rqalpha之api_base.py

梦里梦外; 2021-11-17 17:54 186阅读 0赞

###  **对国内量化平台进行解析** ###

# -*- coding: utf-8 -*-
    #
    # Copyright 2019 Ricequant, Inc
    #
    # * Commercial Usage: please contact public@ricequant.com
    # * Non-Commercial Usage:
    #     Licensed under the Apache License, Version 2.0 (the "License");
    #     you may not use this file except in compliance with the License.
    #     You may obtain a copy of the License at
    #
    #         http://www.apache.org/licenses/LICENSE-2.0
    #
    #     Unless required by applicable law or agreed to in writing, software
    #     distributed under the License is distributed on an "AS IS" BASIS,
    #     WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    #     See the License for the specific language governing permissions and
    #     limitations under the License.
    
    from __future__ import division
    
    import datetime  
    import inspect
    import sys
    import types
    from collections import Iterable
    from functools import wraps
    from types import FunctionType
    
    import pandas as pd
    import numpy as np
    import six
    from dateutil.parser import parse
    
    from rqalpha.api import names
    from rqalpha.environment import Environment
    from rqalpha.execution_context import ExecutionContext
    from rqalpha.utils import to_industry_code, to_sector_name, unwrapper, is_valid_price
    from rqalpha.utils.exception import (
        patch_user_exc,
        patch_system_exc,
        EXC_EXT_NAME,
        RQInvalidArgument,
    )
    from rqalpha.utils.i18n import gettext as _
    
    # noinspection PyUnresolvedReferences
    from rqalpha.utils.logger import user_log as logger
    from rqalpha.utils.logger import user_system_log
    
    from rqalpha.model.instrument import SectorCodeItem, IndustryCodeItem
    from rqalpha.utils.arg_checker import apply_rules, verify_that
    
    # noinspection PyUnresolvedReferences
    from rqalpha.model.instrument import (
        Instrument,
        SectorCode as sector_code,
        IndustryCode as industry_code,
    )
    
    # noinspection PyUnresolvedReferences
    from rqalpha.const import (
        EXECUTION_PHASE,
        EXC_TYPE,
        ORDER_STATUS,
        SIDE,
        POSITION_EFFECT,
        ORDER_TYPE,
        MATCHING_TYPE,
        RUN_TYPE,
        POSITION_DIRECTION,
    )
    
    # noinspection PyUnresolvedReferences
    from rqalpha.model.order import Order, MarketOrder, LimitOrder, OrderStyle
    
    # noinspection PyUnresolvedReferences
    from rqalpha.events import EVENT
    
    
    __all__ = [
        "logger",
        "sector_code",
        "industry_code",
        "LimitOrder",
        "MarketOrder",
        "ORDER_STATUS",
        "SIDE",
        "POSITION_EFFECT",
        "POSITION_DIRECTION",
        "ORDER_TYPE",
        "RUN_TYPE",
        "MATCHING_TYPE",
        "EVENT",
    ]
    
    
    def decorate_api_exc(func):
        f = func
        exception_checked = False
        while True:
            if getattr(f, "_rq_exception_checked", False):
                exception_checked = True
                break
    
            f = getattr(f, "__wrapped__", None)
            if f is None:
                break
        if not exception_checked:
            func = api_exc_patch(func)
    
        return func
    
    
    def api_exc_patch(func):
        if isinstance(func, FunctionType):
    
            @wraps(func)
            def deco(*args, **kwargs):
                try:
                    return func(*args, **kwargs)
                except RQInvalidArgument:
                    raise
                except Exception as e:
                    if isinstance(e, TypeError):
                        exc_info = sys.exc_info()
                        try:
                            ret = inspect.getcallargs(unwrapper(func), *args, **kwargs)
                        except TypeError:
                            t, v, tb = exc_info
                            raise patch_user_exc(v.with_traceback(tb))
    
                    if getattr(e, EXC_EXT_NAME, EXC_TYPE.NOTSET) == EXC_TYPE.NOTSET:
                        patch_system_exc(e)
    
