from AlgorithmImports import *

class BenzingaNewsDataAlgorithm(QCAlgorithm):

    current_holdings = 0
    target_holdings = 0
    word_scores = {
        'good': 1, 'great': 1, 'best': 1, 'growth': 1,
        'bad': -1, 'terrible': -1, 'worst': -1, 'loss': -1}

    def Initialize(self):
        self.SetStartDate(2021, 1, 1)
        self.SetEndDate(2021, 6, 1)
        self.SetCash(100000)
        
        # Requesting data
        self.aapl = self.AddEquity("AAPL", Resolution.Minute).Symbol
        self.benzinga_symbol = self.AddData(BenzingaNews, self.aapl).Symbol
        
        # Historical data
        history = self.History(self.benzinga_symbol, 14, Resolution.Daily)
        self.Debug(f"We got {len(history)} items from our history request")
        
        
    def OnData(self, data):
        if data.ContainsKey(self.benzinga_symbol):
            # Assign a sentiment score to the news article
            content_words = data[self.benzinga_symbol].Contents.lower()
            score = 0
            for word, word_score in self.word_scores.items():
                score += (content_words.count(word) * word_score)
            self.target_holdings = int(score > 0)
        
        # Ensure we have AAPL data in the current Slice
        if not (data.ContainsKey(self.aapl) and data[self.aapl] is not None and not data[self.aapl].IsFillForward):
            return
        
        # Buy or sell if the sentiment has changed from our current holdings
        if self.current_holdings != self.target_holdings:
            self.SetHoldings(self.aapl, self.target_holdings)
            self.current_holdings = self.target_holdings