# source: https://raw.githubusercontent.com/xebecsdemise/xebtradestrat/59de0b9450d107267d7ac053a2dab83c9bba8d67/XebTradeStrat.py
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame
import numpy as np
# --------------------------------

import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib


def bollinger_bands(stock_price, window_size, num_of_std):
    rolling_mean = stock_price.rolling(window=window_size).mean()
    rolling_std = stock_price.rolling(window=window_size).std()
    lower_band = rolling_mean - (rolling_std * num_of_std)

    return rolling_mean, lower_band


class github_xebecsdemise_xebtradestrat__XebTradeStrat__20211013_174131(IStrategy):
    minimal_roi = {
      "4": 0.002,
      "2": 0.005,
      "0": 0.01
    }

    stoploss = -0.01
    timeframe = '1m'
    trailing_stop = True
    trailing_only_offset_is_reached = True
    trailing_stop_positive_offset = 0.001  # Trigger positive stoploss once crosses above this percentage
    trailing_stop_positive = 0.0005 # Sell asset if it dips down this much


    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
        dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
        return dataframe

    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (dataframe['ema5'] > dataframe['ema10']) &
                (dataframe['ema5'] .shift(1) < dataframe['ema10'].shift(1)) &
                (dataframe['volume'] > 0)
            ),
            'buy'] = 1
        return dataframe

    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        no sell signal
        """
        dataframe.loc[:, 'sell'] = 0
        return dataframe