# rstat_tool/database.py

import sqlite3
import time
from .ticker_extractor import COMMON_WORDS_BLACKLIST
from .logger_setup import logger as log
from datetime import datetime, timedelta, timezone

DB_FILE = "reddit_stocks.db"
MARKET_CAP_REFRESH_INTERVAL = 86400

def clean_stale_tickers():
    """
    Removes tickers and their associated mentions from the database
    if the ticker symbol exists in the COMMON_WORDS_BLACKLIST.
    """
    log.info("\n--- Cleaning Stale Tickers from Database ---")
    conn = get_db_connection()
    cursor = conn.cursor()

    placeholders = ','.join('?' for _ in COMMON_WORDS_BLACKLIST)
    query = f"SELECT id, symbol FROM tickers WHERE symbol IN ({placeholders})"
    
    cursor.execute(query, tuple(COMMON_WORDS_BLACKLIST))
    stale_tickers = cursor.fetchall()

    if not stale_tickers:
        log.info("No stale tickers to clean.")
        conn.close()
        return

    for ticker in stale_tickers:
        ticker_id = ticker['id']
        ticker_symbol = ticker['symbol']
        log.info(f"Removing stale ticker '{ticker_symbol}' (ID: {ticker_id})...")
        cursor.execute("DELETE FROM mentions WHERE ticker_id = ?", (ticker_id,))
        cursor.execute("DELETE FROM tickers WHERE id = ?", (ticker_id,))
    
    deleted_count = conn.total_changes
    conn.commit()
    conn.close()
    log.info(f"Cleanup complete. Removed {deleted_count} records.")

def clean_stale_subreddits(active_subreddits):
    """
    Removes all data associated with subreddits that are NOT in the active list.
    """
    log.info("\n--- Cleaning Stale Subreddits from Database ---")
    conn = get_db_connection()
    cursor = conn.cursor()

    # Convert the list of active subreddits from the config file to a lowercase set for fast,
    # case-insensitive lookups.
    active_subreddits_lower = {sub.lower() for sub in active_subreddits}

    cursor.execute("SELECT id, name FROM subreddits")
    db_subreddits = cursor.fetchall()
    stale_sub_ids = []
    for sub in db_subreddits:
        if sub['name'] not in active_subreddits_lower:
            log.info(f"Found stale subreddit to remove: r/{sub['name']}")
            stale_sub_ids.append(sub['id'])
    if not stale_sub_ids:
        log.info("No stale subreddits to clean.")
        conn.close()
        return
    for sub_id in stale_sub_ids:
        log.info(f"  -> Deleting associated data for subreddit ID: {sub_id}")
        cursor.execute("DELETE FROM mentions WHERE subreddit_id = ?", (sub_id,))
        cursor.execute("DELETE FROM posts WHERE subreddit_id = ?", (sub_id,))
        cursor.execute("DELETE FROM subreddits WHERE id = ?", (sub_id,))
    conn.commit()
    conn.close()
    log.info("Stale subreddit cleanup complete.")

def get_db_connection():
    conn = sqlite3.connect(DB_FILE)
    conn.row_factory = sqlite3.Row
    return conn

def initialize_db():
    conn = get_db_connection()
    cursor = conn.cursor()
    cursor.execute("""
        CREATE TABLE IF NOT EXISTS tickers (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            symbol TEXT NOT NULL UNIQUE,
            market_cap INTEGER,
            closing_price REAL,
            last_updated INTEGER
        )
    """)
    cursor.execute("""
        CREATE TABLE IF NOT EXISTS subreddits (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            name TEXT NOT NULL UNIQUE
        )
    """)
    cursor.execute("""
        CREATE TABLE IF NOT EXISTS mentions (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            ticker_id INTEGER,
            subreddit_id INTEGER,
            post_id TEXT NOT NULL,
            mention_type TEXT NOT NULL,
            mention_sentiment REAL,
            post_avg_sentiment REAL,
            mention_timestamp INTEGER NOT NULL,
            FOREIGN KEY (ticker_id) REFERENCES tickers (id),
            FOREIGN KEY (subreddit_id) REFERENCES subreddits (id)
        )
    """)
    cursor.execute("""
        CREATE TABLE IF NOT EXISTS posts (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            post_id TEXT NOT NULL UNIQUE,
            title TEXT NOT NULL,
            post_url TEXT,
            subreddit_id INTEGER,
            post_timestamp INTEGER,
            comment_count INTEGER,
            avg_comment_sentiment REAL,
            FOREIGN KEY (subreddit_id) REFERENCES subreddits (id)
        )
    """)
    conn.commit()
    conn.close()
    log.info("Database initialized successfully.")

