mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-27 19:14:36 +08:00
DEV: Adds type hinting stub for zipline.api
as well as tooling and docs to generate this for each release Also moved Cython files to package_data, so that we install them, instead of just packaging them.
This commit is contained in:
Richard Frank
@@ -2,7 +2,5 @@ include LICENSE
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include etc/requirements*.txt
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recursive-include zipline/resources *.*
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recursive-include zipline *.pyx
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recursive-include zipline *.pxi
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include versioneer.py
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include zipline/_version.py
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@@ -27,6 +27,32 @@ update the underline of the title to match the title's width.
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If you are renaming the release at this point, you'll need to git mv the file
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and also update releases.rst to reference the renamed file.
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Updating the Python stub files
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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PyCharm and other linters and type checkers can use `Python stub files
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<https://www.python.org/dev/peps/pep-0484/#stub-files>`__ for type hinting. For
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example, we generate stub files for the :mod:`~zipline.api` namespace, since that
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namespace is populated at import time by decorators on TradingAlgorithm
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methods. Those functions are therefore hidden from static analysis tools, but
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we can generate static files to make them available. Under **Python 3**, run
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the following to generate any stub files:
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.. code-block:: bash
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$ python etc/gen_type_stubs.py
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.. note::
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In order to make stub consumers aware of the classes referred to in the
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stub, the stub file should import those classes. However, since
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``... import *`` and ``... import ... as ...`` in a stub file will export
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those imports, we import the names explicitly. For the stub for
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``zipline.api``, this is done in a header string in the
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``gen_type_stubs.py`` script mentioned above. If new classes are added as
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parameters or return types of ``zipline.api`` functions, then new imports
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should be added to that header.
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Updating the ``__version__``
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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@@ -0,0 +1,42 @@
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import inspect
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from operator import attrgetter
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from textwrap import dedent
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from zipline import api, TradingAlgorithm
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def main():
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with open(api.__file__.rstrip('c') + 'i', 'w') as stub:
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# Imports so that Asset et al can be resolved.
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# "from MOD import *" will re-export the imports from the stub, so
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# explicitly importing.
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stub.write(dedent("""\
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from zipline.assets import Asset, Equity, Future
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from zipline.assets.futures import FutureChain
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from zipline.finance.cancel_policy import CancelPolicy
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from zipline.pipeline import Pipeline
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from zipline.protocol import Order
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from zipline.utils.events import EventRule
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"""))
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# Sort to generate consistent stub file:
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for api_func in sorted(TradingAlgorithm.all_api_methods(),
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key=attrgetter('__name__')):
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sig = inspect._signature_bound_method(inspect.signature(api_func))
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indent = ' ' * 4
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stub.write(dedent('''\
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def {func_name}{func_sig}:
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"""'''.format(func_name=api_func.__name__,
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func_sig=sig)))
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stub.write(dedent('{indent}{func_doc}'.format(
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func_doc=api_func.__doc__ or '\n', # handle None docstring
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indent=indent,
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)))
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stub.write('{indent}"""\n\n'.format(indent=indent))
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if __name__ == '__main__':
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main()
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@@ -270,9 +270,13 @@ setup(
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},
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author='Quantopian Inc.',
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author_email='opensource@quantopian.com',
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packages=find_packages('.', include=['zipline', 'zipline.*']),
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packages=find_packages(include=['zipline', 'zipline.*']),
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ext_modules=ext_modules,
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include_package_data=True,
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package_data={root.replace(os.sep, '.'):
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['*.pyi', '*.pyx', '*.pxi', '*.pxd']
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for root, dirnames, filenames in os.walk('zipline')
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if '__pycache__' not in root},
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license='Apache 2.0',
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classifiers=[
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'Development Status :: 4 - Beta',
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+688
@@ -0,0 +1,688 @@
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from zipline.assets import Asset, Equity, Future
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from zipline.assets.futures import FutureChain
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from zipline.finance.cancel_policy import CancelPolicy
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from zipline.pipeline import Pipeline
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from zipline.protocol import Order
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from zipline.utils.events import EventRule
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def attach_pipeline(pipeline, name, chunksize=None):
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"""Register a pipeline to be computed at the start of each day.
