SimpleRsi

# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib

# --- Strategy Class ---
class SimpleRsi(IStrategy):
    """
    This is a sample strategy from the Freqtrade Strategy Development Starter Kit.
    The full kit, with advanced templates and detailed guides, is available for purchase.
    
    [Find out more on Gumroad](https://YOUR_GUMROAD_LINK_HERE)
    """
    
    # Minimal ticker timeframe for the strategy (in minutes)
    timeframe = '5m'

    # Number of candles to load at startup
    startup_candle_count: int = 30

    # Stoploss configuration for the strategy
    stoploss = -0.10

    # Return on Investment (ROI) table
    minimal_roi = {
        "0": 0.05,
        "30": 0.03,
        "60": 0.01,
        "120": 0
    }

    # Trailing stoploss configuration
    trailing_stop = True
    trailing_stop_positive = 0.01
    trailing_stop_positive_offset = 0.02
    trailing_only_offset_is_reached = True

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        Calculates and adds the indicators needed for the strategy.
        """
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
        
        return dataframe

    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        Defines the conditions for the buy signal.
        """
        dataframe.loc[
            (
                (dataframe['rsi'] < 30) &
                (dataframe['volume'] > 0)
            ),
            'buy'] = 1
            
        return dataframe

    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        Defines the conditions for the sell signal.
        """
        dataframe.loc[
            (
                (dataframe['rsi'] > 70) &
                (dataframe['volume'] > 0)
            ),
            'sell'] = 1
            
        return dataframe