def add_mention(conn, ticker_id, subreddit_id, post_id, mention_type, timestamp, mention_sentiment, post_avg_sentiment=None):
    cursor = conn.cursor()
    try:
        cursor.execute(
            """
            INSERT INTO mentions (ticker_id, subreddit_id, post_id, mention_type, mention_timestamp, mention_sentiment, post_avg_sentiment)
            VALUES (?, ?, ?, ?, ?, ?, ?)
            """,
            (ticker_id, subreddit_id, post_id, mention_type, timestamp, mention_sentiment, post_avg_sentiment)
        )
        conn.commit()
    except sqlite3.IntegrityError:
        pass

def get_or_create_entity(conn, table_name, column_name, value):
    """Generic function to get or create an entity and return its ID."""
    cursor = conn.cursor()
    cursor.execute(f"SELECT id FROM {table_name} WHERE {column_name} = ?", (value,))
    result = cursor.fetchone()
    if result:
        return result['id']
    else:
        cursor.execute(f"INSERT INTO {table_name} ({column_name}) VALUES (?)", (value,))
        conn.commit()
        return cursor.lastrowid

def update_ticker_financials(conn, ticker_id, market_cap, closing_price):
    """Updates the financials and timestamp for a specific ticker."""
    cursor = conn.cursor()
    current_timestamp = int(time.time())
    cursor.execute(
        "UPDATE tickers SET market_cap = ?, closing_price = ?, last_updated = ? WHERE id = ?",
        (market_cap, closing_price, current_timestamp, ticker_id)
    )
    conn.commit()

def get_ticker_info(conn, ticker_id):
    """Retrieves all info for a specific ticker by its ID."""
    cursor = conn.cursor()
    cursor.execute("SELECT * FROM tickers WHERE id = ?", (ticker_id,))
    return cursor.fetchone()

def get_week_start_end(for_date):
    """
    Calculates the start (Monday, 00:00:00) and end (Sunday, 23:59:59)
    of the week that a given date falls into.
    Returns two datetime objects.
    """
    # Monday is 0, Sunday is 6
    start_of_week = for_date - timedelta(days=for_date.weekday())
    end_of_week = start_of_week + timedelta(days=6)
    
    # Set time to the very beginning and very end of the day for an inclusive range
    start_of_week = start_of_week.replace(hour=0, minute=0, second=0, microsecond=0)
    end_of_week = end_of_week.replace(hour=23, minute=59, second=59, microsecond=999999)
    
    return start_of_week, end_of_week

def add_or_update_post_analysis(conn, post_data):
    """
    Inserts a new post analysis record or updates an existing one.
    This prevents duplicate entries for the same post.
    """
    cursor = conn.cursor()
    # Use the UNIQUE post_id to replace old data with new on conflict
    cursor.execute(
        """
        INSERT INTO posts (post_id, title, post_url, subreddit_id, post_timestamp, comment_count, avg_comment_sentiment)
        VALUES (:post_id, :title, :post_url, :subreddit_id, :post_timestamp, :comment_count, :avg_comment_sentiment)
        ON CONFLICT(post_id) DO UPDATE SET
            comment_count = excluded.comment_count,
            avg_comment_sentiment = excluded.avg_comment_sentiment;
        """,
        post_data
    )
    conn.commit()

def get_overall_summary(limit=10):
    """
    Gets the top tickers across all subreddits from the LAST 24 HOURS.
    """
    conn = get_db_connection()
    one_day_ago = datetime.now(timezone.utc) - timedelta(days=1)
    one_day_ago_timestamp = int(one_day_ago.timestamp())
    