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Parameters
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----------
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pipeline : Pipeline
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The pipeline to have computed.
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name : str
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The name of the pipeline.
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chunksize : int, optional
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The number of days to compute pipeline results for. Increasing
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this number will make it longer to get the first results but
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may improve the total runtime of the simulation.
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Returns
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-------
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pipeline : Pipeline
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Returns the pipeline that was attached unchanged.
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See Also
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--------
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:func:`zipline.api.pipeline_output`
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"""
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def cancel_order(order_param):
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"""Cancel an open order.
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Parameters
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----------
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order_param : str or Order
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The order_id or order object to cancel.
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"""
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def fetch_csv(url, pre_func=None, post_func=None, date_column='date', date_format=None, timezone='UTC', symbol=None, mask=True, symbol_column=None, special_params_checker=None, **kwargs):
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"""Fetch a csv from a remote url and register the data so that it is
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queryable from the ``data`` object.
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Parameters
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----------
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url : str
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The url of the csv file to load.
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pre_func : callable[pd.DataFrame -> pd.DataFrame], optional
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A callback to allow preprocessing the raw data returned from
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fetch_csv before dates are paresed or symbols are mapped.
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post_func : callable[pd.DataFrame -> pd.DataFrame], optional
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A callback to allow postprocessing of the data after dates and
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symbols have been mapped.
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date_column : str, optional
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The name of the column in the preprocessed dataframe containing
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datetime information to map the data.
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date_format : str, optional
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The format of the dates in the ``date_column``. If not provided
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``fetch_csv`` will attempt to infer the format. For information
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about the format of this string, see :func:`pandas.read_csv`.
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timezone : tzinfo or str, optional
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The timezone for the datetime in the ``date_column``.
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symbol : str, optional
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If the data is about a new asset or index then this string will
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be the name used to identify the values in ``data``. For example,
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one may use ``fetch_csv`` to load data for VIX, then this field
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could be the string ``'VIX'``.
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mask : bool, optional
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Drop any rows which cannot be symbol mapped.
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symbol_column : str
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If the data is attaching some new attribute to each asset then this
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argument is the name of the column in the preprocessed dataframe
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containing the symbols. This will be used along with the date
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information to map the sids in the asset finder.
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**kwargs
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Forwarded to :func:`pandas.read_csv`.
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Returns
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-------
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csv_data_source : zipline.sources.requests_csv.PandasRequestsCSV
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A requests source that will pull data from the url specified.
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"""
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def future_chain(root_symbol, as_of_date=None):
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"""Look up a future chain with the specified parameters.
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Parameters
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----------
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root_symbol : str
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The root symbol of a future chain.
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as_of_date : datetime.datetime or pandas.Timestamp or str, optional
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Date at which the chain determination is rooted. I.e. the
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existing contract whose notice date is first after this date is
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the primary contract, etc.
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Returns
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-------
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chain : FutureChain
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The future chain matching the specified parameters.
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Raises
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------
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RootSymbolNotFound
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If a future chain could not be found for the given root symbol.
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"""
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def future_symbol(symbol):
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"""Lookup a futures contract with a given symbol.
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Parameters
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----------
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symbol : str
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The symbol of the desired contract.
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Returns
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-------
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future : Future
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The future that trades with the name ``symbol``.
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Raises
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------
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SymbolNotFound
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Raised when no contract named 'symbol' is found.
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"""
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def get_datetime(tz=None):
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"""Returns the current simulation datetime.
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Parameters
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----------
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tz : tzinfo or str, optional
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The timezone to return the datetime in. This defaults to utc.
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Returns
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-------
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dt : datetime
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The current simulation datetime converted to ``tz``.
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"""
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def get_environment(field='platform'):
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"""Query the execution environment.
