pkhamre/reddit_stock_analyzer
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Added better dashboarding.

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Pål-Kristian Hamre
2025-07-21 23:06:29 +02:00
parent 0c90fed0eb
commit d375f4ef38
10 changed files with 513 additions and 145 deletions
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120
rstat_tool/main.py
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@@ -15,21 +15,23 @@ from .sentiment_analyzer import get_sentiment_score
load_dotenv()
MARKET_CAP_REFRESH_INTERVAL = 86400
POST_AGE_LIMIT = 86400
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}")
print(f"Error loading config file '{filepath}': {e}")
return None
def get_market_cap(ticker_symbol):
def get_financial_data(ticker_symbol):
try:
ticker = yf.Ticker(ticker_symbol)
return ticker.fast_info.get('marketCap')
data = { "market_cap": ticker.fast_info.get('marketCap'), "closing_price": ticker.fast_info.get('previousClose') }
return data
except Exception:
return None
return {"market_cap": None, "closing_price": None}
def get_reddit_instance():
client_id = os.getenv("REDDIT_CLIENT_ID")
@@ -38,59 +40,55 @@ def get_reddit_instance():
if not all([client_id, client_secret, user_agent]):
print("Error: Reddit API credentials not found in .env file.")
return None
# --- THIS IS THE CORRECTED LINE ---
# The argument is 'client_secret', not 'secret_client'.
return praw.Reddit(client_id=client_id, client_secret=client_secret, user_agent=user_agent)
def scan_subreddits(reddit, subreddits_list, post_limit=25, comment_limit=100):
"""Scans subreddits, analyzes posts and comments, and stores results in the database."""
def scan_subreddits(reddit, subreddits_list, post_limit=100, comment_limit=100, days_to_scan=1):
conn = database.get_db_connection()
post_age_limit = days_to_scan * 86400
current_time = time.time()
print(f"\nScanning {len(subreddits_list)} subreddits (Top {post_limit} posts, {comment_limit} comments/post)...")
print(f"\nScanning {len(subreddits_list)} subreddit(s) for NEW posts in the last {days_to_scan} day(s)...")
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):
# --- LOGIC PART 1: PROCESS INDIVIDUAL MENTIONS ---
# 1a. Process the Post Title and Body for mentions
for submission in subreddit.new(limit=post_limit):
if (current_time - submission.created_utc) > post_age_limit:
print(f" -> Reached posts older than the {days_to_scan}-day limit. Moving to next subreddit.")
break
post_text = submission.title + " " + submission.selftext
tickers_in_post = extract_tickers(post_text)
post_sentiment = get_sentiment_score(submission.title)
for ticker_symbol in set(tickers_in_post):
ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
database.add_mention(conn, ticker_id, subreddit_id, submission.id, int(submission.created_utc), post_sentiment)
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'])
# 1b. Process Comments for mentions
submission.comments.replace_more(limit=0)
for comment in submission.comments.list()[:comment_limit]:
tickers_in_comment = extract_tickers(comment.body)
if not tickers_in_comment:
continue
comment_sentiment = get_sentiment_score(comment.body)
for ticker_symbol in set(tickers_in_comment):
if tickers_in_post:
post_sentiment = get_sentiment_score(submission.title)
for ticker_symbol in set(tickers_in_post):
ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
database.add_mention(conn, ticker_id, subreddit_id, submission.id, int(comment.created_utc), comment_sentiment)
# --- LOGIC PART 2: DEEP DIVE ANALYSIS ---
database.add_mention(conn, ticker_id, subreddit_id, submission.id, 'post', int(submission.created_utc), post_sentiment)
ticker_info = database.get_ticker_info(conn, ticker_id)
if not ticker_info['last_updated'] or (current_time - ticker_info['last_updated'] > MARKET_CAP_REFRESH_INTERVAL):
print(f" -> Fetching financial data for {ticker_symbol}...")
financials = get_financial_data(ticker_symbol)
database.update_ticker_financials(
conn, ticker_id,
financials['market_cap'] or ticker_info['market_cap'],
financials['closing_price'] or ticker_info['closing_price']
)
submission.comments.replace_more(limit=0)
all_comment_sentiments = []
for comment in submission.comments.list()[:comment_limit]:
all_comment_sentiments.append(get_sentiment_score(comment.body))
tickers_in_comment = extract_tickers(comment.body)
if tickers_in_comment:
comment_sentiment = get_sentiment_score(comment.body)
for ticker_symbol in set(tickers_in_comment):
ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
database.add_mention(conn, ticker_id, subreddit_id, submission.id, 'comment', int(comment.created_utc), comment_sentiment)
avg_sentiment = sum(all_comment_sentiments) / len(all_comment_sentiments) if all_comment_sentiments else 0
post_analysis_data = {
"post_id": submission.id, "title": submission.title,
"post_url": f"https://reddit.com{submission.permalink}",
@@ -98,7 +96,7 @@ def scan_subreddits(reddit, subreddits_list, post_limit=25, comment_limit=100):
"comment_count": len(all_comment_sentiments), "avg_comment_sentiment": avg_sentiment
}
database.add_or_update_post_analysis(conn, post_analysis_data)
except Exception as e:
print(f"Could not scan r/{subreddit_name}. Error: {e}")
@@ -106,23 +104,47 @@ def scan_subreddits(reddit, subreddits_list, post_limit=25, comment_limit=100):
print("\n--- Scan Complete ---")
def main():
"""Main function to run the Reddit stock analysis tool."""
parser = argparse.ArgumentParser(description="Analyze stock ticker mentions on Reddit.", formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument("config_file", help="Path to the JSON file containing subreddits.")
parser.add_argument("-p", "--posts", type=int, default=25, help="Number of posts to scan per subreddit.\n(Default: 25)")
parser.add_argument("--config", default="subreddits.json", help="Path to the JSON file containing subreddits.\n(Default: subreddits.json)")
parser.add_argument("--subreddit", help="Scan a single subreddit, ignoring the config file.")
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)")
parser.add_argument("-p", "--posts", type=int, default=200, help="Max posts to check per subreddit.\n(Default: 200)")
parser.add_argument("-c", "--comments", type=int, default=100, help="Number of comments to scan per post.\n(Default: 100)")
parser.add_argument("-l", "--limit", type=int, default=20, help="Number of tickers to show in the final report.\n(Default: 20)")
parser.add_argument("-l", "--limit", type=int, default=20, help="Number of tickers to show in the CLI report.\n(Default: 20)")
args = parser.parse_args()
# --- THIS IS THE CORRECTED LOGIC BLOCK ---
if args.subreddit:
# If --subreddit is used, create a list with just that one.
subreddits_to_scan = [args.subreddit]
print(f"Targeted Scan Mode: Focusing on r/{args.subreddit}")
else:
# Otherwise, load from the config file.
print(f"Config Scan Mode: Loading subreddits from {args.config}")
# Use the correct argument name: args.config
subreddits_to_scan = load_subreddits(args.config)
if not subreddits_to_scan:
print("Error: No subreddits to scan. Please check your config file or --subreddit argument.")
return
# --- Initialize and Run ---
database.initialize_db()
database.clean_stale_tickers()
subreddits = load_subreddits(args.config_file)
if not subreddits: return
reddit = get_reddit_instance()
if not reddit: return
scan_subreddits(reddit, subreddits, post_limit=args.posts, comment_limit=args.comments)
scan_subreddits(
reddit,
subreddits_to_scan,
post_limit=args.posts,
comment_limit=args.comments,
days_to_scan=args.days
)
database.generate_summary_report(limit=args.limit)
if __name__ == "__main__":