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* feat: support snake-case style Python QCAlgorithm implementations * feat: add unit tests and minor fixes * feat: implement new BasePythonWrapper class for python wrappers. Used to cache methods and contains invoke functionality * feat: make python wrappers implement the new base class for pep8 style support * feat: keep overriden methods in Algorithm Python Wrapper * feat: add unit tests for custom models algorithms with PEP8 style * Bump pythonnet version to 2.0.30 * fix bugs and address peer review * Address peer review * Minor revert * feat: StubsIgnoreAttribute for ignoring members or classes by the stubs generator * Minor fixes * Minor fix * Minor fix * Bump pythonnet version to 2.0.31 * Added Greeks.Lambda_ alias of Lambda for python compatibility. Remove unused method
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| Original file line number | Diff line number | Diff line change |
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| # QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. | ||
| # Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
|
|
||
| from AlgorithmImports import * | ||
| import random | ||
|
|
||
| ### <summary> | ||
| ### Demonstration of using custom fee, slippage, fill, and buying power models for modeling transactions in backtesting. | ||
| ### QuantConnect allows you to model all orders as deeply and accurately as you need. | ||
| ### This example illustrates how Lean exports its API to Python conforming to PEP8 style guide. | ||
| ### </summary> | ||
| ### <meta name="tag" content="trading and orders" /> | ||
| ### <meta name="tag" content="transaction fees and slippage" /> | ||
| ### <meta name="tag" content="custom buying power models" /> | ||
| ### <meta name="tag" content="custom transaction models" /> | ||
| ### <meta name="tag" content="custom slippage models" /> | ||
| ### <meta name="tag" content="custom fee models" /> | ||
| class CustomModelsPEP8Algorithm(QCAlgorithm): | ||
| '''Demonstration of using custom fee, slippage, fill, and buying power models for modeling transactions in backtesting. | ||
| QuantConnect allows you to model all orders as deeply and accurately as you need.''' | ||
|
|
||
| def initialize(self): | ||
| self.set_start_date(2013,10,1) # Set Start Date | ||
| self.set_end_date(2013,10,31) # Set End Date | ||
| self.security = self.add_equity("SPY", Resolution.HOUR) | ||
| self.spy = self.security.symbol | ||
|
|
||
| # set our models | ||
| self.security.set_fee_model(CustomFeeModelPEP8(self)) | ||
| self.security.set_fill_model(CustomFillModelPEP8(self)) | ||
| self.security.set_slippage_model(CustomSlippageModelPEP8(self)) | ||
| self.security.set_buying_power_model(CustomBuyingPowerModelPEP8(self)) | ||
|
|
||
| def on_data(self, data): | ||
| open_orders = self.transactions.get_open_orders(self.spy) | ||
| if len(open_orders) != 0: return | ||
| if self.time.day > 10 and self.security.holdings.quantity <= 0: | ||
| quantity = self.calculate_order_quantity(self.spy, .5) | ||
| self.log(f"MarketOrder: {quantity}") | ||
| self.market_order(self.spy, quantity, True) # async needed for partial fill market orders | ||
| elif self.time.day > 20 and self.security.holdings.quantity >= 0: | ||
| quantity = self.calculate_order_quantity(self.spy, -.5) | ||
| self.log(f"MarketOrder: {quantity}") | ||
| self.market_order(self.spy, quantity, True) # async needed for partial fill market orders | ||
|
|
||
| class CustomFillModelPEP8(ImmediateFillModel): | ||
| def __init__(self, algorithm): | ||
| super().__init__() | ||
| self.algorithm = algorithm | ||
| self.absolute_remaining_by_order_id = {} | ||
| self.random = Random(387510346) | ||
|
|
||
| def market_fill(self, asset, order): | ||
| absolute_remaining = order.absolute_quantity | ||
|
|
||
| if order.id in self.absolute_remaining_by_order_id.keys(): | ||
| absolute_remaining = self.absolute_remaining_by_order_id[order.id] | ||
|
|
||
| fill = super().market_fill(asset, order) | ||
| absolute_fill_quantity = int(min(absolute_remaining, self.random.next(0, 2*int(order.absolute_quantity)))) | ||
| fill.fill_quantity = np.sign(order.quantity) * absolute_fill_quantity | ||
|
|
||
| if absolute_remaining == absolute_fill_quantity: | ||
| fill.status = OrderStatus.FILLED | ||
| if self.absolute_remaining_by_order_id.get(order.id): | ||
| self.absolute_remaining_by_order_id.pop(order.id) | ||
| else: | ||
| absolute_remaining = absolute_remaining - absolute_fill_quantity | ||
| self.absolute_remaining_by_order_id[order.id] = absolute_remaining | ||
| fill.status = OrderStatus.PARTIALLY_FILLED | ||
| self.algorithm.log(f"CustomFillModel: {fill}") | ||
| return fill | ||
|
|
||
| class CustomFeeModelPEP8(FeeModel): | ||
| def __init__(self, algorithm): | ||
| super().__init__() | ||
| self.algorithm = algorithm | ||
|
|
||
| def get_order_fee(self, parameters): | ||
| # custom fee math | ||
| fee = max(1, parameters.security.price | ||
| * parameters.order.absolute_quantity | ||
| * 0.00001) | ||
| self.algorithm.log(f"CustomFeeModel: {fee}") | ||
| return OrderFee(CashAmount(fee, "USD")) | ||
|
|
||
| class CustomSlippageModelPEP8: | ||
| def __init__(self, algorithm): | ||