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Parameters
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----------
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field : {'platform', 'arena', 'data_frequency',
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'start', 'end', 'capital_base', 'platform', '*'}
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The field to query. The options have the following meanings:
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arena : str
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The arena from the simulation parameters. This will normally
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be ``'backtest'`` but some systems may use this distinguish
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live trading from backtesting.
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data_frequency : {'daily', 'minute'}
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data_frequency tells the algorithm if it is running with
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daily data or minute data.
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start : datetime
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The start date for the simulation.
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end : datetime
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The end date for the simulation.
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capital_base : float
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The starting capital for the simulation.
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platform : str
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The platform that the code is running on. By default this
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will be the string 'zipline'. This can allow algorithms to
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know if they are running on the Quantopian platform instead.
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* : dict[str -> any]
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Returns all of the fields in a dictionary.
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Returns
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-------
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val : any
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The value for the field queried. See above for more information.
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Raises
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------
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ValueError
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Raised when ``field`` is not a valid option.
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"""
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def get_order(order_id):
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"""Lookup an order based on the order id returned from one of the
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order functions.
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Parameters
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----------
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order_id : str
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The unique identifier for the order.
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Returns
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-------
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order : Order
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The order object.
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"""
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def history(bar_count, frequency, field, ffill=True):
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"""DEPRECATED: use ``data.history`` instead.
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"""
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def order(asset, amount, limit_price=None, stop_price=None, style=None):
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"""Place an order.
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Parameters
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----------
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asset : Asset
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The asset that this order is for.
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amount : int
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The amount of shares to order. If ``amount`` is positive, this is
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the number of shares to buy or cover. If ``amount`` is negative,
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this is the number of shares to sell or short.
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style : ExecutionStyle, optional
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The execution style for the order.
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Returns
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-------
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order_id : str
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The unique identifier for this order.
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See Also
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--------
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:class:`zipline.finance.execution.ExecutionStyle`
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:func:`zipline.api.order_value`
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:func:`zipline.api.order_percent`
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"""
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def order_percent(asset, percent, limit_price=None, stop_price=None, style=None):
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"""Place an order in the specified asset corresponding to the given
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percent of the current portfolio value.
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Parameters
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----------
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asset : Asset
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The asset that this order is for.
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percent : float
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The percentage of the porfolio value to allocate to ``asset``.
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This is specified as a decimal, for example: 0.50 means 50%.
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style : ExecutionStyle
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The execution style for the order.
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Returns
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-------
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order_id : str
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The unique identifier for this order.
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See Also
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--------
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:class:`zipline.finance.execution.ExecutionStyle`
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:func:`zipline.api.order`
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:func:`zipline.api.order_value`
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"""
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def order_target(asset, target, limit_price=None, stop_price=None, style=None):
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"""Place an order to adjust a position to a target number of shares. If
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the position doesn't already exist, this is equivalent to placing a new
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order. If the position does exist, this is equivalent to placing an
|
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order for the difference between the target number of shares and the
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current number of shares.
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Parameters
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----------
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asset : Asset
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The asset that this order is for.
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target : int
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The desired number of shares of ``asset``.
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style : ExecutionStyle
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The execution style for the order.
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Returns
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-------
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order_id : str
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The unique identifier for this order.
|
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Notes
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-----
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``order_target`` does not take into account any open orders. For
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example:
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.. code-block:: python
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order_target(sid(0), 10)
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order_target(sid(0), 10)
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This code will result in 20 shares of ``sid(0)`` because the first
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call to ``order_target`` will not have been filled when the second
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``order_target`` call is made.
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See Also
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--------
|
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:class:`zipline.finance.execution.ExecutionStyle`
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:func:`zipline.api.order`
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:func:`zipline.api.order_target_percent`
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:func:`zipline.api.order_target_value`
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"""
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def order_target_percent(asset, target, limit_price=None, stop_price=None, style=None):
|
||||
"""Place an order to adjust a position to a target percent of the
|
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current portfolio value. If the position doesn't already exist, this is
|
||||
equivalent to placing a new order. If the position does exist, this is
|
||||
equivalent to placing an order for the difference between the target
|
||||
percent and the current percent.
