# 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 to validate SecurityCache.Session functionality.
### Verifies that daily session bars (Open, High, Low, Close, Volume) are correctly
### </summary>
class SecuritySessionRegressionAlgorithm(QCAlgorithm):
 
 def initialize(self):
 self.add_security_initializer(self.initialize_session_tracking)
 self.initialize_security()

 # Check initial session values
 session = self.security.session
 if session is None:
 raise RegressionTestException("Security.Session is none")
 if (session.open != 0
 or session.high != 0
 or session.low != 0
 or session.close != 0
 or session.volume != 0
 or session.open_interest != 0):
 raise RegressionTestException("Session should start with all zero values.")
 
 self.security_was_removed = False
 self.open = self.close = self.high = self.volume = 0
 self.low = float('inf')
 self.current_date = self.start_date
 self.previous_session_bar = None

 self.schedule.on(
 self.date_rules.every_day(),
 self.time_rules.after_market_close(self.security.symbol, 1),
 self.validate_session_bars
 )

 def initialize_security(self):
 self.set_start_date(2013, 10, 7)
 self.set_end_date(2013, 10, 11)
 self.security = self.add_equity("SPY", Resolution.HOUR)

 def initialize_session_tracking(self, security):
 # activate session tracking
 security.session.size = 3

 def _are_equal(self, value1, value2):
 tolerance = 1e-10
 return abs(value1 - value2) <= tolerance
 
 def validate_session_bars(self):
 session = self.security.session
 # At this point the data was consolidated (market close)

 # Save previous session bar
 self.previous_session_bar = {
 'date': self.current_date,
 'open': self.open,
 'high': self.high,
 'low': self.low,
 'close': self.close,
 'volume': self.volume
 }

 if self.security_was_removed:
 self.previous_session_bar = None
 self.security_was_removed = False
 return

 # Check current session values
 if (not self._are_equal(session.open, self.open)
 or not self._are_equal(session.high, self.high)
 or not self._are_equal(session.low, self.low)
 or not self._are_equal(session.close, self.close)
 or not self._are_equal(session.volume, self.volume)):
 raise RegressionTestException("Mismatch in current session bar (OHLCV)")

 def is_within_market_hours(self, current_date_time):
 market_open = self.security.exchange.hours.get_next_market_open(current_date_time.date(), False).time()
 market_close = self.security.exchange.hours.get_next_market_close(current_date_time.date(), False).time()
 current_time = current_date_time.time()
 return market_open < current_time <= market_close

 def on_data(self, data):
 if not self.is_within_market_hours(data.time):
 # Skip data outside market hours
 return

 # Accumulate data within regular market hours
 # to later compare against the Session values
 self.accumulate_session_data(data)

 def accumulate_session_data(self, data):
 symbol = self.security.symbol
 if self.current_date.date() == data.time.date():
 # Same trading day
 if self.open == 0:
 self.open = data[symbol].open
 self.high = max(self.high, data[symbol].high)
 self.low = min(self.low, data[symbol].low)
 self.close = data[symbol].close
 self.volume += data[symbol].volume
 else:
 # New trading day

 if self.previous_session_bar is not None:
 session = self.security.session
 if (self.previous_session_bar['open'] != session[1].open
 or self.previous_session_bar['high'] != session[1].high
 or self.previous_session_bar['low'] != session[1].low
 or self.previous_session_bar['close'] != session[1].close
 or self.previous_session_bar['volume'] != session[1].volume):
 raise RegressionTestException("Mismatch in previous session bar (OHLCV)")

 # This is the first data point of the new session
 self.open = data[symbol].open
 self.close = data[symbol].close
 self.high = data[symbol].high
 self.low = data[symbol].low
 self.volume = data[symbol].volume
 self.current_date = data.time