                    raise
    
            return deco
        return func
    
    
    def register_api(name, func):
        globals()[name] = func
        __all__.append(name)
    
    
    def export_as_api(func):
        __all__.append(func.__name__)
    
        if isinstance(func, FunctionType):
            func = decorate_api_exc(func)
        globals()[func.__name__] = func
    
        return func
    
    
    def assure_order_book_id(id_or_ins):
        if isinstance(id_or_ins, Instrument):
            order_book_id = id_or_ins.order_book_id
        elif isinstance(id_or_ins, six.string_types):
            order_book_id = (
                Environment.get_instance().data_proxy.instruments(id_or_ins).order_book_id
            )
        else:
            raise RQInvalidArgument(_(u"unsupported order_book_id type"))
    
        return order_book_id
    
    
    def cal_style(price, style):
        if price is None and style is None:
            return MarketOrder()
    
        if style is not None:
            if not isinstance(style, OrderStyle):
                raise RuntimeError
            return style
    
        if isinstance(price, OrderStyle):
            # 为了 order_xxx('RB1710', 10, MarketOrder()) 这种写法
            if isinstance(price, LimitOrder):
                if np.isnan(price.get_limit_price()):
                    raise RQInvalidArgument(_(u"Limit order price should not be nan."))
            return price
    
        if np.isnan(price):
            raise RQInvalidArgument(_(u"Limit order price should not be nan."))
    
        return LimitOrder(price)
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    def get_order(order):
        return order
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    def get_open_orders():
        """
        获取当日未成交订单数据
    
        :return: List[:class:`~Order` object]
        """
        return Environment.get_instance().broker.get_open_orders()
    
    
    @export_as_api
    @apply_rules(
        verify_that("id_or_ins").is_valid_instrument(),
        verify_that("amount").is_number().is_greater_than(0),
        verify_that("side").is_in([SIDE.BUY, SIDE.SELL]),
    )
    def submit_order(id_or_ins, amount, side, price=None, position_effect=None):
        """
        通用下单函数，策略可以通过该函数自由选择参数下单。
    
        :param id_or_ins: 下单标的物
        :type id_or_ins: :class:`~Instrument` object | `str`
    
        :param float amount: 下单量，需为正数
    
        :param side: 多空方向，多（SIDE.BUY）或空（SIDE.SELL）
        :type side: :class:`~SIDE` enum
    
        :param float price: 下单价格，默认为None，表示市价单
    
        :param position_effect: 开平方向，开仓（POSITION_EFFECT.OPEN），平仓（POSITION.CLOSE）或平今（POSITION_EFFECT.CLOSE_TODAY），交易股票不需要该参数
        :type position_effect: :class:`~POSITION_EFFECT` enum
    
        :return: :class:`~Order` object | None
    
        :example:
    
        .. code-block:: python
    
            # 购买 2000 股的平安银行股票，并以市价单发送：
            submit_order('000001.XSHE', 2000, SIDE.BUY)
            # 平 10 份 RB1812 多方向的今仓，并以 4000 的价格发送限价单
            submit_order('RB1812', 10, SIDE.SELL, price=4000, position_effect=POSITION_EFFECT.CLOSE_TODAY)
    
        """
        order_book_id = assure_order_book_id(id_or_ins)
        env = Environment.get_instance()
        if (
            env.config.base.run_type != RUN_TYPE.BACKTEST
            and env.get_instrument(order_book_id).type == "Future"
        ):
            if "88" in order_book_id:
                raise RQInvalidArgument(
                    _(u"Main Future contracts[88] are not supported in paper trading.")
                )
            if "99" in order_book_id:
                raise RQInvalidArgument(
                    _(u"Index Future contracts[99] are not supported in paper trading.")
                )
        style = cal_style(price, None)
        market_price = env.get_last_price(order_book_id)
        if not is_valid_price(market_price):
            user_system_log.warn(
                _(u"Order Creation Failed: [{order_book_id}] No market data").format(
                    order_book_id=order_book_id
                )
            )
            return
    
        amount = int(amount)
    
        order = Order.__from_create__(
            order_book_id=order_book_id,
            quantity=amount,
            side=side,
            style=style,
            position_effect=position_effect,
        )
    
        if order.type == ORDER_TYPE.MARKET:
            order.set_frozen_price(market_price)
        if env.can_submit_order(order):
            env.broker.submit_order(order)
            return order
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
        EXECUTION_PHASE.GLOBAL,
    )
    @apply_rules(verify_that("order").is_instance_of(Order))
    def cancel_order(order):
        """
        撤单
    
