"""
🤖 Universal Reddit Scraper Suite
Full-featured scraper with analytics, dashboard, notifications, and scheduling.
"""
import requests
import pandas as pd
import datetime
import time
import os
import xml.etree.ElementTree as ET
import argparse
import random
import sys
import json
import subprocess
import tempfile
from urllib.parse import urlparse
from pathlib import Path

# --- CONFIGURATION ---
USER_AGENT = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"

MIRRORS = [
    "https://old.reddit.com",
    "https://redlib.catsarch.com",
    "https://redlib.vsls.cz",
    "https://r.nf",
    "https://libreddit.northboot.xyz",
    "https://redlib.tux.pizza"
]

SEEN_URLS = set()
SESSION = requests.Session()
SESSION.headers.update({"User-Agent": USER_AGENT})

# --- DIRECTORY SETUP ---
def setup_directories(target, prefix):
    """Creates organized folder structure for scraped data."""
    base_dir = f"data/{prefix}_{target}"
    dirs = {
        "base": base_dir,
        "posts": f"{base_dir}/posts.csv",
        "comments": f"{base_dir}/comments.csv",
        "media": f"{base_dir}/media",
        "images": f"{base_dir}/media/images",
        "videos": f"{base_dir}/media/videos",
    }
    
    for key in ["base", "media", "images", "videos"]:
        if not os.path.exists(dirs[key]):
            os.makedirs(dirs[key])
    
    return dirs

def get_file_path(target, type_prefix):
    """Legacy function for backward compatibility."""
    if not os.path.exists("data"):
        os.makedirs("data")
    sanitized_target = target.replace("/", "_")
    return f"data/{type_prefix}_{sanitized_target}.csv"

def load_history(filepath):
    """Loads existing CSV history to prevent duplicates."""
    SEEN_URLS.clear()
    if os.path.exists(filepath):
        try:
            df = pd.read_csv(filepath)
            for url in df['permalink']:
                SEEN_URLS.add(str(url))
            print(f"📚 Loaded {len(SEEN_URLS)} existing items from {filepath}")
        except:
            pass

def save_posts_csv(posts, filepath):
    """Saves posts to CSV with all metadata."""
    if not posts:
        return 0
    
    new_posts = [p for p in posts if p['permalink'] not in SEEN_URLS]
    
    if new_posts:
        df = pd.DataFrame(new_posts)
        if os.path.exists(filepath):
            df.to_csv(filepath, mode='a', header=False, index=False)
        else:
            df.to_csv(filepath, index=False)
        
        for p in new_posts:
            SEEN_URLS.add(p['permalink'])
        
        print(f"✅ Saved {len(new_posts)} new posts")
        return len(new_posts)
    else:
        print("💤 No new unique posts found.")
        return 0

def save_comments_csv(comments, filepath):
    """Saves comments to CSV."""
    if not comments:
        return
    
    df = pd.DataFrame(comments)
    if os.path.exists(filepath):
        df.to_csv(filepath, mode='a', header=False, index=False)
    else:
        df.to_csv(filepath, index=False)
    
    print(f"💬 Saved {len(comments)} comments")

# --- MEDIA DOWNLOAD ---
def get_media_urls(post_data):
    """Extracts all media URLs from a post."""
    media = {"images": [], "videos": [], "galleries": []}
    
    url = post_data.get('url', '')
    if any(ext in url.lower() for ext in ['.jpg', '.jpeg', '.png', '.gif', '.webp']):
        media["images"].append(url)
    
    if 'i.redd.it' in url:
        media["images"].append(url)
    
    if post_data.get('is_video'):
        reddit_video = post_data.get('media', {})
        if reddit_video and 'reddit_video' in reddit_video:
            video_url = reddit_video['reddit_video'].get('fallback_url', '')
            if video_url:
                media["videos"].append(video_url.split('?')[0])
    
    preview = post_data.get('preview', {})
    if preview and 'images' in preview:
        for img in preview['images']:
            source = img.get('source', {})
            if source.get('url'):
                clean_url = source['url'].replace('&', '&')
                media["images"].append(clean_url)
    
    if post_data.get('is_gallery'):
        gallery_data = post_data.get('gallery_data', {})
        media_metadata = post_data.get('media_metadata', {})
        