| self.algorithm = algorithm | ||
|
|
||
| def get_slippage_approximation(self, asset, order): | ||
| # custom slippage math | ||
| slippage = asset.price * 0.0001 * np.log10(2*float(order.absolute_quantity)) | ||
| self.algorithm.log(f"CustomSlippageModel: {slippage}") | ||
| return slippage | ||
|
|
||
| class CustomBuyingPowerModelPEP8(BuyingPowerModel): | ||
| def __init__(self, algorithm): | ||
| super().__init__() | ||
| self.algorithm = algorithm | ||
|
|
||
| def has_sufficient_buying_power_for_order(self, parameters): | ||
| # custom behavior: this model will assume that there is always enough buying power | ||
| has_sufficient_buying_power_for_order_result = HasSufficientBuyingPowerForOrderResult(True) | ||
| self.algorithm.log(f"CustomBuyingPowerModel: {has_sufficient_buying_power_for_order_result.is_sufficient}") | ||
| return has_sufficient_buying_power_for_order_result | ||
|
|
||
| class SimpleCustomFillModelPEP8(FillModel): | ||
| def __init__(self): | ||
| super().__init() | ||
|
|
||
| def _create_order_event(self, asset, order): | ||
| utc_time = Extensions.convert_to_utc(asset.local_time, asset.exchange.time_zone) | ||
| return OrderEvent(order, utc_time, OrderFee.zero) | ||
|
|
||
| def _set_order_event_to_filled(self, fill, fill_price, fill_quantity): | ||
| fill.status = OrderStatus.FILLED | ||
| fill.fill_quantity = fill_quantity | ||
| fill.fill_price = fill_price | ||
| return fill | ||
|
|
||
| def _get_trade_bar(self, asset, order_direction): | ||
| trade_bar = asset.cache.get_data[TradeBar]() | ||
| if trade_bar: | ||
| return trade_bar | ||
|
|
||
| price = asset.price | ||
| return TradeBar(asset.local_time, asset.symbol, price, price, price, price, 0) | ||
|
|
||
| def market_fill(self, asset, order): | ||
| fill = self._create_order_event(asset, order) | ||
| if order.status == OrderStatus.CANCELED: | ||
| return fill | ||
|
|
||
| fill_price = asset.cache.ask_price if order.direction == OrderDirection.BUY else asset.cache.bid_price | ||
| return self._set_order_event_to_filled(fill, fill_price, order.quantity) | ||
|
|
||
| def stop_market_fill(self, asset, order): | ||
| fill = self._create_order_event(asset, order) | ||
| if order.status == OrderStatus.CANCELED: | ||
| return fill | ||
|
|
||
| stop_price = order.stop_price | ||
| trade_bar = self._get_trade_bar(asset, order.direction) | ||
|
|
||
| if order.direction == OrderDirection.SELL and trade_bar.low < stop_price: | ||
| return self._set_order_event_to_filled(fill, stop_price, order.quantity) | ||
|
|
||
| if order.direction == OrderDirection.BUY and trade_bar.high > stop_price: | ||
| return self._set_order_event_to_filled(fill, stop_price, order.quantity) | ||
|
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||
| return fill | ||
|
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||
| def limit_fill(self, asset, order): | ||
| fill = self._create_order_event(asset, order) | ||
| if order.status == OrderStatus.CANCELED: | ||
| return fill | ||
|
|
||
| limit_price = order.limit_price | ||
| trade_bar = self._get_trade_bar(asset, order.direction) | ||
|
|
||
| if order.direction == OrderDirection.SELL and trade_bar.high > limit_price: | ||
| return self._set_order_event_to_filled(fill, limit_price, order.quantity) | ||
|
|
||
| if order.direction == OrderDirection.BUY and trade_bar.low < limit_price: | ||
| return self._set_order_event_to_filled(fill, limit_price, order.quantity) | ||
|
|
||
| return fill |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,48 @@ | ||
| # QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. | ||
| # Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
|
|
||
| from AlgorithmImports import * | ||
|
|
||
| class PEP8StyleBasicAlgorithm(QCAlgorithm): | ||
|
|
||
| def initialize(self): | ||
| self.set_start_date(2013,10, 7) | ||
| self.set_end_date(2013,10,11) | ||
| self.set_cash(100000) | ||
|
|
||
| self.spy = self.add_equity("SPY", Resolution.MINUTE, extended_market_hours=False, fill_forward=True).symbol | ||
|
|
||
| # Test accessing a constant (QCAlgorithm.MaxTagsCount) | ||
| self.debug("MaxTagsCount: " + str(self.MAX_TAGS_COUNT)) | ||
|
|
||
| def on_data(self, slice): | ||
| if not self.portfolio.invested: | ||
| self.set_holdings(self.spy, 1) | ||
| self.debug("Purchased Stock") | ||
|
|
||
| def on_order_event(self, order_event): | ||
| self.log(f"{self.time} :: {order_event}") | ||
|
|
||
| def on_end_of_algorithm(self): | ||
| self.log("Algorithm ended!") | ||
|
|
||
| if not self.portfolio.invested: | ||
| raise Exception("Algorithm should have been invested at the end of the algorithm") | ||
|
|
||
| # let's do some logging to do more pep8 style testing | ||
| self.log("-----------------------------------------------------------------------------------------") | ||
| self.log(f"{self.spy.value} last price: {self.securities[self.spy].price}") | ||
| self.log(f"{self.spy.value} holdings: " | ||
| f"{self.securities[self.spy].holdings.quantity}@{self.securities[self.spy].holdings.price}=" | ||
| f"{self.securities[self.spy].holdings.holdings_value}") | ||
| self.log("-----------------------------------------------------------------------------------------") |
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