        :param order: 需要撤销的order对象
        :type order: :class:`~Order` object
        """
        env = Environment.get_instance()
        if env.can_cancel_order(order):
            env.broker.cancel_order(order)
        return order
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(verify_that("id_or_symbols").are_valid_instruments())
    def update_universe(id_or_symbols):
        """
        该方法用于更新现在关注的证券的集合（e.g.：股票池）。PS：会在下一个bar事件触发时候产生（新的关注的股票池更新）效果。并且update_universe会是覆盖（overwrite）的操作而不是在已有的股票池的基础上进行增量添加。比如已有的股票池为['000001.XSHE', '000024.XSHE']然后调用了update_universe(['000030.XSHE'])之后，股票池就会变成000030.XSHE一个股票了，随后的数据更新也只会跟踪000030.XSHE这一个股票了。
    
        :param id_or_symbols: 标的物
        :type id_or_symbols: :class:`~Instrument` object | `str` | List[:class:`~Instrument`] | List[`str`]
        """
        if isinstance(id_or_symbols, (six.string_types, Instrument)):
            id_or_symbols = [id_or_symbols]
        order_book_ids = set(
            assure_order_book_id(order_book_id) for order_book_id in id_or_symbols
        )
        if order_book_ids != Environment.get_instance().get_universe():
            Environment.get_instance().update_universe(order_book_ids)
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(verify_that("id_or_symbols").are_valid_instruments())
    def subscribe(id_or_symbols):
        """
        订阅合约行情。该操作会导致合约池内合约的增加，从而影响handle_bar中处理bar数据的数量。
    
        需要注意，用户在初次编写策略时候需要首先订阅合约行情，否则handle_bar不会被触发。
    
        :param id_or_symbols: 标的物
        :type id_or_symbols: :class:`~Instrument` object | `str` | List[:class:`~Instrument`] | List[`str`]
        """
        current_universe = Environment.get_instance().get_universe()
        if isinstance(id_or_symbols, six.string_types):
            order_book_id = instruments(id_or_symbols).order_book_id
            current_universe.add(order_book_id)
        elif isinstance(id_or_symbols, Instrument):
            current_universe.add(id_or_symbols.order_book_id)
        elif isinstance(id_or_symbols, Iterable):
            for item in id_or_symbols:
                current_universe.add(assure_order_book_id(item))
        else:
            raise RQInvalidArgument(_(u"unsupported order_book_id type"))
        verify_that("id_or_symbols")._are_valid_instruments("subscribe", id_or_symbols)
        Environment.get_instance().update_universe(current_universe)
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(verify_that("id_or_symbols").are_valid_instruments())
    def unsubscribe(id_or_symbols):
        """
        取消订阅合约行情。取消订阅会导致合约池内合约的减少，如果当前合约池中没有任何合约，则策略直接退出。
    
        :param id_or_symbols: 标的物
        :type id_or_symbols: :class:`~Instrument` object | `str` | List[:class:`~Instrument`] | List[`str`]
        """
        current_universe = Environment.get_instance().get_universe()
        if isinstance(id_or_symbols, six.string_types):
            order_book_id = instruments(id_or_symbols).order_book_id
            current_universe.discard(order_book_id)
        elif isinstance(id_or_symbols, Instrument):
            current_universe.discard(id_or_symbols.order_book_id)
        elif isinstance(id_or_symbols, Iterable):
            for item in id_or_symbols:
                i = assure_order_book_id(item)
                current_universe.discard(i)
        else:
            raise RQInvalidArgument(_(u"unsupported order_book_id type"))
    
