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433 lines
14 KiB
C++
433 lines
14 KiB
C++
#
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# 对 C++ 引出类和函数进行扩展, pybind11 对小函数到导出效率不如 python 直接执行
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#
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from datetime import *
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from .cpp.core import *
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from .util.slice import list_getitem
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try:
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from .cpp.core_pro import *
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except:
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pass
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# ------------------------------------------------------------------
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# 增加Datetime、Stock的hash支持,以便可做为dict的key
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# ------------------------------------------------------------------
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Datetime.__hash__ = lambda self: self.ticks
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TimeDelta.__hash__ = lambda self: self.ticks
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Stock.__hash__ = lambda self: self.id
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# ------------------------------------------------------------------
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# 增强 Datetime
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# ------------------------------------------------------------------
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__old_Datetime_init__ = Datetime.__init__
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__old_Datetime_add__ = Datetime.__add__
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__old_Datetime_sub__ = Datetime.__sub__
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def __new_Datetime_init__(self, *args, **kwargs):
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"""
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日期时间类(精确到秒),通过以下方式构建:
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- 通过字符串:Datetime("2010-1-1 10:00:00")
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- 通过 Python 的date:Datetime(date(2010,1,1))
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- 通过 Python 的datetime:Datetime(datetime(2010,1,1,10)
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- 通过 YYYYMMDDHHMM 形式的整数:Datetime(201001011000)
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- Datetime(year, month, day, hour=0, minute=0, second=0, millisecond=0, microsecond=0)
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获取日期列表参见: :py:func:`getDateRange`
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获取交易日日期参见: :py:meth:`StockManager.getTradingCalendar`
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"""
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if not args:
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__old_Datetime_init__(self, **kwargs)
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# datetime实例同时也是date的实例,判断必须放在date之前
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elif isinstance(args[0], datetime):
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d = args[0]
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milliseconds = d.microsecond // 1000
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microseconds = d.microsecond - milliseconds * 1000
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__old_Datetime_init__(self, d.year, d.month, d.day, d.hour, d.minute, d.second, milliseconds, microseconds)
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elif isinstance(args[0], date):
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d = args[0]
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__old_Datetime_init__(self, d.year, d.month, d.day, 0, 0, 0, 0)
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elif isinstance(args[0], str):
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__old_Datetime_init__(self, args[0])
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else:
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__old_Datetime_init__(self, *args)
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def __new_Datetime_add__(self, td):
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"""加上指定时长,时长对象可为 TimeDelta 或 datetime.timedelta 类型
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:param TimeDelta td: 时长
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:rtype: Datetime
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"""
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if isinstance(td, TimeDelta):
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return __old_Datetime_add__(self, td)
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elif isinstance(td, timedelta):
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return __old_Datetime_add__(self, TimeDelta(td))
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else:
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raise TypeError("unsupported operand type(s) for +: 'TimeDelta' and '{}'".format(type(td)))
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def __new_Datetime_sub__(self, td):
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"""减去指定的时长, 时长对象可为 TimeDelta 或 datetime.timedelta 类型
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:param TimeDelta td: 指定时长
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:rtype: Datetime
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"""
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if isinstance(td, TimeDelta):
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return __old_Datetime_sub__(self, td)
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elif isinstance(td, timedelta):
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return __old_Datetime_sub__(self, TimeDelta(td))
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elif isinstance(td, Datetime):
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return __old_Datetime_sub__(self, td)
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else:
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raise TypeError("unsupported operand type(s) for +: 'TimeDelta' and '{}'".format(type(td)))
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def Datetime_date(self):
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"""转化生成 python 的 date"""
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return date(self.year, self.month, self.day)
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def Datetime_datetime(self):
