# main.py

import argparse
import json
import os
from collections import Counter

import praw
import yfinance as yf
from dotenv import load_dotenv

from ticker_extractor import extract_tickers

# Load environment variables from .env file
load_dotenv()

def load_subreddits(filepath):
    """Loads a list of subreddits from a JSON file."""
    try:
        with open(filepath, 'r') as f:
            data = json.load(f)
            return data.get("subreddits", [])
    except FileNotFoundError:
        print(f"Error: The file '{filepath}' was not found.")
        return None
    except json.JSONDecodeError:
        print(f"Error: Could not decode JSON from '{filepath}'.")
        return None

def get_market_cap(ticker_symbol):
    """Fetches the market capitalization for a given stock ticker."""
    try:
        ticker = yf.Ticker(ticker_symbol)
        market_cap = ticker.info.get('marketCap')
        if market_cap:
            # Formatting for better readability
            return f"${market_cap:,}"

        return "N/A"
    except Exception as e:
        # yfinance can sometimes fail for various reasons (e.g., invalid ticker)
        return "N/A"

def get_reddit_instance():
    """Initializes and returns a PRAW 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 in .env file.")
        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 for stock tickers and returns a count of each."""
    all_tickers = Counter()

    print(f"\nScanning {len(subreddits_list)} subreddits for top {post_limit} posts...")
    for subreddit_name in subreddits_list:
        try:
            subreddit = reddit.subreddit(subreddit_name)
            print(f"r/{subreddit_name}...")
            # Fetch hot posts from the subreddit
            for submission in subreddit.hot(limit=post_limit):
                # Combine title and selftext for analysis
                full_text = submission.title + " " + submission.selftext

                # Extract tickers from the combined text
                tickers_in_post = extract_tickers(full_text)
                all_tickers.update(tickers_in_post)

                # Future work: also scan comments
                # submission.comments.replace_more(limit=0) # Expand all comment trees
                # for comment in submission.comments.list():
                #     tickers_in_comment = extract_tickers(comment.body)
                #     all_tickers.update(tickers_in_comment)

        except Exception as e:
            print(f"Could not scan r/{subreddit_name}. Error: {e}")

    return all_tickers

def main():
    """Main function to run the Reddit stock analysis tool."""
    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()

    # --- Part 1: Load Configuration & Initialize Reddit ---
    subreddits = load_subreddits(args.config_file)
    if not subreddits:
        return

    reddit = get_reddit_instance()
    if not reddit:
        return

    # --- Part 2: Scan Reddit for Tickers ---
    ticker_counts = scan_subreddits(reddit, subreddits)
    if not ticker_counts:
        print("No tickers found.")
        return

    print("\n--- Scan Complete ---")
    print("Top 15 mentioned tickers:")

    # --- Part 3: Display Results ---
    # We will enrich this data with market cap and sentiment in the next steps
    for ticker, count in ticker_counts.most_common(15):
        print(f"{ticker}: {count} mentions")

if __name__ == "__main__":
    main()