        Environment.get_instance().update_universe(current_universe)
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(
        verify_that("date").is_valid_date(ignore_none=True),
        verify_that("tenor").is_in(names.VALID_TENORS, ignore_none=True),
    )
    def get_yield_curve(date=None, tenor=None):
        """
        获取某个国家市场指定日期的收益率曲线水平。
    
        数据为2002年至今的中债国债收益率曲线，来源于中央国债登记结算有限责任公司。
    
        :param date: 查询日期，默认为策略当前日期前一天
        :type date: `str` | `date` | `datetime` | `pandas.Timestamp`
    
        :param str tenor: 标准期限，'0S' - 隔夜，'1M' - 1个月，'1Y' - 1年，默认为全部期限
    
        :return: `pandas.DataFrame` - 查询时间段内无风险收益率曲线
    
        :example:
    
        ..  code-block:: python3
            :linenos:
    
            [In]
            get_yield_curve('20130104')
    
            [Out]
                            0S      1M      2M      3M      6M      9M      1Y      2Y  \
            2013-01-04  0.0196  0.0253  0.0288  0.0279  0.0280  0.0283  0.0292  0.0310
    
                            3Y      4Y   ...        6Y      7Y      8Y      9Y     10Y  \
            2013-01-04  0.0314  0.0318   ...    0.0342  0.0350  0.0353  0.0357  0.0361
            ...
        """
        env = Environment.get_instance()
        trading_date = env.trading_dt.date()
        yesterday = env.data_proxy.get_previous_trading_date(trading_date)
    
        if date is None:
            date = yesterday
        else:
            date = pd.Timestamp(date)
            if date > yesterday:
                raise RQInvalidArgument(
                    "get_yield_curve: {} >= now({})".format(date, yesterday)
                )
    
        return env.data_proxy.get_yield_curve(start_date=date, end_date=date, tenor=tenor)
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(
        verify_that("order_book_id").is_valid_instrument(),
        verify_that("bar_count").is_instance_of(int).is_greater_than(0),
        verify_that("frequency").is_valid_frequency(),
        verify_that("fields").are_valid_fields(
            names.VALID_HISTORY_FIELDS, ignore_none=True
        ),
        verify_that("skip_suspended").is_instance_of(bool),
        verify_that("include_now").is_instance_of(bool),
        verify_that("adjust_type").is_in({"pre", "none", "post"}),
    )
    def history_bars(
        order_book_id,
        bar_count,
        frequency,
        fields=None,
        skip_suspended=True,
        include_now=False,
        adjust_type="pre",
    ):
        """
        获取指定合约的历史行情，同时支持日以及分钟历史数据。不能在init中调用。 注意，该API会自动跳过停牌数据。
    
        日回测获取分钟历史数据：不支持
    
        日回测获取日历史数据
    
        =========================   ===================================================
        调用时间                      返回数据
        =========================   ===================================================
        T日before_trading            T-1日day bar
        T日handle_bar                T日day bar
        =========================   ===================================================
    
        分钟回测获取日历史数据
    
        =========================   ===================================================
        调用时间                      返回数据
        =========================   ===================================================
        T日before_trading            T-1日day bar
        T日handle_bar                T-1日day bar
        =========================   ===================================================
    
        分钟回测获取分钟历史数据
    
        =========================   ===================================================
        调用时间                      返回数据
        =========================   ===================================================
        T日before_trading            T-1日最后一个minute bar
        T日handle_bar                T日当前minute bar
        =========================   ===================================================
    
        :param order_book_id: 合约代码
        :type order_book_id: `str`
    
        :param int bar_count: 获取的历史数据数量，必填项
        :param str frequency: 获取数据什么样的频率进行。'1d'或'1m'分别表示每日和每分钟，必填项
        :param str fields: 返回数据字段。必填项。见下方列表。
    
