wehub-resource-sync
61 lines
2.5 KiB
Python
61 lines
2.5 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from AlgorithmImports import *
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from collections import deque
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import numpy as np
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### <summary>
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### Algorithm asserting that security dynamic properties keep Python references to the Python class they are instances of,
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### specifically when this class is a subclass of a C# class.
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### </summary>
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class SecurityDynamicPropertyPythonClassAlgorithm(QCAlgorithm):
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def initialize(self) -> None:
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self.set_start_date(2013, 10, 7)
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self.set_end_date(2013, 10, 7)
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self._spy = self.add_equity("SPY", Resolution.MINUTE)
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custom_sma = CustomSimpleMovingAverage('custom', 60)
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self._spy.custom_sma = custom_sma
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custom_sma.security = self._spy
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self.register_indicator(self._spy.symbol, self._spy.custom_sma, Resolution.MINUTE)
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def on_warmup_finished(self) -> None:
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if type(self._spy.custom_sma) != CustomSimpleMovingAverage:
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raise AssertionError("spy.custom_sma is not an instance of CustomSimpleMovingAverage")
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if not self._spy.custom_sma.security:
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raise AssertionError("spy.custom_sma.security is None")
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else:
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self.debug(f"spy.custom_sma.security.symbol: {self._spy.custom_sma.security.symbol}")
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def on_data(self, slice: Slice) -> None:
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if self._spy.custom_sma.is_ready:
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self.debug(f"CustomSMA: {self._spy.custom_sma.current.value}")
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class CustomSimpleMovingAverage(PythonIndicator):
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def __init__(self, name: str, period: int) -> None:
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super().__init__()
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self.name = name
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self.value = 0
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self._queue = deque(maxlen=period)
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def update(self, input: IndicatorDataPoint) -> bool:
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self._queue.appendleft(input.value)
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count = len(self._queue)
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self.value = np.sum(self._queue) / count
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return count == self._queue.maxlen
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