180 lines
8.7 KiB
Python
180 lines
8.7 KiB
Python
# rstat_tool/main.py
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import argparse
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import json
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import os
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import time
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import praw
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import yfinance as yf
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from dotenv import load_dotenv
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from . import database
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from .ticker_extractor import extract_tickers
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from .sentiment_analyzer import get_sentiment_score
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load_dotenv()
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MARKET_CAP_REFRESH_INTERVAL = 86400
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POST_AGE_LIMIT = 86400
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def load_subreddits(filepath):
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try:
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with open(filepath, 'r') as f:
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return json.load(f).get("subreddits", [])
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except (FileNotFoundError, json.JSONDecodeError) as e:
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print(f"Error loading config file '{filepath}': {e}")
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return None
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def get_financial_data(ticker_symbol):
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try:
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ticker = yf.Ticker(ticker_symbol)
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data = { "market_cap": ticker.fast_info.get('marketCap'), "closing_price": ticker.fast_info.get('previousClose') }
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return data
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except Exception:
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return {"market_cap": None, "closing_price": None}
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def get_reddit_instance():
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client_id = os.getenv("REDDIT_CLIENT_ID")
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client_secret = os.getenv("REDDIT_CLIENT_SECRET")
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user_agent = os.getenv("REDDIT_USER_AGENT")
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if not all([client_id, client_secret, user_agent]):
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print("Error: Reddit API credentials not found in .env file.")
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return None
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return praw.Reddit(client_id=client_id, client_secret=client_secret, user_agent=user_agent)
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def scan_subreddits(reddit, subreddits_list, post_limit=100, comment_limit=100, days_to_scan=1):
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"""
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Scans subreddits with a hybrid mention counting logic.
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- If a ticker is in the title, it gets credit for all comments.
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- If not, tickers only get credit for direct mentions in comments.
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"""
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conn = database.get_db_connection()
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post_age_limit = days_to_scan * 86400
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current_time = time.time()
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print(f"\nScanning {len(subreddits_list)} subreddit(s) for NEW posts in the last {days_to_scan} day(s)...")
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for subreddit_name in subreddits_list:
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try:
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subreddit_id = database.get_or_create_entity(conn, 'subreddits', 'name', subreddit_name)
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subreddit = reddit.subreddit(subreddit_name)
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print(f"Scanning r/{subreddit_name}...")
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for submission in subreddit.new(limit=post_limit):
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if (current_time - submission.created_utc) > post_age_limit:
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print(f" -> Reached posts older than the {days_to_scan}-day limit.")
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break
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# --- NEW HYBRID LOGIC ---
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tickers_in_title = set(extract_tickers(submission.title))
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all_tickers_found_in_post = set(tickers_in_title) # Start a set to track all tickers for financials
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submission.comments.replace_more(limit=0)
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all_comments = submission.comments.list()[:comment_limit]
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# --- CASE A: Tickers were found in the title ---
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if tickers_in_title:
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print(f" -> Title Mention(s): {', '.join(tickers_in_title)}. Attributing all comments.")
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post_sentiment = get_sentiment_score(submission.title)
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# Add one 'post' mention for each title ticker
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for ticker_symbol in tickers_in_title:
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ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
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database.add_mention(conn, ticker_id, subreddit_id, submission.id, 'post', int(submission.created_utc), post_sentiment)
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# Add one 'comment' mention for EACH comment FOR EACH title ticker
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for comment in all_comments:
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comment_sentiment = get_sentiment_score(comment.body)
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for ticker_symbol in tickers_in_title:
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ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
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database.add_mention(conn, ticker_id, subreddit_id, submission.id, 'comment', int(comment.created_utc), comment_sentiment)
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# --- CASE B: No tickers in the title, scan comments individually ---
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else:
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for comment in all_comments:
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tickers_in_comment = set(extract_tickers(comment.body))
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if tickers_in_comment:
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all_tickers_found_in_post.update(tickers_in_comment) # Add to our set for financials
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comment_sentiment = get_sentiment_score(comment.body)
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for ticker_symbol in tickers_in_comment:
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ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
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database.add_mention(conn, ticker_id, subreddit_id, submission.id, 'comment', int(comment.created_utc), comment_sentiment)
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# --- EFFICIENT FINANCIALS UPDATE ---
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# Now, update market cap once for every unique ticker found in the whole post
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for ticker_symbol in all_tickers_found_in_post:
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ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
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ticker_info = database.get_ticker_info(conn, ticker_id)
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if not ticker_info['last_updated'] or (current_time - ticker_info['last_updated'] > MARKET_CAP_REFRESH_INTERVAL):
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print(f" -> Fetching financial data for {ticker_symbol}...")
