github-featured/quantconnect--lean
2
0
Fork 0
Code Issues Pull Requests Deployments Models Agent Notes Packages Projects Releases Wiki Activity

PEP8 algorithms conversion (#7962)

Browse Source 
* PEP8 algorithms conversion

* PEP8 unit tests algorithms conversion

* Minor fixes
This commit is contained in:
Jhonathan Abreu
2024-04-22 12:59:50 -04:00
committed by GitHub
parent 8fa824b19e
commit 6bfe45dbcf
14 changed files with 208 additions and 269 deletions
Download Patch File Download Diff File Expand all files Collapse all files
Algorithm.Python/RegisterIndicatorRegressionAlgorithm.py
+51 -51
View File
@@ -19,98 +19,98 @@ from CustomDataRegressionAlgorithm import Bitcoin
### </summary>
class RegisterIndicatorRegressionAlgorithm(QCAlgorithm):
# Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
def Initialize(self):
self.SetStartDate(2013, 10, 7)
self.SetEndDate(2013, 10, 9)
def initialize(self):
self.set_start_date(2013, 10, 7)
self.set_end_date(2013, 10, 9)
SP500 = Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.CME)
self._symbol = _symbol = self.FutureChainProvider.GetFutureContractList(SP500, (self.StartDate + timedelta(days=1)))[0]
self.AddFutureContract(_symbol)
SP500 = Symbol.create(Futures.Indices.SP_500_E_MINI, SecurityType.FUTURE, Market.CME)
self._symbol = _symbol = self.future_chain_provider.get_future_contract_list(SP500, (self.start_date + timedelta(days=1)))[0]
self.add_future_contract(_symbol)
# this collection will hold all indicators and at the end of the algorithm we will assert that all of them are ready
self._indicators = []
# this collection will be used to determine if the Selectors were called, we will assert so at the end of algorithm
self._selectorCalled = [ False, False, False, False, False, False ]
self._selector_called = [ False, False, False, False, False, False ]
# First we will test that we can register our custom indicator using a QuoteBar consolidator
indicator = CustomIndicator()
consolidator = self.ResolveConsolidator(_symbol, Resolution.Minute, QuoteBar)
self.RegisterIndicator(_symbol, indicator, consolidator)
consolidator = self.resolve_consolidator(_symbol, Resolution.MINUTE, QuoteBar)
self.register_indicator(_symbol, indicator, consolidator)
self._indicators.append(indicator)
indicator2 = CustomIndicator()
# We use the TimeDelta overload to fetch the consolidator
consolidator = self.ResolveConsolidator(_symbol, timedelta(minutes=1), QuoteBar)
consolidator = self.resolve_consolidator(_symbol, timedelta(minutes=1), QuoteBar)
# We specify a custom selector to be used
self.RegisterIndicator(_symbol, indicator2, consolidator, lambda bar: self.SetSelectorCalled(0) and bar)
self.register_indicator(_symbol, indicator2, consolidator, lambda bar: self.set_selector_called(0) and bar)
self._indicators.append(indicator2)
# We use a IndicatorBase<IndicatorDataPoint> with QuoteBar data and a custom selector
indicator3 = SimpleMovingAverage(10)
consolidator = self.ResolveConsolidator(_symbol, timedelta(minutes=1), QuoteBar)
self.RegisterIndicator(_symbol, indicator3, consolidator, lambda bar: self.SetSelectorCalled(1) and (bar.Ask.High - bar.Bid.Low))
consolidator = self.resolve_consolidator(_symbol, timedelta(minutes=1), QuoteBar)
self.register_indicator(_symbol, indicator3, consolidator, lambda bar: self.set_selector_called(1) and (bar.ask.high - bar.bid.low))
self._indicators.append(indicator3)
# We test default consolidator resolution works correctly
movingAverage = SimpleMovingAverage(10)
# Using Resolution, specifying custom selector and explicitly using TradeBar.Volume
self.RegisterIndicator(_symbol, movingAverage, Resolution.Minute, lambda bar: self.SetSelectorCalled(2) and bar.Volume)
self._indicators.append(movingAverage)
moving_average = SimpleMovingAverage(10)
# Using Resolution, specifying custom selector and explicitly using TradeBar.volume
self.register_indicator(_symbol, moving_average, Resolution.MINUTE, lambda bar: self.set_selector_called(2) and bar.volume)
