# 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>
### Demonstration of requesting daily resolution data for US Equities.
### This is a simple regression test algorithm using a skeleton algorithm and requesting daily data.
### </summary>
### <meta name="tag" content="using data" />
class NamedArgumentsRegression(QCAlgorithm):
    '''Regression algorithm that makes use of PythonNet kwargs'''

    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.'''

        #Use named args for setting up our algorithm
        self.SetStartDate(month=10,day=8,year=2013)   #Set Start Date
        self.SetEndDate(month=10,day=17,year=2013)    #Set End Date
        self.SetCash(startingCash=100000)           #Set Strategy Cash

        #Check our values
        if self.StartDate.year != 2013 or self.StartDate.month != 10 or self.StartDate.day != 8:
            raise AssertionError(f"Start date was incorrect! Expected 10/8/2013 Recieved {self.StartDate}")

        if self.EndDate.year != 2013 or self.EndDate.month != 10 or self.EndDate.day != 17:
            raise AssertionError(f"End date was incorrect! Expected 10/17/2013 Recieved {self.EndDate}")

        if self.Portfolio.Cash != 100000:
            raise AssertionError(f"Portfolio cash was incorrect! Expected 100000 Recieved {self.Portfolio.Cash}")

        # Use named args for addition of this security to our algorithm
        symbol = self.AddEquity(resolution=Resolution.Daily, ticker="SPY").Symbol

        # Check our subscriptions for the symbol and check its resolution
        for config in self.SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol):
            if config.Resolution != Resolution.Daily:
                raise AssertionError(f"Resolution was not correct on security")


    def OnData(self, data):
        '''OnData 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.SetHoldings(symbol="SPY", percentage=1)
            self.Debug(message="Purchased Stock")