main.py

from lumibot.brokers import Alpaca
from lumibot.backtesting import YahooDataBacktesting #other backesting like polygon backtesting (for crypto) can also be set
from lumibot.strategies.strategy import Strategy
from lumibot.traders import Trader
from datetime import datetime
from alpaca_trade_api import REST
from timedelta import Timedelta
from finbert import estimate_sentiment
import os
from dotenv import load_dotenv

load_dotenv()

API_KEY = os.getenv("API_KEY")
API_SECRET = os.getenv("API_SECRET")
BASE_URL = os.getenv("BASE_URL")

ALPACA_CREDS = {
    "API_KEY":API_KEY,
    "API_SECRET":API_SECRET,
    "PAPER": True
}

class MLTrader(Strategy):
    def initialize(self, symbol:str="SPY", cash_at_rish:float=.5):
        self.symbol = symbol
        self.sleeptime = "24H"
        self.last_trade = None
        self.cash_at_risk = cash_at_rish
        self.api = REST(base_url=BASE_URL, key_id=API_KEY, secret_key=API_SECRET)

    def position_sizing(self):
        cash = self.get_cash()
        last_price = self.get_last_price(self.symbol)
        quantity = round((cash * self.cash_at_risk) / last_price, 0)
        return cash, last_price, quantity

    def get_dates(self):
        today = self.get_datetime()
        three_days_prior = today - Timedelta(days = 3)
        return today.strftime('%Y-%m-%d'), three_days_prior.strftime('%Y-%m-%d')

    def get_sentiment(self):
        today, three_days_prior =  self.get_dates()
        news = self.api.get_news(symbol=self.symbol,
                                 start=three_days_prior, 
                                 end=today)
        news = [ev.__dict__['_raw']['headline'] for ev in news]
        probability, sentiment = estimate_sentiment(news)
        return probability, sentiment

    def on_trading_iteration(self):
        cash, last_price, quantity = self.position_sizing()
        probability, sentiment = self.get_sentiment()

        if cash > last_price:
            if sentiment == "positive" and probability > .999:
                if self.last_order == "sell":
                    self.sell_all()
                order = self.create_order(
                    self.symbol,
                    quantity,
                    "buy",
                    type = "bracket",
                    take_profit_price=last_price*.8,
                    stop_loss_price=last_price*1.05
                )
                self.submit_order(order)
                self.last_trade = "buy"
            elif sentiment == "negative" and probability > .999:
                if self.last_trade == "buy":
                    self.sell_all()
                order = self.create_order(
                    self.symbol,
                    quantity,
                    "sell",
                    type = "bracket",
                    take_profit_price=last_price*1.20,
                    stop_loss_price=last_price*0.95
                )
                self.submit_order(order)
                self.last_trade = "sell"

#set your own dates
start_date = datetime(2024,1,1) 
end_date = datetime(2025,1,1)

broker = Alpaca(ALPACA_CREDS)
strategy = MLTrader(name='mlstrat', broker = broker,
                    parameters={"symbol":"SPY",
                                "cash_at_risk":.5})

strategy.backtest(
    YahooDataBacktesting,
    start_date,
    end_date,
    parameters={"symbol":"SPY", "cash_at_risk":.5}
)