self._indicators.append(moving_average)
movingAverage2 = SimpleMovingAverage(10)
moving_average2 = SimpleMovingAverage(10)
# Using Resolution
self.RegisterIndicator(_symbol, movingAverage2, Resolution.Minute)
self._indicators.append(movingAverage2)
self.register_indicator(_symbol, moving_average2, Resolution.MINUTE)
self._indicators.append(moving_average2)
movingAverage3 = SimpleMovingAverage(10)
moving_average3 = SimpleMovingAverage(10)
# Using timedelta
self.RegisterIndicator(_symbol, movingAverage3, timedelta(minutes=1))
self._indicators.append(movingAverage3)
self.register_indicator(_symbol, moving_average3, timedelta(minutes=1))
self._indicators.append(moving_average3)
movingAverage4 = SimpleMovingAverage(10)
# Using timeDelta, specifying custom selector and explicitly using TradeBar.Volume
self.RegisterIndicator(_symbol, movingAverage4, timedelta(minutes=1), lambda bar: self.SetSelectorCalled(3) and bar.Volume)
self._indicators.append(movingAverage4)
moving_average4 = SimpleMovingAverage(10)
# Using time_delta, specifying custom selector and explicitly using TradeBar.volume
self.register_indicator(_symbol, moving_average4, timedelta(minutes=1), lambda bar: self.set_selector_called(3) and bar.volume)
self._indicators.append(moving_average4)
# Test custom data is able to register correctly and indicators updated
symbolCustom = self.AddData(Bitcoin, "BTC", Resolution.Minute).Symbol
symbol_custom = self.add_data(Bitcoin, "BTC", Resolution.MINUTE).symbol
smaCustomData = SimpleMovingAverage(1)
self.RegisterIndicator(symbolCustom, smaCustomData, timedelta(minutes=1), lambda bar: self.SetSelectorCalled(4) and bar.Volume)
self._indicators.append(smaCustomData)
sma_custom_data = SimpleMovingAverage(1)
self.register_indicator(symbol_custom, sma_custom_data, timedelta(minutes=1), lambda bar: self.set_selector_called(4) and bar.volume)
self._indicators.append(sma_custom_data)
smaCustomData2 = SimpleMovingAverage(1)
self.RegisterIndicator(symbolCustom, smaCustomData2, Resolution.Minute)
self._indicators.append(smaCustomData2)
sma_custom_data2 = SimpleMovingAverage(1)
self.register_indicator(symbol_custom, sma_custom_data2, Resolution.MINUTE)
self._indicators.append(sma_custom_data2)
smaCustomData3 = SimpleMovingAverage(1)
consolidator = self.ResolveConsolidator(symbolCustom, timedelta(minutes=1))
self.RegisterIndicator(symbolCustom, smaCustomData3, consolidator, lambda bar: self.SetSelectorCalled(5) and bar.Volume)
self._indicators.append(smaCustomData3)
sma_custom_data3 = SimpleMovingAverage(1)
consolidator = self.resolve_consolidator(symbol_custom, timedelta(minutes=1))
self.register_indicator(symbol_custom, sma_custom_data3, consolidator, lambda bar: self.set_selector_called(5) and bar.volume)
self._indicators.append(sma_custom_data3)
def SetSelectorCalled(self, position):
self._selectorCalled[position] = True
def set_selector_called(self, position):
self._selector_called[position] = True
return True
# OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
def OnData(self, data):
if not self.Portfolio.Invested:
self.SetHoldings(self._symbol, 0.5)
def on_data(self, data):
if not self.portfolio.invested:
self.set_holdings(self._symbol, 0.5)
def OnEndOfAlgorithm(self):
if any(not wasCalled for wasCalled in self._selectorCalled):
def on_end_of_algorithm(self):
if any(not was_called for was_called in self._selector_called):
raise ValueError("All selectors should of been called")
if any(not indicator.IsReady for indicator in self._indicators):
if any(not indicator.is_ready for indicator in self._indicators):
raise ValueError("All indicators should be ready")
self.Log(f'Total of {len(self._indicators)} are ready')
self.log(f'Total of {len(self._indicators)} are ready')
class CustomIndicator(PythonIndicator):
def __init__(self):
super().__init__()
self.Name = "Jose"
self.Value = 0
self.name = "Jose"
self.value = 0
def Update(self, input):
self.Value = input.Ask.High
def update(self, input):
self.value = input.ask.high
return True