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,
    )