def test(detail):
def get_first_n_lines(string, n):
lines = string.splitlines()
n = min(n, len(lines))
return '\n'.join(lines[:n])
#gc.set_debug(gc.DEBUG_UNCOLLECTABLE | gc.DEBUG_SAVEALL)
start_time = time.time()
with codecs.open('../test/testcode7.py', 'r', 'utf-8') as f:
code = f.read()
user = User('10032')
backtest = Backtesting(user, 'test', code, ['EURUSD'], 'M30', '2015-01-01', '2016-01-01')
print(backtest.progress)
for _ in range(4):
backtest.start()
print(backtest.get_performance().trade_summary)
if detail:
translator = DataframeTranslator()
user_dir = UserDirectory(user)
print(user_dir.get_sys_func_list())
print(backtest.get_profit_records()) # 获取浮动收益曲线
print(backtest.get_parameters()) # 获取策略中的参数（用于优化）
performance = backtest.get_performance() # 获取策略的各项指标
print('trade_info:\n%s' % performance._manager.trade_info)
print('trade_summary:\n%s' % performance.trade_summary)
print('trade_details:\n%s' % performance.trade_details)
print(translator.dumps(performance._manager.trade_info))
print(translator.dumps(performance.trade_details))
print('strategy_summary:\n%s' % performance.strategy_summary)
print('optimize_info:\n%s' % performance.optimize_info)
print('info_on_home_page\n%s' % performance.get_info_on_home_page())
print(performance.get_factor_list())
# print(performance.yield_curve)
print('ar:\n%s' % performance.ar) # 年化收益率
print('risk_free_rate:\n%s' % performance._manager.risk_free_rate) # 无风险收益率
print('volatility:\n%s' % performance.volatility) # 波动率
print('sharpe_ratio:\n%s' % performance.sharpe_ratio) # sharpe比率
print('max_drawdown:\n%s' % performance.max_drawdown) # 最大回测
print('trade_position\n%s' % performance.trade_positions) # 交易仓位
print(time.time() - start_time)
# print('output:\n%s' % get_first_n_lines(backtest.get_output(), 100))
print(time.time() - start_time)
print(backtest.progress)
paras = {'handle': {'times': {'start': 10, 'end': 10, 'step': 1}}}
optimize = backtest.optimize(paras, None, None)
print('optimize\n%s' % optimize)
print(time.time() - start_time)
del backtest
performance = None
optimize = None
class StrategyPerformanceJsonCache(RedisCacheWithExpire):
_cls = StrategyPerformance
_time_expire = 15 * 60
def __init__(self, user):
super().__init__(user)
self._translator = DataframeTranslator({
'height': 'auto',
'width': '98%',
'pageSize': 20,
'where': 'f_getWhere()'
})
def put_performance(self, performance):
for key, value in performance.__dict__.items():
cache_key = ':'.join([self._cls.__name__, key])
if isinstance(value, pd.DataFrame):
context = self._translator.dumps(value)
elif isinstance(value, pd.Series):
context = self._translator.dumps(pd.DataFrame(value))
else:
context = value
self.put(cache_key, json.dumps(context))
def get_performance(self):
fields = list(self._cls().__dict__.keys())
return RedisObject(fields, self._cls.__name__, self, encode='json')
def __init__(self, user):
super().__init__(user)
self._translator = DataframeTranslator({
'height': 'auto',
'width': '98%',
'pageSize': 20,
'where': 'f_getWhere()'
})
def test(detail):
def get_first_n_lines(string, n):
lines = string.splitlines()
n = min(n, len(lines))
return '\n'.join(lines[:n])
#gc.set_debug(gc.DEBUG_UNCOLLECTABLE | gc.DEBUG_SAVEALL)
start_time = time.time()
with codecs.open('../test/testcode7.py', 'r', 'utf-8') as f:
code = f.read()
user = User('10032')
backtest = Backtesting(user, 'test', code, ['EURUSD'], 'M30', '2015-01-01',
'2016-01-01')
print(backtest.progress)
for _ in range(4):
backtest.start()
print(backtest.get_performance().trade_summary)
if detail:
translator = DataframeTranslator()
user_dir = UserDirectory(user)
print(user_dir.get_sys_func_list())
print(backtest.get_profit_records()) # 获取浮动收益曲线
print(backtest.get_parameters()) # 获取策略中的参数（用于优化）
performance = backtest.get_performance() # 获取策略的各项指标
print('trade_info:\n%s' % performance._manager.trade_info)
print('trade_summary:\n%s' % performance.trade_summary)
print('trade_details:\n%s' % performance.trade_details)
print(translator.dumps(performance._manager.trade_info))
print(translator.dumps(performance.trade_details))
print('strategy_summary:\n%s' % performance.strategy_summary)
print('optimize_info:\n%s' % performance.optimize_info)
print('info_on_home_page\n%s' % performance.get_info_on_home_page())
print(performance.get_factor_list())
# print(performance.yield_curve)
print('ar:\n%s' % performance.ar) # 年化收益率
print('risk_free_rate:\n%s' %
performance._manager.risk_free_rate) # 无风险收益率
print('volatility:\n%s' % performance.volatility) # 波动率