        if gallery_data and media_metadata:
            for item in gallery_data.get('items', []):
                media_id = item.get('media_id')
                if media_id and media_id in media_metadata:
                    meta = media_metadata[media_id]
                    if meta.get('s', {}).get('u'):
                        clean_url = meta['s']['u'].replace('&', '&')
                        media["galleries"].append(clean_url)
    
    if 'youtube.com' in url or 'youtu.be' in url:
        media["videos"].append(url)
    
    return media

def download_media(url, save_path, media_type="image"):
    """Downloads a single media file."""
    try:
        if os.path.exists(save_path):
            return True
        
        response = SESSION.get(url, timeout=30, stream=True)
        if response.status_code == 200:
            with open(save_path, 'wb') as f:
                for chunk in response.iter_content(chunk_size=8192):
                    f.write(chunk)
            return True
    except Exception as e:
        pass
    return False

def download_reddit_video_with_audio(video_url, save_path):
    """
    Downloads Reddit video with audio by fetching both streams and merging.
    Reddit stores video and audio separately - this combines them.
    """
    try:
        if os.path.exists(save_path):
            return True
        
        # Try to find the audio URL by replacing video quality with audio
        # Reddit videos have audio at URLs like .../DASH_audio.mp4 or .../DASH_AUDIO_128.mp4
        base_url = video_url.rsplit('/', 1)[0]
        
        # Common audio URL patterns
        audio_urls = [
            f"{base_url}/DASH_audio.mp4",
            f"{base_url}/DASH_AUDIO_128.mp4",
            f"{base_url}/DASH_AUDIO_64.mp4",
            f"{base_url}/audio.mp4",
            f"{base_url}/audio"
        ]
        
        # Download video to temp file first
        with tempfile.NamedTemporaryFile(suffix='_video.mp4', delete=False) as video_temp:
            video_temp_path = video_temp.name
            response = SESSION.get(video_url, timeout=60, stream=True)
            if response.status_code != 200:
                return False
            for chunk in response.iter_content(chunk_size=8192):
                video_temp.write(chunk)
        
        # Try to download audio
        audio_temp_path = None
        for audio_url in audio_urls:
            try:
                response = SESSION.get(audio_url, timeout=30, stream=True)
                if response.status_code == 200:
                    with tempfile.NamedTemporaryFile(suffix='_audio.mp4', delete=False) as audio_temp:
                        audio_temp_path = audio_temp.name
                        for chunk in response.iter_content(chunk_size=8192):
                            audio_temp.write(chunk)
                    break
            except:
                continue
        
        if audio_temp_path:
            # Merge video and audio using ffmpeg
            try:
                cmd = [
                    'ffmpeg', '-y', '-hide_banner', '-loglevel', 'error',
                    '-i', video_temp_path,
                    '-i', audio_temp_path,
                    '-c:v', 'copy', '-c:a', 'aac',
                    '-shortest', save_path
                ]
                result = subprocess.run(cmd, capture_output=True, timeout=120)
                
                if result.returncode == 0:
                    # Cleanup temp files
                    os.unlink(video_temp_path)
                    os.unlink(audio_temp_path)
                    return True
                else:
                    # ffmpeg failed, fall back to video only
                    print(f"   ⚠️ ffmpeg merge failed, saving video without audio")
                    os.rename(video_temp_path, save_path)
                    os.unlink(audio_temp_path)
                    return True
            except FileNotFoundError:
                # ffmpeg not installed, save video only
                print(f"   ⚠️ ffmpeg not found, saving video without audio")
                os.rename(video_temp_path, save_path)
                if audio_temp_path:
                    os.unlink(audio_temp_path)
                return True
            except Exception as e:
                # Other error, save video only
                os.rename(video_temp_path, save_path)
                if audio_temp_path and os.path.exists(audio_temp_path):
                    os.unlink(audio_temp_path)
                return True
        else:
            # No audio found, just use video
            os.rename(video_temp_path, save_path)
            return True
            
    except Exception as e:
        # Cleanup any temp files on error
        pass
    return False

def download_post_media(post_data, dirs, post_id):
    """Downloads all media from a post."""
    media = get_media_urls(post_data)
    downloaded = {"images": 0, "videos": 0}
    