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"""转化生成 python 的 datetime"""
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return datetime(self.year, self.month, self.day, self.hour, self.minute, self.second, self.microsecond)
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Datetime.__init__ = __new_Datetime_init__
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Datetime.__add__ = __new_Datetime_add__
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Datetime.__radd__ = __new_Datetime_add__
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Datetime.__sub__ = __new_Datetime_sub__
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Datetime.date = Datetime_date
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Datetime.datetime = Datetime_datetime
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# ------------------------------------------------------------------
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# 增强 TimeDelta
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# ------------------------------------------------------------------
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__old_TimeDelta_init__ = TimeDelta.__init__
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__old_TimeDelta_add__ = TimeDelta.__add__
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__old_TimeDelta_sub__ = TimeDelta.__sub__
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def __new_TimeDelta_init__(self, *args, **kwargs):
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"""
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可通过以下方式构建:
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- 通过 datetime.timedelta 构建。TimdeDelta(timedelta实例)
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- TimeDelta(days=0, hours=0, minutes=0, seconds=0, milliseconds=0, microseconds=0)
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- -99999999 <= days <= 99999999
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- -100000 <= hours <= 100000
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- -100000 <= minutes <= 100000
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- -8639900 <= seconds <= 8639900
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- -86399000000 <= milliseconds <= 86399000000
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- -86399000000 <= microseconds <= 86399000000
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"""
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if not args:
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__old_TimeDelta_init__(self, **kwargs)
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elif isinstance(args[0], timedelta):
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days = args[0].days
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secs = args[0].seconds
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hours = secs // 3600
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mins = secs // 60 - hours * 60
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secs = secs - mins * 60 - hours * 3600
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microsecs = args[0].microseconds
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millisecs = microsecs // 1000
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microsecs = microsecs - millisecs * 1000
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__old_TimeDelta_init__(self, days, hours, mins, secs, millisecs, microsecs)
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else:
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__old_TimeDelta_init__(self, *args)
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def __new_TimeDelta_add__(self, td):
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"""可和 TimeDelta, datetime.timedelta, Datetime执行相加操作"""
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if isinstance(td, TimeDelta):
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return __old_TimeDelta_add__(self, td)
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elif isinstance(td, timedelta):
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return __old_TimeDelta_add__(self, TimeDelta(td))
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elif isinstance(td, Datetime):
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return td + self
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elif isinstance(td, datetime):
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return td + Datetime(datetime)
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else:
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raise TypeError("unsupported operand type(s) for +: 'TimeDelta' and '{}'".format(type(td)))
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def __new_TimeDelta_sub__(self, td):
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"""可减去TimeDelta, datetime.timedelta"""
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return __old_TimeDelta_sub__(self, td) if isinstance(td, TimeDelta) else __old_TimeDelta_sub__(self, TimeDelta(td))
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def TimeDelta_timedelta(self):
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""" 转化为 datetime.timedelta """
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return timedelta(
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days=self.days,
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hours=self.hours,
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minutes=self.minutes,
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seconds=self.seconds,
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milliseconds=self.milliseconds,
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microseconds=self.microseconds
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)
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TimeDelta.__init__ = __new_TimeDelta_init__
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TimeDelta.__add__ = __new_TimeDelta_add__
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TimeDelta.__sub__ = __new_TimeDelta_sub__
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TimeDelta.timedelta = TimeDelta_timedelta
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# ------------------------------------------------------------------
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# 增强 KData 的遍历
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# ------------------------------------------------------------------
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def KData_getitem(kdata, i):
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"""
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:param i: int | Datetime | slice | str 类型