        =========================   ===================================================
        fields                      字段名
        =========================   ===================================================
        datetime                    时间戳
        open                        开盘价
        high                        最高价
        low                         最低价
        close                       收盘价
        volume                      成交量
        total_turnover              成交额
        open_interest               持仓量（期货专用）
        basis_spread                期现差（股指期货专用）
        settlement                  结算价（期货日线专用）
        prev_settlement             结算价（期货日线专用）
        =========================   ===================================================
    
        :param bool skip_suspended: 是否跳过停牌数据
        :param bool include_now: 是否包含当前数据
        :param str adjust_type: 复权类型，默认为前复权 pre；可选 pre, none, post
    
        :return: `ndarray`, 方便直接与talib等计算库对接，效率较history返回的DataFrame更高。
    
        :example:
    
        获取最近5天的日线收盘价序列（策略当前日期为20160706）:
    
        ..  code-block:: python3
            :linenos:
    
            [In]
            logger.info(history_bars('000002.XSHE', 5, '1d', 'close'))
            [Out]
            [ 8.69  8.7   8.71  8.81  8.81]
        """
        order_book_id = assure_order_book_id(order_book_id)
        env = Environment.get_instance()
        dt = env.calendar_dt
    
        if frequency[-1] not in {"m", "d"}:
            raise RQInvalidArgument("invalid frequency {}".format(frequency))
    
        if frequency[-1] == "m" and env.config.base.frequency == "1d":
            raise RQInvalidArgument("can not get minute history in day back test")
    
        if frequency[-1] == "d" and frequency != "1d":
            raise RQInvalidArgument("invalid frequency")
    
        if adjust_type not in {"pre", "post", "none"}:
            raise RuntimeError("invalid adjust_type")
    
        if frequency == "1d":
            sys_frequency = Environment.get_instance().config.base.frequency
            if (
                sys_frequency in ["1m", "tick"]
                and not include_now
                and ExecutionContext.phase() != EXECUTION_PHASE.AFTER_TRADING
            ) or (ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING):
                dt = env.data_proxy.get_previous_trading_date(env.trading_dt.date())
                # 当 EXECUTION_PHASE.BEFORE_TRADING 的时候，强制 include_now 为 False
                include_now = False
            if sys_frequency == "1d":
                # 日回测不支持 include_now
                include_now = False
    
        if fields is None:
            fields = ["datetime", "open", "high", "low", "close", "volume"]
    
        return env.data_proxy.history_bars(
            order_book_id,
            bar_count,
            frequency,
            fields,
            dt,
            skip_suspended=skip_suspended,
            include_now=include_now,
            adjust_type=adjust_type,
            adjust_orig=env.trading_dt,
        )
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(
        verify_that("type").are_valid_fields(
            names.VALID_INSTRUMENT_TYPES, ignore_none=True
        ),
        verify_that("date").is_valid_date(ignore_none=True),
    )
    def all_instruments(type=None, date=None):
        """
        获取某个国家市场的所有合约信息。使用者可以通过这一方法很快地对合约信息有一个快速了解，目前仅支持中国市场。
    
        :param str type: 需要查询合约类型，例如：type='CS'代表股票。默认是所有类型
    
        :param date: 查询时间点
        :type date: `str` | `datetime` | `date`
    
    
        :return: `pandas DataFrame` 所有合约的基本信息。
    
        其中type参数传入的合约类型和对应的解释如下：
    
        =========================   ===================================================
        合约类型                      说明
        =========================   ===================================================
        CS                          Common Stock, 即股票
        ETF                         Exchange Traded Fund, 即交易所交易基金
        LOF                         Listed Open-Ended Fund，即上市型开放式基金
        FenjiMu                     Fenji Mu Fund, 即分级母基金
        FenjiA                      Fenji A Fund, 即分级A类基金
        FenjiB                      Fenji B Funds, 即分级B类基金
        INDX                        Index, 即指数
        Future                      Futures，即期货，包含股指、国债和商品期货
        =========================   ===================================================
    
        :example:
    
        获取中国市场所有分级基金的基础信息:
    
        ..  code-block:: python3
            :linenos:
    
            [In]all_instruments('FenjiA')
            [Out]
                abbrev_symbol    order_book_id    product    sector_code  symbol
            0    CYGA    150303.XSHE    null    null    华安创业板50A
            1    JY500A    150088.XSHE    null    null    金鹰500A
            2    TD500A    150053.XSHE    null    null    泰达稳健
            3    HS500A    150110.XSHE    null    null    华商500A
            4    QSAJ    150235.XSHE    null    null    鹏华证券A
            ...
    
