# 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 *
from QuantConnect.Data.Custom.Tiingo import TiingoPrice

### <summary>
### This example algorithm shows how to import and use Tiingo daily prices data.
### </summary>
### <meta name="tag" content="strategy example" />
### <meta name="tag" content="using data" />
### <meta name="tag" content="custom data" />
### <meta name="tag" content="tiingo" />
class TiingoPriceAlgorithm(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(2017, 1, 1)
        self.set_end_date(2017, 12, 31)
        self.set_cash(100000)

        # Set your Tiingo API Token here
        Tiingo.set_auth_code("my-tiingo-api-token")

        self._equity = self.add_equity("AAPL").symbol
        self._aapl = self.add_data(TiingoPrice, self._equity, Resolution.DAILY).symbol

        self._ema_fast = self.ema(self._equity, 5)
        self._ema_slow = self.ema(self._equity, 10)


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

        if not slice.contains_key(self._equity): return

        # Extract Tiingo data from the slice
        row = slice[self._equity]

        if not row:
            return

        if self._ema_fast.is_ready and self._ema_slow.is_ready:
            self.log(f"{self.time} - {row.symbol.value} - {row.close} {row.value} {row.price} - EmaFast:{self._ema_fast} - EmaSlow:{self._ema_slow}")

        # Simple EMA cross
        if not self.portfolio.invested and self._ema_fast > self._ema_slow:
            self.set_holdings(self._equity, 1)

        elif self.portfolio.invested and self._ema_fast < self._ema_slow:
            self.liquidate(self._equity)