    query = """
        SELECT t.symbol, t.market_cap, t.closing_price, COUNT(m.id) as mention_count,
            SUM(CASE WHEN m.mention_sentiment > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
            SUM(CASE WHEN m.mention_sentiment < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
            SUM(CASE WHEN m.mention_sentiment BETWEEN -0.1 AND 0.1 THEN 1 ELSE 0 END) as neutral_mentions
        FROM mentions m JOIN tickers t ON m.ticker_id = t.id
        WHERE m.mention_timestamp >= ? -- <-- ADDED TIME FILTER
        GROUP BY t.symbol, t.market_cap, t.closing_price
        ORDER BY mention_count DESC LIMIT ?;
    """
    results = conn.execute(query, (one_day_ago_timestamp, limit)).fetchall()
    conn.close()
    return results

def get_subreddit_summary(subreddit_name, limit=10):
    """
    Gets the top tickers for a specific subreddit from the LAST 24 HOURS.
    """
    conn = get_db_connection()
    one_day_ago = datetime.now(timezone.utc) - timedelta(days=1)
    one_day_ago_timestamp = int(one_day_ago.timestamp())
    
    query = """
        SELECT t.symbol, t.market_cap, t.closing_price, COUNT(m.id) as mention_count,
            SUM(CASE WHEN m.mention_sentiment > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
            SUM(CASE WHEN m.mention_sentiment < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
            SUM(CASE WHEN m.mention_sentiment BETWEEN -0.1 AND 0.1 THEN 1 ELSE 0 END) as neutral_mentions
        FROM mentions m JOIN tickers t ON m.ticker_id = t.id JOIN subreddits s ON m.subreddit_id = s.id
        WHERE LOWER(s.name) = LOWER(?) AND m.mention_timestamp >= ? -- <-- ADDED TIME FILTER
        GROUP BY t.symbol, t.market_cap, t.closing_price
        ORDER BY mention_count DESC LIMIT ?;
    """
    results = conn.execute(query, (subreddit_name, one_day_ago_timestamp, limit)).fetchall()
    conn.close()
    return results

def get_daily_summary_for_subreddit(subreddit_name):
    """ Gets a summary for the DAILY image view (last 24 hours). """
    conn = get_db_connection()
    one_day_ago = datetime.now(timezone.utc) - timedelta(days=1)
    one_day_ago_timestamp = int(one_day_ago.timestamp())
    query = """
        SELECT
            t.symbol, t.market_cap, t.closing_price,
            COUNT(m.id) as total_mentions,
            COUNT(CASE WHEN m.mention_sentiment > 0.1 THEN 1 END) as bullish_mentions,
            COUNT(CASE WHEN m.mention_sentiment < -0.1 THEN 1 END) as bearish_mentions
        FROM mentions m JOIN tickers t ON m.ticker_id = t.id JOIN subreddits s ON m.subreddit_id = s.id
        WHERE LOWER(s.name) = LOWER(?) AND m.mention_timestamp >= ?
        GROUP BY t.symbol, t.market_cap, t.closing_price
        ORDER BY total_mentions DESC LIMIT 10;
    """
    results = conn.execute(query, (subreddit_name, one_day_ago_timestamp)).fetchall()
    conn.close()
    return results

def get_weekly_summary_for_subreddit(subreddit_name, for_date):
    """ Gets a summary for the WEEKLY image view (full week). """
    conn = get_db_connection()
    start_of_week, end_of_week = get_week_start_end(for_date)
    start_timestamp = int(start_of_week.timestamp())
    end_timestamp = int(end_of_week.timestamp())
    query = """
        SELECT
            t.symbol, t.market_cap, t.closing_price,
            COUNT(m.id) as total_mentions,
            COUNT(CASE WHEN m.mention_sentiment > 0.1 THEN 1 END) as bullish_mentions,
            COUNT(CASE WHEN m.mention_sentiment < -0.1 THEN 1 END) as bearish_mentions
        FROM mentions m JOIN tickers t ON m.ticker_id = t.id JOIN subreddits s ON m.subreddit_id = s.id
        WHERE LOWER(s.name) = LOWER(?) AND m.mention_timestamp BETWEEN ? AND ?
        GROUP BY t.symbol, t.market_cap, t.closing_price
        ORDER BY total_mentions DESC LIMIT 10;
    """
    results = conn.execute(query, (subreddit_name, start_timestamp, end_timestamp)).fetchall()
    conn.close()
    return results, start_of_week, end_of_week