|
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|
||||
Parameters
|
||||
----------
|
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asset : Asset
|
||||
The asset that this order is for.
|
||||
percent : float
|
||||
The desired percentage of the porfolio value to allocate to
|
||||
``asset``. This is specified as a decimal, for example:
|
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0.50 means 50%.
|
||||
style : ExecutionStyle
|
||||
The execution style for the order.
|
||||
|
||||
Returns
|
||||
-------
|
||||
order_id : str
|
||||
The unique identifier for this order.
|
||||
|
||||
Notes
|
||||
-----
|
||||
``order_target_value`` does not take into account any open orders. For
|
||||
example:
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
order_target_percent(sid(0), 10)
|
||||
order_target_percent(sid(0), 10)
|
||||
|
||||
This code will result in 20% of the portfolio being allocated to sid(0)
|
||||
because the first call to ``order_target_percent`` will not have been
|
||||
filled when the second ``order_target_percent`` call is made.
|
||||
|
||||
See Also
|
||||
--------
|
||||
:class:`zipline.finance.execution.ExecutionStyle`
|
||||
:func:`zipline.api.order`
|
||||
:func:`zipline.api.order_target`
|
||||
:func:`zipline.api.order_target_value`
|
||||
"""
|
||||
|
||||
def order_target_value(asset, target, limit_price=None, stop_price=None, style=None):
|
||||
"""Place an order to adjust a position to a target value. If
|
||||
the position doesn't already exist, this is equivalent to placing a new
|
||||
order. If the position does exist, this is equivalent to placing an
|
||||
order for the difference between the target value and the
|
||||
current value.
|
||||
If the Asset being ordered is a Future, the 'target value' calculated
|
||||
is actually the target exposure, as Futures have no 'value'.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
asset : Asset
|
||||
The asset that this order is for.
|
||||
target : float
|
||||
The desired total value of ``asset``.
|
||||
style : ExecutionStyle
|
||||
The execution style for the order.
|
||||
|
||||
Returns
|
||||
-------
|
||||
order_id : str
|
||||
The unique identifier for this order.
|
||||
|
||||
Notes
|
||||
-----
|
||||
``order_target_value`` does not take into account any open orders. For
|
||||
example:
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
order_target_value(sid(0), 10)
|
||||
order_target_value(sid(0), 10)
|
||||
|
||||
This code will result in 20 dollars of ``sid(0)`` because the first
|
||||
call to ``order_target_value`` will not have been filled when the
|
||||
second ``order_target_value`` call is made.
|
||||
|
||||
See Also
|
||||
--------
|
||||
:class:`zipline.finance.execution.ExecutionStyle`
|
||||
:func:`zipline.api.order`
|
||||
:func:`zipline.api.order_target`
|
||||
:func:`zipline.api.order_target_percent`
|
||||
"""
|
||||
|
||||
def order_value(asset, value, limit_price=None, stop_price=None, style=None):
|
||||
"""Place an order by desired value rather than desired number of
|
||||
shares.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
asset : Asset
|
||||
The asset that this order is for.
|
||||
value : float
|
||||
If the requested asset exists, the requested value is
|
||||
divided by its price to imply the number of shares to transact.
|
||||
If the Asset being ordered is a Future, the 'value' calculated
|
||||
is actually the exposure, as Futures have no 'value'.
|
||||
|
||||
value > 0 :: Buy/Cover
|
||||
value < 0 :: Sell/Short
|
||||
style : ExecutionStyle
|
||||
The execution style for the order.
|
||||
|
||||
Returns
|
||||
-------
|
||||
order_id : str
|
||||
The unique identifier for this order.
|
||||
|
||||
See Also
|
||||
--------
|
||||
:class:`zipline.finance.execution.ExecutionStyle`
|
||||
:func:`zipline.api.order`
|
||||
:func:`zipline.api.order_percent`
|
||||
"""
|
||||
|
||||
def pipeline_output(name):
|
||||
"""Get the results of the pipeline that was attached with the name:
|
||||
``name``.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
name : str
|
||||
Name of the pipeline for which results are requested.