    for i, img_url in enumerate(media["images"][:5]):
        ext = os.path.splitext(urlparse(img_url).path)[1] or '.jpg'
        save_path = os.path.join(dirs["images"], f"{post_id}_{i}{ext}")
        if download_media(img_url, save_path, "image"):
            downloaded["images"] += 1
    
    for i, img_url in enumerate(media["galleries"][:10]):
        ext = '.jpg'
        save_path = os.path.join(dirs["images"], f"{post_id}_gallery_{i}{ext}")
        if download_media(img_url, save_path, "gallery"):
            downloaded["images"] += 1
    
    for i, vid_url in enumerate(media["videos"][:2]):
        if 'youtube' not in vid_url:
            ext = '.mp4'
            save_path = os.path.join(dirs["videos"], f"{post_id}_{i}{ext}")
            # Use enhanced download for Reddit videos (includes audio)
            if 'v.redd.it' in vid_url or 'reddit.com' in vid_url:
                if download_reddit_video_with_audio(vid_url, save_path):
                    downloaded["videos"] += 1
            elif download_media(vid_url, save_path, "video"):
                downloaded["videos"] += 1
    
    return downloaded

# --- COMMENT SCRAPING ---
def scrape_comments(permalink, max_depth=3):
    """Scrapes comments from a post."""
    comments = []
    
    try:
        if not permalink.startswith('http'):
            url = f"https://old.reddit.com{permalink}.json?limit=100"
        else:
            url = f"{permalink}.json?limit=100"
        
        response = SESSION.get(url, timeout=15)
        if response.status_code != 200:
            return comments
        
        data = response.json()
        
        if len(data) > 1:
            comment_data = data[1]['data']['children']
            comments = parse_comments(comment_data, permalink, depth=0, max_depth=max_depth)
    
    except Exception as e:
        pass
    
    if len(comments) > 0:
        print(f"   + Scraped {len(comments)} comments")
    
    return comments

def parse_comments(comment_list, post_permalink, depth=0, max_depth=3):
    """Recursively parses comments."""
    comments = []
    
    if depth > max_depth:
        return comments
    
    for item in comment_list:
        if item['kind'] != 't1':
            continue
        
        c = item['data']
        
        comment = {
            "post_permalink": post_permalink,
            "comment_id": c.get('id'),
            "parent_id": c.get('parent_id'),
            "author": c.get('author'),
            "body": c.get('body', ''),
            "score": c.get('score', 0),
            "created_utc": datetime.datetime.fromtimestamp(c.get('created_utc', 0)).isoformat(),
            "depth": depth,
            "is_submitter": c.get('is_submitter', False),
        }
        comments.append(comment)
        
        replies = c.get('replies')
        if replies and isinstance(replies, dict):
            reply_children = replies.get('data', {}).get('children', [])
            comments.extend(parse_comments(reply_children, post_permalink, depth + 1, max_depth))
    
    return comments

# --- POST EXTRACTION ---
def extract_post_data(post_json):
    """Extracts comprehensive post data."""
    p = post_json
    
    post_type = "text"
    if p.get('is_video'):
        post_type = "video"
    elif p.get('is_gallery'):
        post_type = "gallery"
    elif any(ext in p.get('url', '').lower() for ext in ['.jpg', '.jpeg', '.png', '.gif', '.webp']) or 'i.redd.it' in p.get('url', ''):
        post_type = "image"
    elif p.get('is_self'):
        post_type = "text"
    else:
        post_type = "link"
    
    return {
        "id": p.get('id'),
        "title": p.get('title'),
        "author": p.get('author'),
        "created_utc": datetime.datetime.fromtimestamp(p.get('created_utc', 0)).isoformat(),
        "permalink": p.get('permalink'),
        "url": p.get('url_overridden_by_dest', p.get('url')),
        "score": p.get('score', 0),
        "upvote_ratio": p.get('upvote_ratio', 0),
        "num_comments": p.get('num_comments', 0),
        "num_crossposts": p.get('num_crossposts', 0),
        "selftext": p.get('selftext', ''),
        "post_type": post_type,
        "is_nsfw": p.get('over_18', False),
        "is_spoiler": p.get('spoiler', False),
        "flair": p.get('link_flair_text', ''),
        "total_awards": p.get('total_awards_received', 0),
        "has_media": p.get('is_video', False) or p.get('is_gallery', False) or 'i.redd.it' in p.get('url', ''),
        "media_downloaded": False,
        "source": "History-Full"
    }

# --- FULL HISTORY SCRAPE ---
def run_full_history(target, limit, is_user=False, download_media_flag=True, 
                     scrape_comments_flag=True, dry_run=False, use_plugins=False):
    """
    Full scrape with images, videos, and comments.
    
