Exemple #1
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    def init_engine(self, loader):
        """
        Construct and save an FFCEngine from loader.

        If loader is None, constructs a NoOpFFCEngine.
        """
        if loader is not None:
            self.engine = SimpleFFCEngine(
                loader,
                self.trading_environment.trading_days,
                self.asset_finder,
            )
        else:
            self.engine = NoOpFFCEngine()
Exemple #2
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    def __init__(self, *args, **kwargs):
        """Initialize sids and other state variables.

        :Arguments:
        :Optional:
            initialize : function
                Function that is called with a single
                argument at the begninning of the simulation.
            handle_data : function
                Function that is called with 2 arguments
                (context and data) on every bar.
            script : str
                Algoscript that contains initialize and
                handle_data function definition.
            data_frequency : {'daily', 'minute'}
               The duration of the bars.
            capital_base : float <default: 1.0e5>
               How much capital to start with.
            instant_fill : bool <default: False>
               Whether to fill orders immediately or on next bar.
            asset_finder : An AssetFinder object
                A new AssetFinder object to be used in this TradingEnvironment
            asset_metadata: can be either:
                            - dict
                            - pandas.DataFrame
                            - object with 'read' property
                If dict is provided, it must have the following structure:
                * keys are the identifiers
                * values are dicts containing the metadata, with the metadata
                  field name as the key
                If pandas.DataFrame is provided, it must have the
                following structure:
                * column names must be the metadata fields
                * index must be the different asset identifiers
                * array contents should be the metadata value
                If an object with a 'read' property is provided, 'read' must
                return rows containing at least one of 'sid' or 'symbol' along
                with the other metadata fields.
            identifiers : List
                Any asset identifiers that are not provided in the
                asset_metadata, but will be traded by this TradingAlgorithm
        """
        self.sources = []

        # List of trading controls to be used to validate orders.
        self.trading_controls = []

        # List of account controls to be checked on each bar.
        self.account_controls = []

        self._recorded_vars = {}
        self.namespace = kwargs.get('namespace', {})

        self._platform = kwargs.pop('platform', 'zipline')

        self.logger = None

        self.benchmark_return_source = None

        # default components for transact
        self.slippage = VolumeShareSlippage()
        self.commission = PerShare()

        self.instant_fill = kwargs.pop('instant_fill', False)

        # set the capital base
        self.capital_base = kwargs.pop('capital_base', DEFAULT_CAPITAL_BASE)

        self.sim_params = kwargs.pop('sim_params', None)
        if self.sim_params is None:
            self.sim_params = create_simulation_parameters(
                capital_base=self.capital_base,
                start=kwargs.pop('start', None),
                end=kwargs.pop('end', None))
        self.perf_tracker = PerformanceTracker(self.sim_params)

        # Update the TradingEnvironment with the provided asset metadata
        self.trading_environment = kwargs.pop('env',
                                              TradingEnvironment.instance())
        self.trading_environment.update_asset_finder(
            asset_finder=kwargs.pop('asset_finder', None),
            asset_metadata=kwargs.pop('asset_metadata', None),
            identifiers=kwargs.pop('identifiers', None))
        # Pull in the environment's new AssetFinder for quick reference
        self.asset_finder = self.trading_environment.asset_finder

        ffc_loader = kwargs.get('ffc_loader', None)
        if ffc_loader is not None:
            self.engine = SimpleFFCEngine(
                ffc_loader,
                self.trading_environment.trading_days,
                self.asset_finder,
            )
        else:
            self.engine = NoOpFFCEngine()

        # Maps from name to Term
        self._filters = {}
        self._factors = {}
        self._classifiers = {}

        self.blotter = kwargs.pop('blotter', None)
        if not self.blotter:
            self.blotter = Blotter()

        # Set the dt initally to the period start by forcing it to change
        self.on_dt_changed(self.sim_params.period_start)

        self.portfolio_needs_update = True
        self.account_needs_update = True
        self.performance_needs_update = True
        self._portfolio = None
        self._account = None

        self.history_container_class = kwargs.pop(
            'history_container_class',
            HistoryContainer,
        )
        self.history_container = None
        self.history_specs = {}

        # If string is passed in, execute and get reference to
        # functions.
        self.algoscript = kwargs.pop('script', None)

        self._initialize = None
        self._before_trading_start = None
        self._analyze = None

        self.event_manager = EventManager()

        if self.algoscript is not None:
            filename = kwargs.pop('algo_filename', None)
            if filename is None:
                filename = '<string>'
            code = compile(self.algoscript, filename, 'exec')
            exec_(code, self.namespace)
            self._initialize = self.namespace.get('initialize')
            if 'handle_data' not in self.namespace:
                raise ValueError('You must define a handle_data function.')
            else:
                self._handle_data = self.namespace['handle_data']

            self._before_trading_start = \
                self.namespace.get('before_trading_start')
            # Optional analyze function, gets called after run
            self._analyze = self.namespace.get('analyze')

        elif kwargs.get('initialize') and kwargs.get('handle_data'):
            if self.algoscript is not None:
                raise ValueError('You can not set script and \
                initialize/handle_data.')
            self._initialize = kwargs.pop('initialize')
            self._handle_data = kwargs.pop('handle_data')
            self._before_trading_start = kwargs.pop('before_trading_start',
                                                    None)

        self.event_manager.add_event(
            zipline.utils.events.Event(
                zipline.utils.events.Always(),
                # We pass handle_data.__func__ to get the unbound method.
                # We will explicitly pass the algorithm to bind it again.
                self.handle_data.__func__,
            ),
            prepend=True,
        )

        # If method not defined, NOOP
        if self._initialize is None:
            self._initialize = lambda x: None

        # Alternative way of setting data_frequency for backwards
        # compatibility.
        if 'data_frequency' in kwargs:
            self.data_frequency = kwargs.pop('data_frequency')

        self._most_recent_data = None

        # Prepare the algo for initialization
        self.initialized = False
        self.initialize_args = args
        self.initialize_kwargs = kwargs