# main.py import argparse import json import os import time import praw import yfinance as yf from dotenv import load_dotenv import database from ticker_extractor import extract_tickers from sentiment_analyzer import get_sentiment_score # <-- IMPORT OUR NEW MODULE load_dotenv() MARKET_CAP_REFRESH_INTERVAL = 86400 # ... (load_subreddits, get_market_cap, get_reddit_instance functions are unchanged) def load_subreddits(filepath): # ... try: with open(filepath, 'r') as f: return json.load(f).get("subreddits", []) except (FileNotFoundError, json.JSONDecodeError) as e: print(f"Error loading config: {e}") return None def get_market_cap(ticker_symbol): # ... try: ticker = yf.Ticker(ticker_symbol) return ticker.fast_info.get('marketCap') except Exception: return None def get_reddit_instance(): # ... client_id = os.getenv("REDDIT_CLIENT_ID") client_secret = os.getenv("REDDIT_CLIENT_SECRET") user_agent = os.getenv("REDDIT_USER_AGENT") if not all([client_id, client_secret, user_agent]): print("Error: Reddit API credentials not found.") return None return praw.Reddit(client_id=client_id, client_secret=client_secret, user_agent=user_agent) def scan_subreddits(reddit, subreddits_list, post_limit=25): """Scans subreddits, performs sentiment analysis, and stores results in the database.""" conn = database.get_db_connection() print(f"\nScanning {len(subreddits_list)} subreddits for top {post_limit} posts...") for subreddit_name in subreddits_list: try: subreddit_id = database.get_or_create_entity(conn, 'subreddits', 'name', subreddit_name) subreddit = reddit.subreddit(subreddit_name) print(f"Scanning r/{subreddit_name}...") for submission in subreddit.hot(limit=post_limit): # We analyze the title for sentiment as it's often the most concise summary. # Analyzing all comments could be a future enhancement. text_to_analyze = submission.title tickers_in_post = extract_tickers(text_to_analyze + " " + submission.selftext) # --- NEW: Get sentiment score for the post's title --- sentiment = get_sentiment_score(text_to_analyze) for ticker_symbol in set(tickers_in_post): ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol) # --- NEW: Pass the sentiment score to the database --- database.add_mention( conn, ticker_id=ticker_id, subreddit_id=subreddit_id, post_id=submission.id, timestamp=int(submission.created_utc), sentiment=sentiment # Pass the score here ) # (The market cap update logic remains the same) ticker_info = database.get_ticker_info(conn, ticker_id) current_time = int(time.time()) if not ticker_info['last_updated'] or (current_time - ticker_info['last_updated'] > MARKET_CAP_REFRESH_INTERVAL): print(f" -> Fetching market cap for {ticker_symbol}...") market_cap = get_market_cap(ticker_symbol) database.update_ticker_market_cap(conn, ticker_id, market_cap or ticker_info['market_cap']) except Exception as e: print(f"Could not scan r/{subreddit_name}. Error: {e}") conn.close() print("\n--- Scan Complete ---") def main(): # --- IMPORTANT: Delete your old DB file before running! --- # Since we changed the schema and logic, old data won't have sentiment. # It's best to start fresh. Delete the `reddit_stocks.db` file now. parser = argparse.ArgumentParser(description="Analyze stock ticker mentions on Reddit.") parser.add_argument("config_file", help="Path to the JSON file containing subreddits.") args = parser.parse_args() database.initialize_db() subreddits = load_subreddits(args.config_file) if not subreddits: return reddit = get_reddit_instance() if not reddit: return scan_subreddits(reddit, subreddits) database.generate_summary_report() if __name__ == "__main__": main()