    Args:
        target: Subreddit or username
        limit: Maximum posts to scrape
        is_user: True if target is a user
        download_media_flag: Download images/videos
        scrape_comments_flag: Scrape comments
        dry_run: Simulate without saving data
        use_plugins: Run post-processing plugins
    """
    prefix = "u" if is_user else "r"
    mode = "full" if download_media_flag and scrape_comments_flag else "history"
    
    # Display mode banner
    if dry_run:
        print("=" * 50)
        print("🧪 DRY RUN MODE - No data will be saved")
        print("=" * 50)
    
    print(f"🚀 Starting {'DRY RUN' if dry_run else 'FULL HISTORY'} scrape for {prefix}/{target}")
    print(f"   📊 Target posts: {limit}")
    print(f"   🖼️  Download media: {download_media_flag and not dry_run}")
    print(f"   💬 Scrape comments: {scrape_comments_flag}")
    print(f"   🔌 Plugins enabled: {use_plugins}")
    print("-" * 50)
    
    # Start job tracking
    job_id = None
    try:
        from export.database import start_job_record, complete_job_record
        job_id = start_job_record(target, mode, is_user, dry_run)
    except Exception as e:
        print(f"⚠️ Job tracking unavailable: {e}")
    
    # Setup directories (even for dry run, to check existing data)
    dirs = setup_directories(target, prefix)
    load_history(dirs["posts"])
    
    after = None
    total_posts = 0
    total_media = {"images": 0, "videos": 0}
    total_comments = 0
    all_scraped_posts = []  # For plugin processing
    all_scraped_comments = []
    start_time = time.time()
    error_msg = None
    
    try:
        while total_posts < limit:
            random.shuffle(MIRRORS)
            success = False
            
            for base_url in MIRRORS:
                try:
                    if is_user:
                        path = f"/user/{target}/submitted.json"
                    else:
                        path = f"/r/{target}/new.json"
                    
                    # Use proper batch size - min of remaining posts needed or 100 (Reddit's max per request)
                    batch_size = min(100, limit - total_posts)
                    target_url = f"{base_url}{path}?limit={batch_size}&raw_json=1"
                    if after:
                        target_url += f"&after={after}"
                    
                    print(f"\n📡 Fetching from: {base_url}")
                    response = SESSION.get(target_url, timeout=15)
                    
                    if response.status_code == 200:
                        data = response.json()
                        posts = []
                        batch_comments = []
                        
                        children = data['data']['children']
                        print(f"   Found {len(children)} posts in this batch")
                        
                        for child in children:
                            p = child['data']
                            post = extract_post_data(p)
                            
                            if post['permalink'] in SEEN_URLS:
                                continue
                            
                            # Download media (skip in dry run)
                            if download_media_flag and not dry_run:
                                downloaded = download_post_media(p, dirs, post['id'])
                                post['media_downloaded'] = downloaded['images'] > 0 or downloaded['videos'] > 0
                                total_media['images'] += downloaded['images']
                                total_media['videos'] += downloaded['videos']
                                
                                if downloaded['images'] > 0 or downloaded['videos'] > 0:
                                    print(f"   + Downloaded: {downloaded['images']} images, {downloaded['videos']} videos")
                            
                            posts.append(post)
                            
                            # Scrape comments
                            if scrape_comments_flag and post['num_comments'] > 0:
                                print(f"   💬 Fetching comments for: {post['title'][:40]}...")
                                comments = scrape_comments(post['permalink'])
                                batch_comments.extend(comments)
                                total_comments += len(comments)
                                time.sleep(1)
                        
                        # Collect for plugins
                        all_scraped_posts.extend(posts)
                        all_scraped_comments.extend(batch_comments)
                        
                        # Save data (skip in dry run)
                        if not dry_run:
                            saved = save_posts_csv(posts, dirs["posts"])
                            total_posts += saved
                            
                            if batch_comments:
                                save_comments_csv(batch_comments, dirs["comments"])
                        else:
                            # In dry run, just count
                            total_posts += len(posts)
                            print(f"   🧪 [DRY RUN] Would save {len(posts)} posts")
                        