|
||||
|
||||
Returns
|
||||
-------
|
||||
results : pd.DataFrame
|
||||
DataFrame containing the results of the requested pipeline for
|
||||
the current simulation date.
|
||||
|
||||
Raises
|
||||
------
|
||||
NoSuchPipeline
|
||||
Raised when no pipeline with the name `name` has been registered.
|
||||
|
||||
See Also
|
||||
--------
|
||||
:func:`zipline.api.attach_pipeline`
|
||||
:meth:`zipline.pipeline.engine.PipelineEngine.run_pipeline`
|
||||
"""
|
||||
|
||||
def record(*args, **kwargs):
|
||||
"""Track and record values each day.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
**kwargs
|
||||
The names and values to record.
|
||||
|
||||
Notes
|
||||
-----
|
||||
These values will appear in the performance packets and the performance
|
||||
dataframe passed to ``analyze`` and returned from
|
||||
:func:`~zipline.run_algorithm`.
|
||||
"""
|
||||
|
||||
def schedule_function(func, date_rule=None, time_rule=None, half_days=True):
|
||||
"""Schedules a function to be called according to some timed rules.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
func : callable[(context, data) -> None]
|
||||
The function to execute when the rule is triggered.
|
||||
date_rule : EventRule, optional
|
||||
The rule for the dates to execute this function.
|
||||
time_rule : EventRule, optional
|
||||
The rule for the times to execute this function.
|
||||
half_days : bool, optional
|
||||
Should this rule fire on half days?
|
||||
|
||||
See Also
|
||||
--------
|
||||
:class:`zipline.api.date_rules`
|
||||
:class:`zipline.api.time_rules`
|
||||
"""
|
||||
|
||||
def set_benchmark(benchmark):
|
||||
"""Set the benchmark asset.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
benchmark : Asset
|
||||
The asset to set as the new benchmark.
|
||||
|
||||
Notes
|
||||
-----
|
||||
Any dividends payed out for that new benchmark asset will be
|
||||
automatically reinvested.
|
||||
"""
|
||||
|
||||
def set_cancel_policy(cancel_policy):
|
||||
"""Sets the order cancellation policy for the simulation.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
cancel_policy : CancelPolicy
|
||||
The cancellation policy to use.
|
||||
|
||||
See Also
|
||||
--------
|
||||
:class:`zipline.api.EODCancel`
|
||||
:class:`zipline.api.NeverCancel`
|
||||
"""
|
||||
|
||||
def set_commission(commission):
|
||||
"""Sets the commision model for the simulation.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
commision : PerShare, PerTrade, or PerDollar
|
||||
The commision model to use.
|
||||
|
||||
See Also
|
||||
--------
|
||||
:class:`zipline.finance.commission.PerShare`
|
||||
:class:`zipline.finance.commission.PerTrade`
|
||||
:class:`zipline.finance.commission.PerDollar`
|
||||
"""
|
||||
|
||||
def set_do_not_order_list(restricted_list):
|
||||
"""Set a restriction on which assets can be ordered.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
restricted_list : container[Asset]
|
||||
The assets that cannot be ordered.
|
||||
"""
|
||||
|
||||
def set_long_only():
|
||||
"""Set a rule specifying that this algorithm cannot take short
|
||||
positions.
|
||||
"""
|
||||
|
||||
def set_max_leverage(max_leverage):
|
||||
"""Set a limit on the maximum leverage of the algorithm.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
max_leverage : float
|
||||
The maximum leverage for the algorithm. If not provided there will
|
||||
be no maximum.
|
||||
"""
|
||||
|
||||
def set_max_order_count(max_count):
|
||||
"""Set a limit on the number of orders that can be placed in a single
|
||||
day.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
max_count : int
|
||||
The maximum number of orders that can be placed on any single day.
|
||||
"""
|
||||
|
||||
def set_max_order_size(asset=None, max_shares=None, max_notional=None):
|
||||
"""Set a limit on the number of shares and/or dollar value of any single
|
||||
order placed for sid. Limits are treated as absolute values and are
|
||||
enforced at the time that the algo attempts to place an order for sid.