        """
        env = Environment.get_instance()
        if date is None:
            dt = env.trading_dt
        else:
            dt = pd.Timestamp(date).to_pydatetime()
            dt = min(dt, env.trading_dt)
    
        if type is not None:
            if isinstance(type, six.string_types):
                type = [type]
    
            types = set()
            for t in type:
                if t == "Stock":
                    types.add("CS")
                elif t == "Fund":
                    types.update(["ETF", "LOF", "SF", "FenjiA", "FenjiB", "FenjiMu"])
                else:
                    types.add(t)
        else:
            types = None
    
        result = env.data_proxy.all_instruments(types, dt)
        if types is not None and len(types) == 1:
            return pd.DataFrame([i.__dict__ for i in result])
    
        return pd.DataFrame(
            [
                [i.order_book_id, i.symbol, i.type, i.listed_date, i.de_listed_date]
                for i in result
            ],
            columns=["order_book_id", "symbol", "type", "listed_date", "de_listed_date"],
        )
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(verify_that("id_or_symbols").is_instance_of((str, Iterable)))
    def instruments(id_or_symbols):
        """
        获取某个国家市场内一个或多个合约的详细信息。目前仅支持中国市场。
    
        :param id_or_symbols: 合约代码或者合约代码列表
        :type id_or_symbols: `str` | List[`str`]
    
        :return: :class:`~StockInstrument` | :class:`~FutureInstrument`
    
        目前系统并不支持跨国家市场的同时调用。传入 order_book_id list必须属于同一国家市场，不能混合着中美两个国家市场的order_book_id。
    
        :example:
    
        *   获取单一股票合约的详细信息:
    
            ..  code-block:: python3
                :linenos:
    
                [In]instruments('000001.XSHE')
                [Out]
                Instrument(order_book_id=000001.XSHE, symbol=平安银行, abbrev_symbol=PAYH, listed_date=19910403, de_listed_date=null, board_type=MainBoard, sector_code_name=金融, sector_code=Financials, round_lot=100, exchange=XSHE, special_type=Normal, status=Active)
    
        *   获取多个股票合约的详细信息:
    
            ..  code-block:: python3
                :linenos:
    
                [In]instruments(['000001.XSHE', '000024.XSHE'])
                [Out]
                [Instrument(order_book_id=000001.XSHE, symbol=平安银行, abbrev_symbol=PAYH, listed_date=19910403, de_listed_date=null, board_type=MainBoard, sector_code_name=金融, sector_code=Financials, round_lot=100, exchange=XSHE, special_type=Normal, status=Active), Instrument(order_book_id=000024.XSHE, symbol=招商地产, abbrev_symbol=ZSDC, listed_date=19930607, de_listed_date=null, board_type=MainBoard, sector_code_name=金融, sector_code=Financials, round_lot=100, exchange=XSHE, special_type=Normal, status=Active)]
    
        *   获取合约已上市天数:
    
            ..  code-block:: python
                :linenos:
    
                instruments('000001.XSHE').days_from_listed()
    
        *   获取合约距离到期天数:
    