def get_overall_image_view_summary():
    """
    Gets a summary of top tickers across ALL subreddits for the DAILY image view (last 24 hours).
    """
    conn = get_db_connection()
    one_day_ago = datetime.now(timezone.utc) - timedelta(days=1)
    one_day_ago_timestamp = int(one_day_ago.timestamp())
    query = """
        SELECT
            t.symbol, t.market_cap, t.closing_price,
            COUNT(m.id) as total_mentions,
            COUNT(CASE WHEN m.mention_sentiment > 0.1 THEN 1 END) as bullish_mentions,
            COUNT(CASE WHEN m.mention_sentiment < -0.1 THEN 1 END) as bearish_mentions
        FROM mentions m JOIN tickers t ON m.ticker_id = t.id
        WHERE m.mention_timestamp >= ? -- <-- ADDED TIME FILTER
        GROUP BY t.symbol, t.market_cap, t.closing_price
        ORDER BY total_mentions DESC LIMIT 10;
    """
    results = conn.execute(query, (one_day_ago_timestamp,)).fetchall()
    conn.close()
    return results

def get_overall_daily_summary():
    """
    Gets the top tickers across all subreddits from the LAST 24 HOURS.
    (This is a copy of get_overall_summary, renamed for clarity).
    """
    conn = get_db_connection()
    one_day_ago = datetime.now(timezone.utc) - timedelta(days=1)
    one_day_ago_timestamp = int(one_day_ago.timestamp())
    query = """
        SELECT t.symbol, t.market_cap, t.closing_price, COUNT(m.id) as total_mentions,
            SUM(CASE WHEN m.mention_sentiment > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
            SUM(CASE WHEN m.mention_sentiment < -0.1 THEN 1 ELSE 0 END) as bearish_mentions
        FROM mentions m JOIN tickers t ON m.ticker_id = t.id
        WHERE m.mention_timestamp >= ?
        GROUP BY t.symbol, t.market_cap, t.closing_price
        ORDER BY total_mentions DESC LIMIT 10;
    """
    results = conn.execute(query, (one_day_ago_timestamp,)).fetchall()
    conn.close()
    return results

def get_overall_weekly_summary():
    """
    Gets the top tickers across all subreddits for the LAST 7 DAYS.
    """
    conn = get_db_connection()
    today = datetime.now(timezone.utc)
    start_of_week, end_of_week = get_week_start_end(today - timedelta(days=7)) # Get last week's boundaries
    start_timestamp = int(start_of_week.timestamp())
    end_timestamp = int(end_of_week.timestamp())
    query = """
        SELECT t.symbol, t.market_cap, t.closing_price, COUNT(m.id) as total_mentions,
            SUM(CASE WHEN m.mention_sentiment > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
            SUM(CASE WHEN m.mention_sentiment < -0.1 THEN 1 ELSE 0 END) as bearish_mentions
        FROM mentions m JOIN tickers t ON m.ticker_id = t.id
        WHERE m.mention_timestamp BETWEEN ? AND ?
        GROUP BY t.symbol, t.market_cap, t.closing_price
        ORDER BY total_mentions DESC LIMIT 10;
    """
    results = conn.execute(query, (start_timestamp, end_timestamp)).fetchall()
    conn.close()
    return results, start_of_week, end_of_week

def get_deep_dive_details(ticker_symbol):
    """ Gets all analyzed posts that mention a specific ticker. """
    conn = get_db_connection()
    query = """
        SELECT DISTINCT p.*, s.name as subreddit_name FROM posts p
        JOIN mentions m ON p.post_id = m.post_id JOIN tickers t ON m.ticker_id = t.id
        JOIN subreddits s ON p.subreddit_id = s.id
        WHERE LOWER(t.symbol) = LOWER(?) ORDER BY p.post_timestamp DESC;
    """
    results = conn.execute(query, (ticker_symbol,)).fetchall()
    conn.close()
    return results