|
||||
|
||||
If an algorithm attempts to place an order that would result in
|
||||
exceeding one of these limits, raise a TradingControlException.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
asset : Asset, optional
|
||||
If provided, this sets the guard only on positions in the given
|
||||
asset.
|
||||
max_shares : int, optional
|
||||
The maximum number of shares that can be ordered at one time.
|
||||
max_notional : float, optional
|
||||
The maximum value that can be ordered at one time.
|
||||
"""
|
||||
|
||||
def set_max_position_size(asset=None, max_shares=None, max_notional=None):
|
||||
"""Set a limit on the number of shares and/or dollar value held for the
|
||||
given sid. Limits are treated as absolute values and are enforced at
|
||||
the time that the algo attempts to place an order for sid. This means
|
||||
that it's possible to end up with more than the max number of shares
|
||||
due to splits/dividends, and more than the max notional due to price
|
||||
improvement.
|
||||
|
||||
If an algorithm attempts to place an order that would result in
|
||||
increasing the absolute value of shares/dollar value exceeding one of
|
||||
these limits, raise a TradingControlException.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
asset : Asset, optional
|
||||
If provided, this sets the guard only on positions in the given
|
||||
asset.
|
||||
max_shares : int, optional
|
||||
The maximum number of shares to hold for an asset.
|
||||
max_notional : float, optional
|
||||
The maximum value to hold for an asset.
|
||||
"""
|
||||
|
||||
def set_slippage(slippage):
|
||||
"""Set the slippage model for the simulation.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
slippage : SlippageModel
|
||||
The slippage model to use.
|
||||
|
||||
See Also
|
||||
--------
|
||||
:class:`zipline.finance.slippage.SlippageModel`
|
||||
"""
|
||||
|
||||
def set_symbol_lookup_date(dt):
|
||||
"""Set the date for which symbols will be resolved to their assets
|
||||
(symbols may map to different firms or underlying assets at
|
||||
different times)
|
||||
|
||||
Parameters
|
||||
----------
|
||||
dt : datetime
|
||||
The new symbol lookup date.
|
||||
"""
|
||||
|
||||
def sid(sid):
|
||||
"""Lookup an Asset by its unique asset identifier.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
sid : int
|
||||
The unique integer that identifies an asset.
|
||||
|
||||
Returns
|
||||
-------
|
||||
asset : Asset
|
||||
The asset with the given ``sid``.
|
||||
|
||||
Raises
|
||||
------
|
||||
SidsNotFound
|
||||
When a requested ``sid`` does not map to any asset.
|
||||
"""
|
||||
|
||||
def symbol(symbol_str):
|
||||
"""Lookup an Equity by its ticker symbol.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbol_str : str
|
||||
The ticker symbol for the equity to lookup.
|
||||
|
||||
Returns
|
||||
-------
|
||||
equity : Equity
|
||||
The equity that held the ticker symbol on the current
|
||||
symbol lookup date.
|
||||
|
||||
Raises
|
||||
------
|
||||
SymbolNotFound
|
||||
Raised when the symbols was not held on the current lookup date.
|
||||
|
||||
See Also
|
||||
--------
|
||||
:func:`zipline.api.set_symbol_lookup_date`
|
||||
"""
|
||||
|
||||
def symbols(*args):
|
||||
"""Lookup multuple Equities as a list.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
*args : iterable[str]
|
||||
The ticker symbols to lookup.
|
||||
|
||||
Returns
|
||||
-------
|
||||
equities : list[Equity]
|
||||
The equities that held the given ticker symbols on the current
|
||||
symbol lookup date.
|
||||
|
||||
Raises
|
||||
------
|
||||
SymbolNotFound
|
||||
Raised when one of the symbols was not held on the current
|
||||
lookup date.
|
||||
|
||||
See Also
|
||||
--------
|
||||
:func:`zipline.api.set_symbol_lookup_date`
|
||||
"""
|
||||
|
||||
Reference in New Issue
Block a user