# 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 *

### <summary>
### Regression algorithm asserting the behavior of auxiliary data history requests
### </summary>
class HistoryAuxiliaryDataRegressionAlgorithm(QCAlgorithm):

 def initialize(self):
 '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''

 self.set_start_date(2021, 1, 1)
 self.set_end_date(2021, 1, 5)

 aapl = self.add_equity("AAPL", Resolution.DAILY).symbol

 # multi symbol request
 spy = Symbol.create("SPY", SecurityType.EQUITY, Market.USA)
 multi_symbol_request = self.history(Dividend, [ aapl, spy ], 360, Resolution.DAILY)
 if len(multi_symbol_request) != 12:
 raise ValueError(f"Unexpected multi symbol dividend count: {len(multi_symbol_request)}")

 # continuous future mapping requests
 sp500 = Symbol.create(Futures.Indices.SP_500_E_MINI, SecurityType.FUTURE, Market.CME)
 continuous_future_open_interest_mapping = self.history(SymbolChangedEvent, sp500, datetime(2007, 1, 1), datetime(2012, 1, 1), data_mapping_mode = DataMappingMode.OPEN_INTEREST)
 if len(continuous_future_open_interest_mapping) != 9:
 raise ValueError(f"Unexpected continuous future mapping event count: {len(continuous_future_open_interest_mapping)}")
 continuous_future_last_trading_day_mapping = self.history(SymbolChangedEvent, sp500, datetime(2007, 1, 1), datetime(2012, 1, 1), data_mapping_mode = DataMappingMode.LAST_TRADING_DAY)
 if len(continuous_future_last_trading_day_mapping) != 9:
 raise ValueError(f"Unexpected continuous future mapping event count: {len(continuous_future_last_trading_day_mapping)}")

 dividend = self.history(Dividend, aapl, 360)
 self.debug(str(dividend))
 if len(dividend) != 6:
 raise ValueError(f"Unexpected dividend count: {len(dividend)}")
 for distribution in dividend.distribution:
 if distribution == 0:
 raise ValueError(f"Unexpected distribution: {distribution}")

 split = self.history(Split, aapl, 360)
 self.debug(str(split))
 if len(split) != 2:
 raise ValueError(f"Unexpected split count: {len(split)}")
 for splitfactor in split.splitfactor:
 if splitfactor == 0:
 raise ValueError(f"Unexpected splitfactor: {splitfactor}")

 symbol = Symbol.create("BTCUSD", SecurityType.CRYPTO_FUTURE, Market.BINANCE)
 margin_interest = self.history(MarginInterestRate, symbol, 24 * 3, Resolution.HOUR)
 self.debug(str(margin_interest))
 if len(margin_interest) != 8:
 raise ValueError(f"Unexpected margin interest count: {len(margin_interest)}")
 for interestrate in margin_interest.interestrate:
 if interestrate == 0:
 raise ValueError(f"Unexpected interestrate: {interestrate}")

 # last trading date on 2007年05月18日
 delisted_symbol = Symbol.create("AAA.1", SecurityType.EQUITY, Market.USA)
 delistings = self.history(Delisting, delisted_symbol, datetime(2007, 5, 15), datetime(2007, 5, 21))
 self.debug(str(delistings))
 if len(delistings) != 2:
 raise ValueError(f"Unexpected delistings count: {len(delistings)}")
 if delistings.iloc[0].type != DelistingType.WARNING:
 raise ValueError(f"Unexpected delisting: {delistings.iloc[0]}")
 if delistings.iloc[1].type != DelistingType.DELISTED:
 raise ValueError(f"Unexpected delisting: {delistings.iloc[1]}")

 # get's remapped:
 # 2008年09月30日 spwr -> spwra
 # 2011年11月17日 spwra -> spwr
 remapped_symbol = Symbol.create("SPWR", SecurityType.EQUITY, Market.USA)
 symbol_changed_events = self.history(SymbolChangedEvent, remapped_symbol, datetime(2007, 1, 1), datetime(2012, 1, 1))
 self.debug(str(symbol_changed_events))
 if len(symbol_changed_events) != 2:
 raise ValueError(f"Unexpected SymbolChangedEvents count: {len(symbol_changed_events)}")
 first_event = symbol_changed_events.iloc[0]
 if first_event.oldsymbol != "SPWR" or first_event.newsymbol != "SPWRA" or symbol_changed_events.index[0][1] != datetime(2008, 9, 30):
 raise ValueError(f"Unexpected SymbolChangedEvents: {first_event}")
 second_event = symbol_changed_events.iloc[1]
 if second_event.newsymbol != "SPWR" or second_event.oldsymbol != "SPWRA" or symbol_changed_events.index[1][1] != datetime(2011, 11, 17):
 raise ValueError(f"Unexpected SymbolChangedEvents: {second_event}")

 def on_data(self, data):
 '''on_data event is the primary entry point for your algorithm. Each new data point will be pumped in here.

 Arguments:
 data: Slice object keyed by symbol containing the stock data
 '''
 if not self.portfolio.invested:
 self.set_holdings("AAPL", 1)