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financials = get_financial_data(ticker_symbol)
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database.update_ticker_financials(
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conn, ticker_id,
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financials['market_cap'] or ticker_info['market_cap'],
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financials['closing_price'] or ticker_info['closing_price']
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)
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# --- DEEP DIVE SAVE (Still valuable) ---
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all_comment_sentiments = [get_sentiment_score(c.body) for c in all_comments]
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avg_sentiment = sum(all_comment_sentiments) / len(all_comment_sentiments) if all_comment_sentiments else 0
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post_analysis_data = {
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"post_id": submission.id, "title": submission.title,
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"post_url": f"https://reddit.com{submission.permalink}", "subreddit_id": subreddit_id,
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"post_timestamp": int(submission.created_utc), "comment_count": len(all_comments),
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"avg_comment_sentiment": avg_sentiment
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}
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database.add_or_update_post_analysis(conn, post_analysis_data)
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except Exception as e:
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print(f"Could not scan r/{subreddit_name}. Error: {e}")
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conn.close()
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print("\n--- Scan Complete ---")
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def main():
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"""Main function to run the Reddit stock analysis tool."""
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parser = argparse.ArgumentParser(description="Analyze stock ticker mentions on Reddit.", formatter_class=argparse.RawTextHelpFormatter)
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parser.add_argument("--config", default="subreddits.json", help="Path to the JSON file containing subreddits.\n(Default: subreddits.json)")
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parser.add_argument("--subreddit", help="Scan a single subreddit, ignoring the config file.")
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parser.add_argument("--days", type=int, default=1, help="Number of past days to scan for new posts.\n(Default: 1 for last 24 hours)")
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parser.add_argument("-p", "--posts", type=int, default=200, help="Max posts to check per subreddit.\n(Default: 200)")
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parser.add_argument("-c", "--comments", type=int, default=100, help="Number of comments to scan per post.\n(Default: 100)")
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parser.add_argument("-l", "--limit", type=int, default=20, help="Number of tickers to show in the CLI report.\n(Default: 20)")
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args = parser.parse_args()
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# --- THIS IS THE CORRECTED LOGIC BLOCK ---
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if args.subreddit:
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# If --subreddit is used, create a list with just that one.
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subreddits_to_scan = [args.subreddit]
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print(f"Targeted Scan Mode: Focusing on r/{args.subreddit}")
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else:
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# Otherwise, load from the config file.
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print(f"Config Scan Mode: Loading subreddits from {args.config}")
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# Use the correct argument name: args.config
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subreddits_to_scan = load_subreddits(args.config)
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if not subreddits_to_scan:
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print("Error: No subreddits to scan. Please check your config file or --subreddit argument.")
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return
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# --- Initialize and Run ---
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database.initialize_db()
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database.clean_stale_tickers()
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reddit = get_reddit_instance()
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if not reddit: return
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scan_subreddits(
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reddit,
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subreddits_to_scan,
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post_limit=args.posts,
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comment_limit=args.comments,
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days_to_scan=args.days
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)
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database.generate_summary_report(limit=args.limit)
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if __name__ == "__main__":
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main() |