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Fix bug/syntax in python examples (#8658)

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* CustomDataRegressionAlgorithm

* DescendingCustomDataObjectStoreRegressionAlgorithm

* CustomDataPropertiesRegressionAlgorithm

* DateTime -> should be datetime

* KerasNeuralNetworkAlgorithm

* OptionIndicatorsMirrorContractsRegressionAlgorithm

* BybitCustomDataCryptoRegressionAlgorithm

* DropboxBaseDataUniverseSelectionAlgorithm

* UserDefinedUniverseAlgorithm

* CompleteOrderTagUpdateAlgorithm

* BasicTemplateOptionEquityStrategyAlgorithm hint

* ETFConstituentUniverseFrameworkRegressionAlgorithm

* FutureStopMarketOrderOnExtendedHoursRegressionAlgorithm

* SecurityDynamicPropertyPythonClassAlgorithm

* hint

* hinting

* CallbackCommandRegressionAlgorithm

* CustomWarmUpPeriodIndicatorAlgorithm

* CrunchDAOSignalExportDemonstrationAlgorithm

* ExpiryHelperAlphaModelFrameworkAlgorithm

* ClassicRenkoConsolidatorAlgorithm

* SmaCrossUniverseSelectionAlgorithm

* PEP8 Fix: Assigning to a Method

* SliceGetByTypeRegressionAlgorithm

* MarketOnCloseOrderBufferExtendedMarketHoursRegressionAlgorithm

* MarketOnCloseOrderBufferRegressionAlgorithm

* CustomIndicatorAlgorithm

* ScheduledQueuingAlgorithm

* ComboOrdersFillModelAlgorithm

* CustomIndicatorWithExtensionAlgorithm

* IndicatorWithRenkoBarsRegressionAlgorithm

* CoarseFineOptionUniverseChainRegressionAlgorithm

* NumeraiSignalExportDemonstrationAlgorithm

* DropboxUniverseSelectionAlgorithm

* WeeklyUniverseSelectionRegressionAlgorithm

* AutoRegressiveIntegratedMovingAverageRegressionAlgorithm

* DropboxBaseDataUniverseSelectionAlgorithm

* IronCondorStrategyAlgorithm

* LongAndShortButterflyPutStrategiesAlgorithm

* FutureStopMarketOrderOnExtendedHoursRegressionAlgorithm

* LongAndShortCallCalendarSpreadStrategiesAlgorithm

* KerasNeuralNetworkAlgorithm

* LongAndShortPutCalendarSpreadStrategiesAlgorithm

* OptionPriceModelForOptionStylesBaseRegressionAlgorithm

* TensorFlowNeuralNetworkAlgorithm

* MarketOnCloseOrderBufferRegressionAlgorithm

* MarketOnCloseOrderBufferExtendedMarketHoursRegressionAlgorithm

* typing

* ComboOrderTicketDemoAlgorithm

* PytorchNeuralNetworkAlgorithm

* MultipleSymbolConsolidationAlgorithm

* fixes

* revert getattr mypy syntax

* address peer review

* Addresses Peer-Review

---------

Co-authored-by: Alexandre Catarino <AlexCatarino@users.noreply.github.com>
This commit is contained in:
Louis Szeto
2025-04-14 20:43:03 +08:00
committed by GitHub
parent fe46e5ec3b
commit 020cf013df
55 changed files with 717 additions and 738 deletions
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Algorithm.Python/DailyAlgorithm.py
+11 -14
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@@ -29,11 +29,10 @@ class DailyAlgorithm(QCAlgorithm):
self.set_cash(100000) #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
self.add_equity("SPY", Resolution.DAILY)
self.add_equity("IBM", Resolution.HOUR).set_leverage(1.0)
self.macd = self.macd("SPY", 12, 26, 9, MovingAverageType.WILDERS, Resolution.DAILY, Field.CLOSE)
self.ema = self.ema("IBM", 15 * 6, Resolution.HOUR, Field.SEVEN_BAR)
self.last_action = None
self.add_equity("IBM", Resolution.HOUR, leverage=1)
self._macd = self.macd("SPY", 12, 26, 9, MovingAverageType.WILDERS, Resolution.DAILY, Field.CLOSE)
self._ema = self.ema("IBM", 15 * 6, Resolution.HOUR, Field.SEVEN_BAR)
self._last_action = self.start_date
def on_data(self, data):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
@@ -41,17 +40,15 @@ class DailyAlgorithm(QCAlgorithm):
Arguments:
data: Slice object keyed by symbol containing the stock data
'''
if not self.macd.is_ready: return
if not data.contains_key("IBM"): return
if data["IBM"] is None:
self.log("Price Missing Time: %s"%str(self.time))
return
if self.last_action is not None and self.last_action.date() == self.time.date(): return
if not self._macd.is_ready: return
bar = data.bars.get("IBM")
if not bar: return
if self._last_action.date() == self.time.date(): return
self.last_action = self.time
self._last_action = self.time
quantity = self.portfolio["SPY"].quantity
if quantity <= 0 and self.macd.current.value > self.macd.signal.current.value and data["IBM"].price > self.ema.current.value:
if quantity <= 0 and self._macd.current.value > self._macd.signal.current.value and bar.price > self._ema.current.value:
self.set_holdings("IBM", 0.25)
elif quantity >= 0 and self.macd.current.value < self.macd.signal.current.value and data["IBM"].price < self.ema.current.value:
if quantity >= 0 and self._macd.current.value < self._macd.signal.current.value and bar.price < self._ema.current.value:
self.set_holdings("IBM", -0.25)