print('sharpe_ratio:\n%s' % performance.sharpe_ratio) # sharpe比率
print('max_drawdown:\n%s' % performance.max_drawdown) # 最大回测
print('trade_position\n%s' % performance.trade_positions) # 交易仓位
print(time.time() - start_time)
# print('output:\n%s' % get_first_n_lines(backtest.get_output(), 100))
print(time.time() - start_time)
print(backtest.progress)
paras = {'handle': {'times': {'start': 10, 'end': 10, 'step': 1}}}
optimize = backtest.optimize(paras, None, None)
print('optimize\n%s' % optimize)
print(time.time() - start_time)
del backtest
performance = None
optimize = None
class PerformanceAfterTranslate:
def __init__(self, performance):
self._performance = performance
self._translator = DataframeTranslator(
{'height': 'auto', 'width': '98%', 'pageSize': 20, 'where': 'f_getWhere()'})
def __getattr__(self, item):
result = getattr(self._performance, item)
if isinstance(result, pd.DataFrame):
return self._translator.dumps(result)
elif isinstance(result, pd.Series):
return self._translator.dumps(pd.DataFrame(result))
else:
return result
class StrategyPerformanceJsonCache(RedisCacheWithExpire):
_cls = StrategyPerformance
_time_expire = 15 * 60
def __init__(self, user):
super().__init__(user)
self._translator = DataframeTranslator(
{'height': 'auto', 'width': '98%', 'pageSize': 20, 'where': 'f_getWhere()'})
def put_performance(self, performance):
for key, value in performance.__dict__.items():
cache_key = ':'.join([self._cls.__name__, key])
if isinstance(value, pd.DataFrame):
context = self._translator.dumps(value)
elif isinstance(value, pd.Series):
context = self._translator.dumps(pd.DataFrame(value))
else:
context = value
self.put(cache_key, json.dumps(context))
def get_performance(self):
fields = list(self._cls().__dict__.keys())
return RedisObject(fields, self._cls.__name__, self, encode='json')
def __init__(self, user):
super().__init__(user)
self._translator = DataframeTranslator(
{'height': 'auto', 'width': '98%', 'pageSize': 20, 'where': 'f_getWhere()'})
def __init__(self, performance):
self._performance = performance
self._translator = DataframeTranslator(
{'height': 'auto', 'width': '98%', 'pageSize': 20, 'where': 'f_getWhere()'})
import time
def get_first_n_lines(string, n):
lines = string.splitlines()
n = min(n, len(lines))
return '\n'.join(lines[:n])
start_time = time.time()
with codecs.open('../test/testcode9.py', 'r', 'utf-8') as f:
code = f.read()
user = User('10032')
backtest = Backtesting(user, 'test', code, ['EURUSD'], 'M15', '2015-01-02',
'2015-03-01')
print(backtest.progress)
backtest.start()
translator = DataframeTranslator()
user_dir = UserDirectory(user)
print(user_dir.get_sys_func_list())
print(backtest.get_profit_records()) # 获取浮动收益曲线
print(backtest.get_parameters()) # 获取策略中的参数（用于优化）
performance = backtest.get_performance() # 获取策略的各项指标
print('trade_info:\n%s' % performance._manager.trade_info)
print('trade_summary:\n%s' % performance.trade_summary)
print('trade_details:\n%s' % performance.trade_details)
print(translator.dumps(performance._manager.trade_info))
print(translator.dumps(performance.trade_details))
print('strategy_summary:\n%s' % performance.strategy_summary)
print('optimize_info:\n%s' % performance.optimize_info)
print('info_on_home_page\n%s' % performance.get_info_on_home_page())
print(performance.get_factor_list())
print(performance.yield_curve)
def get_first_n_lines(string, n):
lines = string.splitlines()
n = min(n, len(lines))
return '\n'.join(lines[:n])
start_time = time.time()
with codecs.open('../test/testcode9.py', 'r', 'utf-8') as f:
code = f.read()
user = User('10032')
backtest = Backtesting(user, 'test', code, ['EURUSD'], 'M15', '2015-01-02', '2015-03-01')
print(backtest.progress)
backtest.start()
translator = DataframeTranslator()
user_dir = UserDirectory(user)
print(user_dir.get_sys_func_list())
print(backtest.get_profit_records()) # 获取浮动收益曲线
print(backtest.get_parameters()) # 获取策略中的参数（用于优化）
performance = backtest.get_performance() # 获取策略的各项指标
print('trade_info:\n%s' % performance._manager.trade_info)
print('trade_summary:\n%s' % performance.trade_summary)
print('trade_details:\n%s' % performance.trade_details)
print(translator.dumps(performance._manager.trade_info))
print(translator.dumps(performance.trade_details))
print('strategy_summary:\n%s' % performance.strategy_summary)
print('optimize_info:\n%s' % performance.optimize_info)
print('info_on_home_page\n%s' % performance.get_info_on_home_page())
print(performance.get_factor_list())
print(performance.yield_curve)
