ['open', 'high', 'low', 'close', 'volume']:
setattr(bar, field, data[field])
bar.timestamp = data['ctime']
return bar
def _get_bar_from_dataframe(symbol, time_frame, data):
bar = Bar(symbol)
bar.time_frame = time_frame
for field in ['open', 'high', 'low', 'close', 'volume']:
setattr(bar, field, data[field])
bar.timestamp = get_datetime(data.name).timestamp()
return bar
def product(self):
"""
从数据库中取出数据
"""
conn = MySql().get_connection() # 得到连接
# 构造查询条件
query_params = " where ctime >= '%s'" % (self.__start_time,)
query_params += " and ctime < '%s'" % (self.__end_time,)
coll = "%s_%s" % (self.__symbol, self.__config.time_frame)
cur = conn.cursor(pymysql.cursors.DictCursor)
cur.execute("select * from %s " % coll + query_params + " limit %d " % self.__maxsize)
# print(cur.fetchall())
for row in cur.fetchall():
bar = Bar(self.__symbol)
bar.close = row["close"]
bar.timestamp = int(row["ctime"])
bar.high = row["high"]
bar.low = row["low"]
bar.open = row["open"]
bar.volume = row["volume"]
bar.time_frame = self.__config.time_frame
self.__dq.put(bar)
self.__start_time = bar.timestamp + tf2s(self.__config.time_frame)
cur.close()
# 如果开始时间距结束时间的距离不超过当前时间尺度,证明数据查询完成
if (cur.rownumber == 0) or self.__end_time - self.__start_time <= tf2s(self.__config.time_frame):
self._finished = True
def dict_to_bar(dict_):
dict_['time_frame'] = dict_.pop('timeFrame')
dict_['time'] = dict_.pop('ctime')
bar = Bar(dict_['symbol'])
for field in ['open', 'high', 'low', 'close', 'time_frame', 'volume']:
setattr(bar, field, dict_[field])
return bar
def __init__(self,
quotes,
deals,
positions,
symbols_pool,
currency_symbol='$',
capital_base=100000,
period=86400,
num=20,
**config): # 1day = 86400seconds
super(StrategyPerformanceManagerOffline,
self).__init__(deals,
positions,
currency_symbol=currency_symbol,
capital_base=capital_base)
self._symbols_pool = symbols_pool
self._config = config
if quotes is not None:
self._quotes_raw = quotes
else:
self._quotes_raw = pd.DataFrame(columns=Bar.get_keys())
self._num = num
self._period = period
self._rate_of_return_raw
self._quotes_raw = None # 计算完毕折后就可以释放资源了
def product(self):
"""
从数据库中取出数据
"""
try:
conn = MySql().get_connection() # 得到连接
# 构造查询条件
query_params = " where ctime >= '%s'" % (self.__start_time, )
query_params += " and ctime < '%s'" % (self.__end_time, )
coll = "%s_%s" % (self.__symbol, self.config.time_frame)
cur = conn.cursor(pymysql.cursors.DictCursor)
cur.execute("select * from %s " % coll + query_params +
" limit %d " % self.__maxsize)
# print(cur.fetchall())
for row in cur.fetchall():
bar = Bar(self.__symbol)
bar.close = row["close"]
bar.timestamp = int(row["ctime"])
bar.high = row["high"]
bar.low = row["low"]
bar.open = row["open"]
bar.volume = row["volume"]
# volume maybe None in mysql
if bar.volume is None:
bar.volume = 0
bar.time_frame = self.config.time_frame
self.__dq.put(bar)
self.__start_time = bar.timestamp + tf2s(
self.config.time_frame)
cur.close()
# 如果开始时间距结束时间的距离不超过当前时间尺度,证明数据查询完成
if (cur.rownumber
== 0) or self.__end_time - self.__start_time <= tf2s(
self.config.time_frame):
self.stop()
except:
self.logger.error('\n' + traceback.format_exc())
self.stop()
def __init__(self, quotes, deals, positions, symbols_pool, currency_symbol='$', capital_base=100000, period=86400,
num=20, **config): # 1day = 86400seconds
super(StrategyPerformanceManagerOffline, self).__init__(deals, positions,
currency_symbol=currency_symbol,
capital_base=capital_base)
self._symbols_pool = symbols_pool
self._config = config
if quotes is not None:
self._quotes_raw = quotes
else:
self._quotes_raw = pd.DataFrame(columns=Bar.get_keys())
self._num = num
self._period = period
self._rate_of_return_raw
self._quotes_raw = None # 计算完毕折后就可以释放资源了
def on_tick(self, event: Event):
if self._running:
tick = event.content['data']
symbol = tick.symbol
for time_frame in {item[1] for item in self._data_view.get_keys() if item[0] == symbol}:
bar_interval = tf2s(time_frame)
if symbol not in self._tick_cache:
self._tick_cache[symbol] = {}
if time_frame not in self._tick_cache[symbol]:
self._tick_cache[symbol][time_frame] = {
'open': tick.openPrice, 'high': tick.highPrice,
'low': tick.lastPrice, 'close': tick.lastPrice,
'volume': tick.volume, 'timestamp': tick.time // self.TICK_INTERVAL * self.TICK_INTERVAL,
}
else:
dict_ = self._tick_cache[symbol][time_frame]
if tick.time - dict_['timestamp'] >= self.TICK_INTERVAL: # bar_interval 能被TICK_INTERVAL整除
bar = Bar(symbol)
bar.time_frame = time_frame
bar.timestamp = dict_['timestamp'] // bar_interval * bar_interval
bar.open = dict_['open']
bar.high = dict_['high']
bar.low = dict_['low']
bar.close = dict_['close']
self.update_bar(bar)
dict_["open"] = tick.openPrice
dict_["high"] = tick.highPrice
dict_["low"] = tick.lowPrice
dict_["close"] = tick.lastPrice
dict_["volume"] = tick.volume
dict_["timestamp"] = tick.time // self.TICK_INTERVAL * self.TICK_INTERVAL
else:
dict_['low'] = min(dict_['low'], tick.lowPrice)
dict_['high'] = max(dict_['high'], tick.highPrice)
dict_['close'] = tick.lastPrice
dict_["volume"] += tick.volume
dict_['timestamp'] = tick.time // self.TICK_INTERVAL * self.TICK_INTERVAL