def get_all_scanned_subreddits():
    """ Gets a unique list of all subreddits we have data for. """
    conn = get_db_connection()
    results = conn.execute("SELECT DISTINCT name FROM subreddits ORDER BY name ASC;").fetchall()
    conn.close()
    return [row['name'] for row in results]

def get_all_tickers():
    """Retrieves the ID and symbol of every ticker in the database."""
    conn = get_db_connection()
    results = conn.execute("SELECT id, symbol FROM tickers;").fetchall()
    conn.close()
    return results

def get_ticker_by_symbol(symbol):
    """
    Retrieves a single ticker's ID and symbol from the database.
    The search is case-insensitive. Returns a Row object or None if not found.
    """
    conn = get_db_connection()
    cursor = conn.cursor()
    cursor.execute("SELECT id, symbol FROM tickers WHERE LOWER(symbol) = LOWER(?)", (symbol,))
    result = cursor.fetchone()
    conn.close()
    return result

def get_top_daily_ticker_symbols():
    """Gets a simple list of the Top 10 ticker symbols from the last 24 hours."""
    conn = get_db_connection()
    one_day_ago = datetime.now(timezone.utc) - timedelta(days=1)
    one_day_ago_timestamp = int(one_day_ago.timestamp())
    query = """
        SELECT t.symbol FROM mentions m JOIN tickers t ON m.ticker_id = t.id
        WHERE m.mention_timestamp >= ?
        GROUP BY t.symbol ORDER BY COUNT(m.id) DESC LIMIT 10;
    """
    results = conn.execute(query, (one_day_ago_timestamp,)).fetchall()
    conn.close()
    return [row['symbol'] for row in results] # Return a simple list of strings

def get_top_weekly_ticker_symbols():
    """Gets a simple list of the Top 10 ticker symbols from the last 7 days."""
    conn = get_db_connection()
    seven_days_ago = datetime.now(timezone.utc) - timedelta(days=7)
    seven_days_ago_timestamp = int(seven_days_ago.timestamp())
    query = """
        SELECT t.symbol FROM mentions m JOIN tickers t ON m.ticker_id = t.id
        WHERE m.mention_timestamp >= ?
        GROUP BY t.symbol ORDER BY COUNT(m.id) DESC LIMIT 10;
    """
    results = conn.execute(query, (seven_days_ago_timestamp,)).fetchall()
    conn.close()
    return [row['symbol'] for row in results] # Return a simple list of strings

def get_top_daily_ticker_symbols_for_subreddit(subreddit_name):
    """Gets a list of the Top 10 daily ticker symbols for a specific subreddit."""
    conn = get_db_connection()
    one_day_ago = datetime.now(timezone.utc) - timedelta(days=1)
    one_day_ago_timestamp = int(one_day_ago.timestamp())
    query = """
        SELECT t.symbol FROM mentions m JOIN tickers t ON m.ticker_id = t.id
        JOIN subreddits s ON m.subreddit_id = s.id
        WHERE LOWER(s.name) = LOWER(?) AND m.mention_timestamp >= ?
        GROUP BY t.symbol ORDER BY COUNT(m.id) DESC LIMIT 10;
    """
    results = conn.execute(query, (subreddit_name, one_day_ago_timestamp,)).fetchall()
    conn.close()
    return [row['symbol'] for row in results]

def get_top_weekly_ticker_symbols_for_subreddit(subreddit_name):
    """Gets a list of the Top 10 weekly ticker symbols for a specific subreddit."""
    conn = get_db_connection()
    seven_days_ago = datetime.now(timezone.utc) - timedelta(days=7)
    seven_days_ago_timestamp = int(seven_days_ago.timestamp())
    query = """
        SELECT t.symbol FROM mentions m JOIN tickers t ON m.ticker_id = t.id
        JOIN subreddits s ON m.subreddit_id = s.id
        WHERE LOWER(s.name) = LOWER(?) AND m.mention_timestamp >= ?
        GROUP BY t.symbol ORDER BY COUNT(m.id) DESC LIMIT 10;
    """
    results = conn.execute(query, (subreddit_name, seven_days_ago_timestamp,)).fetchall()
    conn.close()
    return [row['symbol'] for row in results]