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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 *
### <summary>
### The demonstration algorithm shows some of the most common order methods when working with CFD assets.
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="using quantconnect" />
### <meta name="tag" content="trading and orders" />
class BasicTemplateCfdAlgorithm(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_account_currency('EUR')
        self.set_start_date(2019, 2, 20)
        self.set_end_date(2019, 2, 21)
        self.set_cash('EUR', 100000)
        self._symbol = self.add_cfd('DE30EUR').symbol
        # Historical Data
        history = self.history(self._symbol, 60, Resolution.DAILY)
        self.log(f"Received {len(history)} bars from CFD historical data call.")
    def on_data(self, data):
        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
        Arguments:
            slice: Slice object keyed by symbol containing the stock data
        '''
        # Access Data
        if data.quote_bars.contains_key(self._symbol):
            quote_bar = data.quote_bars[self._symbol]
            self.log(f"{quote_bar.end_time} :: {quote_bar.close}")
        if not self.portfolio.invested:
            self.set_holdings(self._symbol, 1)
    def on_order_event(self, order_event):
        self.debug("{} {}".format(self.time, order_event.to_string()))

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