def get_benchmark_values(self, dates):
# 不管几点，要对应整点的的日级数据
# start = str_to_timestamp(str((str_to_datetime(dates[0]) - datetime.timedelta(days=self.refresh_rate)).date()))
start = str2timestamp(
str((str2datetime(dates[0]) - datetime.timedelta(days=1)).date()))
end = str2timestamp(str((str2datetime(dates[-1])).date()))
bm_values = self.benchmark.loc[(self.benchmark["timestamp"] >= start)
& (self.benchmark["timestamp"] <= end)]
# bm_values = bm_values.loc[bm_values.index[::self.refresh_rate]]['close'].tolist()
bm_values = bm_values['close'].tolist()
return bm_values
def get_daily_ohlcv(self, k_lines_key, start, end, attributes):
"""
:param k_lines_key: 'spot-binance-btcusdt'
:param start_date: datetime
:param end_date: datetime
:return: dataframe
"""
start_ts = str2timestamp(str(start.date()))
end_ts = str2timestamp(str(end.date()))
total_data = self.data[k_lines_key]
data = total_data.loc[(total_data["timestamp"] >= start_ts) & (total_data["timestamp"] <= end_ts)][attributes]
return data
def __init__(self,
start_date=None,
end_date=None,
frequency=None,
refresh_rate=None,
trigger_time=None):
"""
:param start_date: 初始日期
:param end_date: 结束日期
"""
self._str_date = start_date + ' ' + trigger_time[
0] if trigger_time else start_date
self._current_date = str2datetime(self._str_date) # 当前日期 datetime
self._previous_date = None
self._current_timestamp = None # 当前日期 时间戳
self._end_timestamp = str2timestamp(end_date) # 结束日期 时间戳
self._bars = 0
self._bars_m = 0 # 开始bars数量
self._bars_start = 0
self._day_bar = 0
self._run_start = time.time() # 记录run运行时间
self._datestart = time.time()
self._run_end = None
self._frequency = frequency
self._refresh_rate = refresh_rate
async def _handle_data(self):
# print("******************************************************************")
clock = self.context.clock
current_date = clock.current_date
logger.current_date = current_date
current_timestamp = clock.current_timestamp
# print(current_date)
prebars=clock.pre_bar
pre_start = str(str2datetime(self.start) - datetime.timedelta(days=prebars))
try:
if not self.cache_data:
self.cache_data = self.context.prepare_data(self.universe, self.all_assets, self.benchmark,
self.frequency, pre_start, self.end, self.timezone)
except Exception:
output({"display_type": "error",
"error_msg": traceback.format_exc()})
return 1
# 记录初始持仓
start = self.start + ' ' + self.trigger_time[0] if self.trigger_time else self.start # 只支持一个trigger_time
if current_timestamp == str2timestamp(start):
for name, account in self.portfolio.accounts.items():
for asset, position in account.current_position.items():
position.context = self.context
init_portfolio_position = dict()
for asset in self.context.asset_varieties:
init_pp_detail = PortfolioPosition(self.context, asset, self.portfolio.accounts).detail()
init_portfolio_position[asset] = init_pp_detail
self.context.init_portfolio_position = init_portfolio_position
self.context.init_position_total = sum([asset['total_amount'] for asset in init_portfolio_position.values()])
self.context.init_total_account_position = {}
for name in self.context.accounts_name:
name_position = "{}_position".format(name)
total_amount = 0
for asset,value in self.context.init_portfolio_position.items():
if name in value['consist_of'].keys():
total_amount += value['consist_of'][name]['amount']
self.context.init_total_account_position[name_position] = total_amount
# logger.info('【记录初始持仓时间】：{} s'.format(str(time.time() - start2)[:5]))
try:
if str(current_date) in self.strategy_dates:
self.handle_data(self.context)
except Exception:
output({"display_type": "error",
"error_msg": traceback.format_exc()})
return 1
self.portfolio.record_history()
def get_price(self, symbol):
"""
:param symbol: "BTC/USDT.binance"
:return: 回测：上一bar close_price
"""
k_lines_key = symbol.split('.')[1] + '-spot-' + symbol.split(
'.')[0].replace('/', '').lower()
date = self.clock.current_date
last_bar_timestamp = str2timestamp(str(date.date())) # date都取日级数据
df = self.cacher.data[k_lines_key]
last_bar_price = df.loc[(
df['timestamp'] == last_bar_timestamp)]['close'].tolist()[0]
return last_bar_price
def value(self):
"""
:return: 持仓市值（随市场价实时变动）
"""
if not self._context:
return 0
else:
date = self._context.clock.current_date
current_timestamp = str2timestamp(str(
date.date())) # 只关注date() time()舍掉
# current_timestamp = datetime.datetime.timestamp(date)
cmc_key = 'cmc-spot-' + self.asset + 'usd'
df = self.context.cacher.data[cmc_key]
return df.loc[(
df['timestamp'] == current_timestamp)]['close'].tolist()[0]
def next(self):
if self._frequency in ['d', '1d', 'day', 'daily']:
# self._current_date += datetime.timedelta(days=self._refresh_rate)
self._current_date += datetime.timedelta(days=self._refresh_rate)
elif self._frequency in ['m', '1m', 'min', 'minute']:
self._current_date += datetime.timedelta(
minutes=self._refresh_rate)
elif self._frequency in ['5m', '5min', '5minutes']:
self._current_date += datetime.timedelta(minutes=5 *
self._refresh_rate)
current_timestamp = str2timestamp(str(
self._current_date.date())) # 只关注date() time()舍掉
current_timestamp = str(
datetime.datetime.fromtimestamp(current_timestamp))
if str(self._current_date) == current_timestamp:
self._day_bar += 1
self._bars += 1
self._bars_m += 1
self._bars_start += 1