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"""
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if isinstance(i, int):
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length = len(kdata)
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index = length + i if i < 0 else i
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if index < 0 or index >= length:
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raise IndexError("index out of range: %d" % i)
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return kdata.get(index)
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elif isinstance(i, Datetime):
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return kdata.get_by_datetime(i)
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elif isinstance(i, str):
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return kdata.get_by_datetime(Datetime(i))
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elif isinstance(i, slice):
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return [kdata.get(x) for x in range(*i.indices(len(kdata)))]
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else:
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raise IndexError("Error index type")
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def KData_iter(kdata):
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for i in range(len(kdata)):
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yield kdata[i]
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def KData_getPos(kdata, datetime):
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"""
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获取指定时间对应的索引位置
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:param Datetime datetime: 指定的时间
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:return: 对应的索引位置,如果不在数据范围内,则返回 None
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"""
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pos = kdata._getPos(datetime)
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return pos if pos != constant.null_size else None
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def KData_getPosInStock(kdata, datetime):
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"""
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获取指定时间对应的原始K线中的索引位置
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:param Datetime datetime: 指定的时间
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:return: 对应的索引位置,如果不在数据范围内,则返回 None
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"""
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pos = kdata._getPosInStock(datetime)
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return pos if pos != constant.null_size else None
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KData.__getitem__ = KData_getitem
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KData.__iter__ = KData_iter
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KData.get_pos = KData_getPos
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KData.get_pos_in_stock = KData_getPosInStock
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# ------------------------------------------------------------------
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# 重定义Query
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# ------------------------------------------------------------------
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Query.INDEX = Query.QueryType.INDEX
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Query.DATE = Query.QueryType.DATE
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Query.DAY = "DAY"
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Query.WEEK = "WEEK"
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Query.MONTH = "MONTH"
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Query.QUARTER = "QUARTER"
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Query.HALFYEAR = "HALFYEAR"
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Query.YEAR = "YEAR"
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Query.MIN = "MIN"
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Query.MIN3 = "MIN3"
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Query.MIN5 = "MIN5"
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Query.MIN15 = "MIN15"
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Query.MIN30 = "MIN30"
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Query.MIN60 = "MIN60"
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Query.HOUR2 = "HOUR2"
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Query.HOUR4 = "HOUR4"
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Query.HOUR6 = "HOUR6"
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Query.HOUR12 = "HOUR12"
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Query.NO_RECOVER = Query.RecoverType.NO_RECOVER
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Query.FORWARD = Query.RecoverType.FORWARD
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Query.BACKWARD = Query.RecoverType.BACKWARD
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Query.EQUAL_FORWARD = Query.RecoverType.EQUAL_FORWARD
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Query.EQUAL_BACKWARD = Query.RecoverType.EQUAL_BACKWARD
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old_Query_init = Query.__init__
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def new_Query_init(self, start=0, end=None, ktype=Query.DAY, recover_type=Query.NO_RECOVER):
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"""
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构建按索引 [start, end) 方式获取K线数据条件。start,end应同为 int 或 同为 Datetime 类型。
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:param int|Datetime start: 起始索引位置或起始日期
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:param int|Datetime end: 结束索引位置或结束日期
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:param Query.KType ktype: K线数据类型(如日线、分钟线等)
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:param Query.RecoverType recover_type: 复权类型
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:return: 查询条件
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:rtype: KQuery
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"""
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if isinstance(start, int):
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end_pos = constant.null_int64 if end is None else end
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elif isinstance(start, Datetime):
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end_pos = constant.null_datetime if end is None else end
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else:
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raise TypeError('Incorrect parameter type error!')
