119 lines
3.9 KiB
Python
119 lines
3.9 KiB
Python
# main.py
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import argparse
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import json
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import os
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from collections import Counter
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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 ticker_extractor import extract_tickers
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# Load environment variables from .env file
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load_dotenv()
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def load_subreddits(filepath):
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"""Loads a list of subreddits from a JSON file."""
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try:
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with open(filepath, 'r') as f:
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data = json.load(f)
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return data.get("subreddits", [])
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except FileNotFoundError:
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print(f"Error: The file '{filepath}' was not found.")
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return None
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except json.JSONDecodeError:
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print(f"Error: Could not decode JSON from '{filepath}'.")
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return None
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def get_market_cap(ticker_symbol):
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"""Fetches the market capitalization for a given stock ticker."""
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try:
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ticker = yf.Ticker(ticker_symbol)
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market_cap = ticker.info.get('marketCap')
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if market_cap:
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# Formatting for better readability
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return f"${market_cap:,}"
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return "N/A"
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except Exception as e:
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# yfinance can sometimes fail for various reasons (e.g., invalid ticker)
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return "N/A"
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def get_reddit_instance():
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"""Initializes and returns a PRAW 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(
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client_id=client_id,
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client_secret=client_secret,
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user_agent=user_agent
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)
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def scan_subreddits(reddit, subreddits_list, post_limit=25):
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"""Scans subreddits for stock tickers and returns a count of each."""
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all_tickers = Counter()
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print(f"\nScanning {len(subreddits_list)} subreddits for top {post_limit} posts...")
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for subreddit_name in subreddits_list:
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try:
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subreddit = reddit.subreddit(subreddit_name)
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print(f"r/{subreddit_name}...")
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# Fetch hot posts from the subreddit
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for submission in subreddit.hot(limit=post_limit):
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# Combine title and selftext for analysis
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full_text = submission.title + " " + submission.selftext
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# Extract tickers from the combined text
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tickers_in_post = extract_tickers(full_text)
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all_tickers.update(tickers_in_post)
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# Future work: also scan comments
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# submission.comments.replace_more(limit=0) # Expand all comment trees
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# for comment in submission.comments.list():
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# tickers_in_comment = extract_tickers(comment.body)
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# all_tickers.update(tickers_in_comment)
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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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return all_tickers
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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.")
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parser.add_argument("config_file", help="Path to the JSON file containing subreddits.")
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args = parser.parse_args()
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# --- Part 1: Load Configuration & Initialize Reddit ---
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subreddits = load_subreddits(args.config_file)
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if not subreddits:
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return
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reddit = get_reddit_instance()
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if not reddit:
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return
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# --- Part 2: Scan Reddit for Tickers ---
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ticker_counts = scan_subreddits(reddit, subreddits)
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if not ticker_counts:
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print("No tickers found.")
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return
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print("\n--- Scan Complete ---")
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print("Top 15 mentioned tickers:")
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# --- Part 3: Display Results ---
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# We will enrich this data with market cap and sentiment in the next steps
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for ticker, count in ticker_counts.most_common(15):
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print(f"{ticker}: {count} mentions")
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if __name__ == "__main__":
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main() |