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pep8 conversion on python algorithms #2 (#7933)

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* pep8 conversion

* more

* Minor fix

* Fix related regression algorithm

---------

Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
This commit is contained in:
Louis Szeto
2024-04-18 04:36:53 +08:00
committed by GitHub
parent c2bea3c173
commit 784e497691
25 changed files with 466 additions and 466 deletions
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Algorithm.Python/BasicTemplateFutureRolloverAlgorithm.py
+55 -55
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@@ -21,48 +21,48 @@ class BasicTemplateFutureRolloverAlgorithm(QCAlgorithm):
### <summary>
### Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
### </summary>
def Initialize(self):
self.SetStartDate(2013, 10, 8)
self.SetEndDate(2013, 12, 10)
self.SetCash(1000000)
def initialize(self):
self.set_start_date(2013, 10, 8)
self.set_end_date(2013, 12, 10)
self.set_cash(1000000)
self.symbol_data_by_symbol = {}
self._symbol_data_by_symbol = {}
futures = [
Futures.Indices.SP500EMini
Futures.Indices.SP_500_E_MINI
]
for future in futures:
# Requesting data
continuous_contract = self.AddFuture(future,
resolution = Resolution.Daily,
extendedMarketHours = True,
dataNormalizationMode = DataNormalizationMode.BackwardsRatio,
dataMappingMode = DataMappingMode.OpenInterest,
contractDepthOffset = 0
continuous_contract = self.add_future(future,
resolution = Resolution.DAILY,
extended_market_hours = True,
data_normalization_mode = DataNormalizationMode.BACKWARDS_RATIO,
data_mapping_mode = DataMappingMode.OPEN_INTEREST,
contract_depth_offset = 0
)
symbol_data = SymbolData(self, continuous_contract)
self.symbol_data_by_symbol[continuous_contract.Symbol] = symbol_data
self._symbol_data_by_symbol[continuous_contract.symbol] = symbol_data
### <summary>
### OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
### on_data event is the primary entry point for your algorithm. Each new data point will be pumped in here.
### </summary>
### <param name="slice">Slice object keyed by symbol containing the stock data</param>
def OnData(self, slice):
for symbol, symbol_data in self.symbol_data_by_symbol.items():
# Call SymbolData.Update() method to handle new data slice received
symbol_data.Update(slice)
def on_data(self, slice):
for symbol, symbol_data in self._symbol_data_by_symbol.items():
# Call SymbolData.update() method to handle new data slice received
symbol_data.update(slice)
# Check if information in SymbolData class and new slice data are ready for trading
if not symbol_data.IsReady or not slice.Bars.ContainsKey(symbol):
if not symbol_data.is_ready or not slice.bars.contains_key(symbol):
return
ema_current_value = symbol_data.EMA.Current.Value
if ema_current_value < symbol_data.Price and not symbol_data.IsLong:
self.MarketOrder(symbol_data.Mapped, 1)
elif ema_current_value > symbol_data.Price and not symbol_data.IsShort:
self.MarketOrder(symbol_data.Mapped, -1)
ema_current_value = symbol_data.EMA.current.value
if ema_current_value < symbol_data.price and not symbol_data.is_long:
self.market_order(symbol_data.mapped, 1)
elif ema_current_value > symbol_data.price and not symbol_data.is_short:
self.market_order(symbol_data.mapped, -1)
### <summary>
### Abstracted class object to hold information (state, indicators, methods, etc.) from a Symbol/Security in a multi-security algorithm
@@ -75,55 +75,55 @@ class SymbolData:
def __init__(self, algorithm, future):
self._algorithm = algorithm
self._future = future
self.EMA = algorithm.EMA(future.Symbol, 20, Resolution.Daily)
self.Price = 0
self.IsLong = False
self.IsShort = False
self.EMA = algorithm.ema(future.symbol, 20, Resolution.DAILY)
self.price = 0
self.is_long = False
self.is_short = False
self.Reset()
self.reset()
@property
def Symbol(self):
return self._future.Symbol
def symbol(self):
return self._future.symbol
@property
def Mapped(self):
return self._future.Mapped
def mapped(self):
return self._future.mapped
@property
def IsReady(self):
return self.Mapped is not None and self.EMA.IsReady
def is_ready(self):
return self.mapped is not None and self.EMA.is_ready
### <summary>
### Handler of new slice of data received
### </summary>
def Update(self, slice):
if slice.SymbolChangedEvents.ContainsKey(self.Symbol):
changed_event = slice.SymbolChangedEvents[self.Symbol]
old_symbol = changed_event.OldSymbol
new_symbol = changed_event.NewSymbol
tag = f"Rollover - Symbol changed at {self._algorithm.Time}: {old_symbol} -> {new_symbol}"
quantity = self._algorithm.Portfolio[old_symbol].Quantity
def update(self, slice):
if slice.symbol_changed_events.contains_key(self.symbol):
changed_event = slice.symbol_changed_events[self.symbol]
old_symbol = changed_event.old_symbol
new_symbol = changed_event.new_symbol
tag = f"Rollover - Symbol changed at {self._algorithm.time}: {old_symbol} -> {new_symbol}"
quantity = self._algorithm.portfolio[old_symbol].quantity
# Rolling over: to liquidate any position of the old mapped contract and switch to the newly mapped contract
self._algorithm.Liquidate(old_symbol, tag = tag)
self._algorithm.MarketOrder(new_symbol, quantity, tag = tag)
self._algorithm.liquidate(old_symbol, tag = tag)
self._algorithm.market_order(new_symbol, quantity, tag = tag)
self.Reset()
self.reset()
self.Price = slice.Bars[self.Symbol].Price if slice.Bars.ContainsKey(self.Symbol) else self.Price
self.IsLong = self._algorithm.Portfolio[self.Mapped].IsLong
self.IsShort = self._algorithm.Portfolio[self.Mapped].IsShort
self.price = slice.bars[self.symbol].price if slice.bars.contains_key(self.symbol) else self.price
self.is_long = self._algorithm.portfolio[self.mapped].is_long
self.is_short = self._algorithm.portfolio[self.mapped].is_short
### <summary>
### Reset RollingWindow/indicator to adapt to newly mapped contract, then warm up the RollingWindow/indicator
### reset RollingWindow/indicator to adapt to newly mapped contract, then warm up the RollingWindow/indicator
### </summary>
def Reset(self):
self.EMA.Reset()
self._algorithm.WarmUpIndicator(self.Symbol, self.EMA, Resolution.Daily)
def reset(self):
self.EMA.reset()
self._algorithm.warm_up_indicator(self.symbol, self.EMA, Resolution.DAILY)
### <summary>
### Disposal method to remove consolidator/update method handler, and reset RollingWindow/indicator to free up memory and speed
### disposal method to remove consolidator/update method handler, and reset RollingWindow/indicator to free up memory and speed
### </summary>
def Dispose(self):
self.EMA.Reset()
def dispose(self):
self.EMA.reset()