Files
catalyst/zipline/test_algorithms.py
T
Stephen Diehl d503ce465a Merge branch 'refactor'
Conflicts:
	zipline/finance/trading.py
	zipline/lines.py
2012-05-15 14:04:05 -04:00

140 lines
4.4 KiB
Python

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