            ..  code-block:: python
                :linenos:
    
                instruments('IF1701').days_to_expire()
        """
        return Environment.get_instance().data_proxy.instruments(id_or_symbols)
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(verify_that("code").is_instance_of((str, SectorCodeItem)))
    def sector(code):
        if not isinstance(code, six.string_types):
            code = code.name
        else:
            code = to_sector_name(code)
    
        return Environment.get_instance().data_proxy.sector(code)
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(verify_that("code").is_instance_of((str, IndustryCodeItem)))
    def industry(code):
        if not isinstance(code, six.string_types):
            code = code.code
        else:
            code = to_industry_code(code)
    
        return Environment.get_instance().data_proxy.industry(code)
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(
        verify_that("start_date").is_valid_date(ignore_none=False),
        verify_that("end_date").is_valid_date(ignore_none=False),
    )
    def get_trading_dates(start_date, end_date):
        """
        获取某个国家市场的交易日列表（起止日期加入判断）。目前仅支持中国市场。
    
        :param start_date: 开始日期
        :type start_date: `str` | `date` | `datetime` | `pandas.Timestamp`
    
        :param end_date: 结束如期
        :type end_date: `str` | `date` | `datetime` | `pandas.Timestamp`
    
        :return: list[`datetime.date`]
    
        :example:
    
        ..  code-block:: python3
            :linenos:
    
            [In]get_trading_dates(start_date='2016-05-05', end_date='20160505')
            [Out]
            [datetime.date(2016, 5, 5)]
        """
        return Environment.get_instance().data_proxy.get_trading_dates(start_date, end_date)
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(
        verify_that("date").is_valid_date(ignore_none=False),
        verify_that("n").is_instance_of(int).is_greater_or_equal_than(1),
    )
    def get_previous_trading_date(date, n=1):
        """
        获取指定日期的之前的第 n 个交易日。
    
        :param date: 指定日期
        :type date: `str` | `date` | `datetime` | `pandas.Timestamp`
        :param n:
    
        :return: `datetime.date`
    
        :example:
    
        ..  code-block:: python3
            :linenos:
    
            [In]get_previous_trading_date(date='2016-05-02')
            [Out]
            [datetime.date(2016, 4, 29)]
        """
        return Environment.get_instance().data_proxy.get_previous_trading_date(date, n)
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(
        verify_that("date").is_valid_date(ignore_none=False),
        verify_that("n").is_instance_of(int).is_greater_or_equal_than(1),
    )
    def get_next_trading_date(date, n=1):
        """
        获取指定日期之后的第 n 个交易日
    
        :param date: 指定日期
        :type date: `str` | `date` | `datetime` | `pandas.Timestamp`
        :param n:
    
        :return: `datetime.date`
    
        :example:
    
        ..  code-block:: python3
            :linenos:
    
            [In]get_next_trading_date(date='2016-05-01')
            [Out]
            [datetime.date(2016, 5, 3)]
        """
        return Environment.get_instance().data_proxy.get_next_trading_date(date, n)
    
    
    def to_date(date):
        if isinstance(date, six.string_types):
            return parse(date).date()
    
        if isinstance(date, datetime.datetime):
            try:
                return date.date()
            except AttributeError:
                return date
    
        raise RQInvalidArgument("unknown date value: {}".format(date))
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_INIT,
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(
        verify_that("order_book_id").is_valid_instrument(),
        verify_that("start_date").is_valid_date(ignore_none=False),
    )
    def get_dividend(order_book_id, start_date, *args, **kwargs):
        # adjusted 参数在不复权数据回测时不再提供
        env = Environment.get_instance()
        dt = env.trading_dt.date() - datetime.timedelta(days=1)
        start_date = to_date(start_date)
        if start_date > dt:
            raise RQInvalidArgument(
                _(
                    u"in get_dividend, start_date {} is later than the previous test day {}"
                ).format(start_date, dt)
            )
        order_book_id = assure_order_book_id(order_book_id)
        array = env.data_proxy.get_dividend(order_book_id)
        if array is None:
            return None
    
        sd = start_date.year * 10000 + start_date.month * 100 + start_date.day
        ed = dt.year * 10000 + dt.month * 100 + dt.day
        return array[
            (array["announcement_date"] >= sd) & (array["announcement_date"] <= ed)
        ]
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.ON_BAR, EXECUTION_PHASE.ON_TICK, EXECUTION_PHASE.SCHEDULED
    )
    @apply_rules(
        verify_that("series_name", pre_check=True).is_instance_of(str),
        verify_that("value", pre_check=True).is_number(),
    )
    def plot(series_name, value):
        """
        Add a point to custom series.
        :param str series_name: the name of custom series
        :param float value: the value of the series in this time
        :return: None
        """
        Environment.get_instance().add_plot(series_name, value)
    
