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fawce
2c7355a0dc
Global state for the financial simulation environment is accessed through the
zipline.finance.trading module, which now contains a module variable:
environment.
Parameters are passed into an algorithm as a keyword argument, sim_params.
SimulationParameters creates a trading day index for the test period that
can be used to find trading days, calculate distance between trading days,
and other common operations. The sim params index is just selected from the
global state.
================
Details:
- adding delorean to the requirements.
- made index symbol a parameter for loading the benchmark data. changed
messagepack storage to be symbol specific.
- ported risk, performance, algorithm, transforms, batch transforms
and associated tests to use simulation parameters and global environment
- factory and sim factory use global state and sim params
- factory method parameter names now reflect the class expected
102 lines
3.1 KiB
Python
102 lines
3.1 KiB
Python
import zipline.utils.factory as factory
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from zipline.test_algorithms import TestAlgorithm
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def create_test_zipline(**config):
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"""
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:param config: A configuration object that is a dict with:
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- sid - an integer, which will be used as the security ID.
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- order_count - the number of orders the test algo will place,
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defaults to 100
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- order_amount - the number of shares per order, defaults to 100
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- trade_count - the number of trades to simulate, defaults to 101
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to ensure all orders are processed.
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- algorithm - optional parameter providing an algorithm. defaults
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to :py:class:`zipline.test.algorithms.TestAlgorithm`
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- trade_source - optional parameter to specify trades, if present.
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If not present :py:class:`zipline.sources.SpecificEquityTrades`
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is the source, with daily frequency in trades.
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- slippage: optional parameter that configures the
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:py:class:`zipline.gens.tradingsimulation.TransactionSimulator`.
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Expects an object with a simulate mehod, such as
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:py:class:`zipline.gens.tradingsimulation.FixedSlippage`.
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:py:mod:`zipline.finance.trading`
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- transforms: optional parameter that provides a list
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of StatefulTransform objects.
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"""
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assert isinstance(config, dict)
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sid_list = config.get('sid_list')
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if not sid_list:
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sid = config.get('sid')
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sid_list = [sid]
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concurrent_trades = config.get('concurrent_trades', False)
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if 'order_count' in config:
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order_count = config['order_count']
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else:
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order_count = 100
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if 'order_amount' in config:
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order_amount = config['order_amount']
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else:
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order_amount = 100
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if 'trade_count' in config:
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trade_count = config['trade_count']
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else:
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# to ensure all orders are filled, we provide one more
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# trade than order
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trade_count = 101
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#-------------------
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# Create the Algo
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#-------------------
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if 'algorithm' in config:
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test_algo = config['algorithm']
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else:
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test_algo = TestAlgorithm(
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sid,
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order_amount,
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order_count,
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sim_params=factory.create_simulation_parameters()
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)
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#-------------------
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# Trade Source
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#-------------------
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if 'trade_source' in config:
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trade_source = config['trade_source']
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else:
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trade_source = factory.create_daily_trade_source(
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sid_list,
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trade_count,
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test_algo.sim_params,
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concurrent=concurrent_trades
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)
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test_algo.set_sources([trade_source])
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#-------------------
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# Transforms
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#-------------------
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transforms = config.get('transforms', None)
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if transforms is not None:
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test_algo.set_transforms(transforms)
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#-------------------
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# Slippage
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# ------------------
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slippage = config.get('slippage', None)
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if slippage is not None:
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test_algo.set_slippage(slippage)
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# ------------------
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# generator/simulator
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sim = test_algo.get_generator()
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return sim
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