# -*- coding: utf-8 -*-
from pandas import Series
from pandas_ta._typing import DictLike, Int, IntFloat
from pandas_ta.maps import Imports
from pandas_ta.utils import (
    non_zero_range,
    v_offset,
    v_scalar,
    v_series,
    v_talib
)


def bop(
    open_: Series, high: Series, low: Series, close: Series,
    scalar: IntFloat = None, talib: bool = None,
    offset: Int = None, **kwargs: DictLike
) -> Series:
    """Balance of Power (BOP)

    Balance of Power measure the market strength of buyers against sellers.

    Sources:
        http://www.worden.com/TeleChartHelp/Content/Indicators/Balance_of_Power.htm

    Args:
        open (pd.Series): Series of 'open's
        high (pd.Series): Series of 'high's
        low (pd.Series): Series of 'low's
        close (pd.Series): Series of 'close's
        scalar (float): How much to magnify. Default: 1
        talib (bool): If TA Lib is installed and talib is True, Returns
            the TA Lib version. Default: True
        offset (int): How many periods to offset the result. Default: 0

    Kwargs:
        fillna (value, optional): pd.DataFrame.fillna(value)
        fill_method (value, optional): Type of fill method

    Returns:
        pd.Series: New feature generated.
    """
    # Validate
    open_ = v_series(open_)
    high = v_series(high)
    low = v_series(low)
    close = v_series(close)
    scalar = v_scalar(scalar, 1)
    mode_tal = v_talib(talib)
    offset = v_offset(offset)

    # Calculate
    if Imports["talib"] and mode_tal and close.size:
        from talib import BOP
        bop = BOP(open_, high, low, close)
    else:
        high_low_range = non_zero_range(high, low)
        close_open_range = non_zero_range(close, open_)
        bop = scalar * close_open_range / high_low_range

    # Offset
    if offset != 0:
        bop = bop.shift(offset)

    # Fill
    if "fillna" in kwargs:
        bop.fillna(kwargs["fillna"], inplace=True)
    if "fill_method" in kwargs:
        bop.fillna(method=kwargs["fill_method"], inplace=True)

    # Name and Category
    bop.name = f"BOP"
    bop.category = "momentum"

    return bop