    
    @export_as_api
    @ExecutionContext.enforce_phase(
        EXECUTION_PHASE.BEFORE_TRADING,
        EXECUTION_PHASE.ON_BAR,
        EXECUTION_PHASE.ON_TICK,
        EXECUTION_PHASE.AFTER_TRADING,
        EXECUTION_PHASE.SCHEDULED,
    )
    @apply_rules(verify_that("id_or_symbol").is_valid_instrument())
    def current_snapshot(id_or_symbol):
        """
        获得当前市场快照数据。只能在日内交易阶段调用，获取当日调用时点的市场快照数据。
        市场快照数据记录了每日从开盘到当前的数据信息，可以理解为一个动态的day bar数据。
        在目前分钟回测中，快照数据为当日所有分钟线累积而成，一般情况下，最后一个分钟线获取到的快照数据应当与当日的日线行情保持一致。
        需要注意，在实盘模拟中，该函数返回的是调用当时的市场快照情况，所以在同一个handle_bar中不同时点调用可能返回的数据不同。
        如果当日截止到调用时候对应股票没有任何成交，那么snapshot中的close, high, low, last几个价格水平都将以0表示。
    
        :param str id_or_symbol: 合约代码或简称
    
        :return: :class:`~Snapshot`
    
        :example:
    
        在handle_bar中调用该函数，假设策略当前时间是20160104 09:33:
    
        ..  code-block:: python3
            :linenos:
    
            [In]
            logger.info(current_snapshot('000001.XSHE'))
            [Out]
            2016-01-04 09:33:00.00  INFO
            Snapshot(order_book_id: '000001.XSHE', datetime: datetime.datetime(2016, 1, 4, 9, 33), open: 10.0, high: 10.025, low: 9.9667, last: 9.9917, volume: 2050320, total_turnover: 20485195, prev_close: 9.99)
        """
        env = Environment.get_instance()
        frequency = env.config.base.frequency
        order_book_id = assure_order_book_id(id_or_symbol)
    
        dt = env.calendar_dt
    
        if env.config.base.run_type == RUN_TYPE.BACKTEST:
            if ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING:
                dt = env.data_proxy.get_previous_trading_date(env.trading_dt.date())
                return env.data_proxy.current_snapshot(order_book_id, "1d", dt)
            elif ExecutionContext.phase() == EXECUTION_PHASE.AFTER_TRADING:
                return env.data_proxy.current_snapshot(order_book_id, "1d", dt)
    
        # PT、实盘直接取最新快照，忽略 frequency, dt 参数
        return env.data_proxy.current_snapshot(order_book_id, frequency, dt)
    
    
    @export_as_api
    def get_positions():
        booking = Environment.get_instance().booking
        if not booking:
            raise RuntimeError(
                _("Booking has not been set, please check your broker configuration.")
            )
        return booking.get_positions()
    
    
    @export_as_api
    @apply_rules(
        verify_that("direction").is_in([POSITION_DIRECTION.LONG, POSITION_DIRECTION.SHORT])
    )
    def get_position(order_book_id, direction):
        booking = Environment.get_instance().booking
        if not booking:
            raise RuntimeError(
                _("Booking has not been set, please check your broker configuration.")
            )
    
        return booking.get_position(order_book_id, direction)
    
    
    @export_as_api
    @apply_rules(
        verify_that("event_type").is_instance_of(EVENT),
        verify_that("handler").is_instance_of(types.FunctionType),
    )
    def subscribe_event(event_type, handler):
        env = Environment.get_instance()
        user_strategy = env.user_strategy
        env.event_bus.add_listener(
            event_type, user_strategy.wrap_user_event_handler(handler), user=True
        )