Generated by Cython 0.29.36
Yellow lines hint at Python interaction.
Click on a line that starts with a "+" to see the C code that Cython generated for it.
Raw output: _protocol.c
+001: #
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002: # Copyright 2016 Quantopian, Inc.
003: #
004: # Licensed under the Apache License, Version 2.0 (the "License");
005: # you may not use this file except in compliance with the License.
006: # You may obtain a copy of the License at
007: #
008: # http://www.apache.org/licenses/LICENSE-2.0
009: #
010: # Unless required by applicable law or agreed to in writing, software
011: # distributed under the License is distributed on an "AS IS" BASIS,
012: # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
013: # See the License for the specific language governing permissions and
014: # limitations under the License.
+015: import warnings
__pyx_t_1 = __Pyx_Import(__pyx_n_s_warnings, 0, 0); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 15, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); if (PyDict_SetItem(__pyx_d, __pyx_n_s_warnings, __pyx_t_1) < 0) __PYX_ERR(0, 15, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
+016: from contextlib import contextmanager
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+017: from functools import wraps
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+018: import pandas as pd
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+019: import numpy as np
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020:
021: from cpython cimport bool
+022: from collections.abc import Iterable
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023:
+024: from zipline.assets import (
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+025: PricingDataAssociable,
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026: )
027: from zipline.assets._assets cimport Asset
+028: from zipline.assets.continuous_futures import ContinuousFuture
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+029: from zipline.utils.pandas_utils import normalize_date
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+030: from zipline.zipline_warnings import ZiplineDeprecationWarning
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031:
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196: """
197: Returns the "current" value of the given fields for the given assets
198: at the current simulation time.
199:
200: Parameters
201: ----------
202: assets : zipline.assets.Asset or iterable of zipline.assets.Asset
203: The asset(s) for which data is requested.
204: fields : str or iterable[str].
205: Requested data field(s). Valid field names are: "price",
206: "last_traded", "open", "high", "low", "close", and "volume".
207:
208: Returns
209: -------
210: current_value : Scalar, pandas Series, or pandas DataFrame.
211: See notes below.
212:
213: Notes
214: -----
215: The return type of this function depends on the types of its inputs:
216:
217: - If a single asset and a single field are requested, the returned
218: value is a scalar (either a float or a ``pd.Timestamp`` depending on
219: the field).
220:
221: - If a single asset and a list of fields are requested, the returned
222: value is a :class:`pd.Series` whose indices are the requested fields.
223:
224: - If a list of assets and a single field are requested, the returned
225: value is a :class:`pd.Series` whose indices are the assets.
226:
227: - If a list of assets and a list of fields are requested, the returned
228: value is a :class:`pd.DataFrame`. The columns of the returned frame
229: will be the requested fields, and the index of the frame will be the
230: requested assets.
231:
232: The values produced for ``fields`` are as follows:
233:
234: - Requesting "price" produces the last known close price for the asset,
235: forward-filled from an earlier minute if there is no trade this
236: minute. If there is no last known value (either because the asset
237: has never traded, or because it has delisted) NaN is returned. If a
238: value is found, and we had to cross an adjustment boundary (split,
239: dividend, etc) to get it, the value is adjusted to the current
240: simulation time before being returned.
241:
242: - Requesting "open", "high", "low", or "close" produces the open, high,
243: low, or close for the current minute. If no trades occurred this
244: minute, ``NaN`` is returned.
245:
246: - Requesting "volume" produces the trade volume for the current
247: minute. If no trades occurred this minute, 0 is returned.
248:
249: - Requesting "last_traded" produces the datetime of the last minute in
250: which the asset traded, even if the asset has stopped trading. If
251: there is no last known value, ``pd.NaT`` is returned.
252:
253: If the current simulation time is not a valid market time for an asset,
254: we use the most recent market close instead.
255: """
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258:
259: # There's some overly verbose code in here, particularly around
260: # 'do something if self._adjust_minutes is False, otherwise do
261: # something else'. This could be less verbose, but the 99% case is that
262: # `self._adjust_minutes` is False, so it's important to keep that code
263: # path as fast as possible.
264:
265: # There's probably a way to make this method (and `history`) less
266: # verbose, but this is OK for now.
267:
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383: """
384: For the given asset or iterable of assets, returns True if all of the
385: following are true:
386:
387: 1. The asset is alive for the session of the current simulation time
388: (if current simulation time is not a market minute, we use the next
389: session).
390: 2. The asset's exchange is open at the current simulation time or at
391: the simulation calendar's next market minute.
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393:
394: Parameters
395: ----------
396: assets: zipline.assets.Asset or iterable of zipline.assets.Asset
397: Asset(s) for which tradability should be determined.
398:
399: Notes
400: -----
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402:
403: - If the asset's exchange calendar is identical to the simulation
404: calendar, then this condition always returns True.
405: - If there are market minutes in the simulation calendar outside of
406: this asset's exchange's trading hours (for example, if the simulation
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409: (for example, 3:15 am Eastern on a weekday, during which the CMES is
410: open but the NYSE is closed).
411:
412: Returns
413: -------
414: can_trade : bool or pd.Series[bool]
415: Bool or series of bools indicating whether the requested asset(s)
416: can be traded in the current minute.
417: """
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439:
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546: """
547: Returns a trailing window of length ``bar_count`` with data for
548: the given assets, fields, and frequency, adjusted for splits, dividends,
549: and mergers as of the current simulation time.
550:
551: The semantics for missing data are identical to the ones described in
552: the notes for :meth:`current`.
553:
554: Parameters
555: ----------
556: assets: zipline.assets.Asset or iterable of zipline.assets.Asset
557: The asset(s) for which data is requested.
558: fields: string or iterable of string.
559: Requested data field(s). Valid field names are: "price",
560: "last_traded", "open", "high", "low", "close", and "volume".
561: bar_count: int
562: Number of data observations requested.
563: frequency: str
564: String indicating whether to load daily or minutely data
565: observations. Pass '1m' for minutely data, '1d' for daily data.
566:
567: Returns
568: -------
569: history : pd.Series or pd.DataFrame or pd.Panel
570: See notes below.
571:
572: Notes
573: -----
574: The return type of this function depends on the types of ``assets`` and
575: ``fields``:
576:
577: - If a single asset and a single field are requested, the returned
578: value is a :class:`pd.Series` of length ``bar_count`` whose index is
579: :class:`pd.DatetimeIndex`.
580:
581: - If a single asset and multiple fields are requested, the returned
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584: :class:`pd.DatetimeIndex`, and its columns will be ``fields``.
585:
586: - If multiple assets and a single field are requested, the returned
587: value is a :class:`pd.DataFrame` with shape
588: ``(bar_count, len(assets))``. The frame's index will be a
589: :class:`pd.DatetimeIndex`, and its columns will be ``assets``.
590:
591: - If multiple assets and multiple fields are requested, the returned
592: value is a :class:`pd.DataFrame` with a pd.MultiIndex containing pairs of
593: :class:`pd.DatetimeIndex`, and ``assets``, while the columns while contain the field(s).
594: It has shape``(bar_count * len(assets), len(fields))``. The names of the pd.MultiIndex are
595: - ``date`` if frequency == '1d'`` or ``date_time`` if frequency == '1m``, and
596: - ``asset``
597:
598: If the current simulation time is not a valid market time, we use the last market close instead.
599: """
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697: )
698:
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700: """The real values of a position.
701:
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704: :class:`zipline.protocol.Position` at the same time without a cycle.
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