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Moved the test folder.
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"""
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Algorithm Protocol
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===================
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For a class to be passed as a trading algorithm to the
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:py:class:`zipline.lines.SimulatedTrading` zipline
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it must follow an implementation protocol. Examples of this algorithm protocol
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are provided below.
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The algorithm must expose methods:
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- initialize: method that takes no args, no returns. Simply called to
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enable the algorithm to set any internal state needed.
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- get_sid_filter: method that takes no args, and returns a list
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of valid sids. List must have a length between 1 and 10. If None is returned
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the filter will block all events.
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- handle_frame: method that accepts a :py:class:`pandas.Dataframe` of the
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current state of the simulation universe. An example frame::
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+-----------------+--------------+----------------+--------------------+
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| | SID(133) | SID(134) | SID(135) |
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+=================+==============+================+====================+
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| price | $10.10 | $22.50 | $13.37 |
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+-----------------+--------------+----------------+--------------------+
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| volume | 10,000 | 5,000 | 50,000 |
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+-----------------+--------------+----------------+--------------------+
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| mvg_avg_30 | $9.97 | $22.61 | $13.37 |
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+-----------------+--------------+----------------+--------------------+
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| dt | 6/30/2012 | 6/30/2011 | 6/29/2012 |
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+-----------------+--------------+----------------+--------------------+
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- set_order: method that accepts a callable. Will be set as the value of the
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order method of trading_client. An algorithm can then place orders with a
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valid SID and a number of shares::
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self.order(SID(133), share_count)
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- set_performance: property which can be set equal to the
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cumulative_trading_performance property of the trading_client. An
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algorithm can then check position information with the
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Portfolio object::
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self.Portfolio[SID(133)]['cost_basis']
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"""
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import zipline.protocol as zp
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class TestAlgorithm():
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"""
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This algorithm will send a specified number of orders, to allow unit tests
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to verify the orders sent/received, transactions created, and positions
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at the close of a simulation.
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"""
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def __init__(self, sid, amount, order_count):
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self.count = order_count
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self.sid = sid
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self.amount = amount
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self.incr = 0
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self.done = False
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self.order = None
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self.frame_count = 0
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self.portfolio = None
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def initialize(self):
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pass
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def set_order(self, order_callable):
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self.order = order_callable
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def set_portfolio(self, portfolio):
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self.portfolio = portfolio
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def handle_frame(self, frame):
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self.frame_count += 1
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#place an order for 100 shares of sid
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if self.incr < self.count:
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self.order(self.sid, self.amount)
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self.incr += 1
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def get_sid_filter(self):
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return [self.sid]
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#
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class HeavyBuyAlgorithm():
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"""
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This algorithm will send a specified number of orders, to allow unit tests
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to verify the orders sent/received, transactions created, and positions
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at the close of a simulation.
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"""
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def __init__(self, sid, amount):
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self.sid = sid
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self.amount = amount
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self.incr = 0
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self.done = False
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self.order = None
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self.frame_count = 0
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self.portfolio = None
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def initialize(self):
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pass
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def set_order(self, order_callable):
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self.order = order_callable
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def set_portfolio(self, portfolio):
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self.portfolio = portfolio
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def handle_frame(self, frame):
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self.frame_count += 1
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#place an order for 100 shares of sid
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self.order(self.sid, self.amount)
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self.incr += 1
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def get_sid_filter(self):
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return [self.sid]
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class NoopAlgorithm(object):
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"""
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Dolce fa niente.
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"""
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def initialize(self):
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pass
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def set_order(self, order_callable):
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pass
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def set_portfolio(self, portfolio):
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pass
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def handle_frame(self, frame):
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pass
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def get_sid_filter(self):
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return None
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