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old_Query_init(self, start, end_pos, ktype, recover_type)
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Query.__init__ = new_Query_init
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# ------------------------------------------------------------------
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# 增加转化为 np.array、pandas.DataFrame 的功能
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# ------------------------------------------------------------------
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try:
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import numpy as np
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import pandas as pd
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def KData_to_np(kdata):
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"""转化为numpy结构数组"""
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if kdata.get_query().ktype in ('DAY', 'WEEK', 'MONTH', 'QUARTER', 'HALFYEAR', 'YEAR'):
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k_type = np.dtype(
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{
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'names': ['datetime', 'open', 'high', 'low', 'close', 'amount', 'volume'],
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'formats': ['datetime64[D]', 'd', 'd', 'd', 'd', 'd', 'd']
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}
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)
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else:
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k_type = np.dtype(
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{
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'names': ['datetime', 'open', 'high', 'low', 'close', 'amount', 'volume'],
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'formats': ['datetime64[ms]', 'd', 'd', 'd', 'd', 'd', 'd']
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}
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)
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return np.array(
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[(k.datetime.datetime(), k.open, k.high, k.low, k.close, k.amount, k.volume) for k in kdata], dtype=k_type
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)
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def KData_to_df(kdata):
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"""转化为pandas的DataFrame"""
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return pd.DataFrame.from_records(KData_to_np(kdata), index='datetime')
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KData.to_np = KData_to_np
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KData.to_df = KData_to_df
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def PriceList_to_np(data):
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"""仅在安装了numpy模块时生效,转换为numpy.array"""
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return np.array(data, dtype='d')
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def PriceList_to_df(data):
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"""仅在安装了pandas模块时生效,转换为pandas.DataFrame"""
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return pd.DataFrame(data.to_np(), columns=('Value', ))
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PriceList.to_np = PriceList_to_np
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PriceList.to_df = PriceList_to_df
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def DatetimeList_to_np(data):
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"""仅在安装了numpy模块时生效,转换为numpy.array"""
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return np.array(data, dtype='datetime64[D]')
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def DatetimeList_to_df(data):
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"""仅在安装了pandas模块时生效,转换为pandas.DataFrame"""
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return pd.DataFrame(data.to_np(), columns=('Datetime', ))
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DatetimeList.to_np = DatetimeList_to_np
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DatetimeList.to_df = DatetimeList_to_df
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def TimeLine_to_np(data):
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"""转化为numpy结构数组"""
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t_type = np.dtype({'names': ['datetime', 'price', 'vol'], 'formats': ['datetime64[ms]', 'd', 'd']})
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return np.array([(t.date.datetime(), t.price, t.vol) for t in data], dtype=t_type)
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def TimeLine_to_df(kdata):
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"""转化为pandas的DataFrame"""
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return pd.DataFrame.from_records(TimeLine_to_np(kdata), index='datetime')
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TimeLineList.to_np = TimeLine_to_np
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TimeLineList.to_df = TimeLine_to_df
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def TransList_to_np(data):
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"""转化为numpy结构数组"""
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t_type = np.dtype(
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{
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'names': ['datetime', 'price', 'vol', 'direct'],
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'formats': ['datetime64[ms]', 'd', 'd', 'd']
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}
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)
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return np.array([(t.date.datetime(), t.price, t.vol, t.direct) for t in data], dtype=t_type)
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def TransList_to_df(kdata):
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"""转化为pandas的DataFrame"""
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return pd.DataFrame.from_records(TransList_to_np(kdata), index='datetime')
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TransList.to_np = TransList_to_np
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TransList.to_df = TransList_to_df
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except:
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pass
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# ------------------------------------------------------------------
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# 增强 Parameter
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# ------------------------------------------------------------------
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def Parameter_iter(self):
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name_list = self.get_name_list()
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for key in name_list:
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yield self[key]
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def Parameter_keys(self):
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return list(self.get_name_list())
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def Parameter_items(self):
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return [(key, self[key]) for key in self.get_name_list()]
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def Parameter_to_dict(self):
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"""转化为 Python dict 对象"""
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return dict(self.items())
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Parameter.__iter__ = Parameter_iter
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Parameter.keys = Parameter_keys
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Parameter.items = Parameter_items
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Parameter.to_dict = Parameter_to_dict
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# ------------------------------------------------------------------
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# 增强 StrategyContext
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# ------------------------------------------------------------------
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__old_StrategyContext_init__ = StrategyContext.__init__
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def __new_StrategyContext_init__(self, stock_code_list=None):
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__old_StrategyContext_init__(self)
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if stock_code_list is not None:
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self.stock_list = stock_code_list
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StrategyContext.__init__ = __new_StrategyContext_init__
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