                        print(f"\n📊 Progress: {total_posts}/{limit} posts")
                        print(f"   🖼️  Images: {total_media['images']} | 🎬 Videos: {total_media['videos']}")
                        print(f"   💬 Comments: {total_comments}")
                        
                        after = data['data'].get('after')
                        if not after:
                            print("\n🏁 Reached end of available history.")
                            break
                        
                        success = True
                        break
                        
                except Exception as e:
                    print(f"   ⚠️ Error with {base_url}: {e}")
                    continue
            
            if not after:
                break
                
            if not success:
                print("\n❌ All sources failed. Waiting 30s...")
                time.sleep(30)
            else:
                print(f"\n⏸️ Cooling down (3s)...")
                time.sleep(3)
        
        # Run plugins on collected data
        if use_plugins and (all_scraped_posts or all_scraped_comments):
            print("\n🔌 Running post-processing plugins...")
            try:
                from plugins import load_plugins, run_plugins
                plugins = load_plugins()
                if plugins:
                    all_scraped_posts, all_scraped_comments = run_plugins(
                        all_scraped_posts, all_scraped_comments, plugins
                    )
                    print(f"   ✅ Processed {len(all_scraped_posts)} posts with {len(plugins)} plugins")
                else:
                    print("   ⚠️ No plugins found")
            except Exception as e:
                print(f"   ⚠️ Plugin error: {e}")
    
    except Exception as e:
        error_msg = str(e)
        print(f"\n❌ Scrape error: {e}")
    
    duration = time.time() - start_time
    
    # Complete job tracking
    if job_id:
        try:
            status = 'failed' if error_msg else 'completed'
            complete_job_record(
                job_id, status, 
                total_posts, total_comments, 
                total_media['images'] + total_media['videos'],
                error_msg
            )
        except Exception as e:
            print(f"⚠️ Failed to complete job record: {e}")
    
    # Summary
    print("\n" + "=" * 50)
    if dry_run:
        print("🧪 DRY RUN COMPLETE!")
        print(f"   📊 Would scrape: {total_posts} posts")
        print(f"   💬 Would scrape: {total_comments} comments")
    else:
        print("✅ SCRAPE COMPLETE!")
        print(f"   📁 Data saved to: {dirs['base']}")
        print(f"   📊 Total posts: {total_posts}")
        print(f"   🖼️  Total images: {total_media['images']}")
        print(f"   🎬 Total videos: {total_media['videos']}")
        print(f"   💬 Total comments: {total_comments}")
    print(f"   ⏱️  Duration: {duration:.1f}s")
    
    return {
        'posts': total_posts,
        'images': total_media['images'],
        'videos': total_media['videos'],
        'comments': total_comments,
        'duration': f"{duration:.1f}s",
        'dry_run': dry_run,
        'job_id': job_id
    }

# --- MONITOR MODE ---
def run_monitor(target, is_user=False):
    prefix = "u" if is_user else "r"
    if is_user:
        rss_url = f"https://www.reddit.com/user/{target}/submitted.rss?limit=100"
    else:
        rss_url = f"https://www.reddit.com/r/{target}/new.rss?limit=100"

    print(f"[{datetime.datetime.now()}] 📡 Checking RSS for {prefix}/{target}...")
    
    try:
        response = SESSION.get(rss_url, timeout=15)
        
        if response.status_code != 200:
            print(f"❌ RSS blocked (Status {response.status_code}), trying JSON...")
            run_full_history(target, 25, is_user, download_media_flag=False, scrape_comments_flag=False)
            return

        root = ET.fromstring(response.content)
        namespace = {'atom': 'http://www.w3.org/2005/Atom'}
        posts = []
        
        for entry in root.findall('atom:entry', namespace):
            posts.append({
                "id": "",
                "title": entry.find('atom:title', namespace).text,
                "author": "",
                "created_utc": entry.find('atom:published', namespace).text,
                "permalink": entry.find('atom:link', namespace).attrib['href'],
                "url": entry.find('atom:link', namespace).attrib['href'],
                "score": 0,
                "upvote_ratio": 0,
                "num_comments": 0,
                "num_crossposts": 0,
                "selftext": "",
                "post_type": "unknown",
                "is_nsfw": False,
                "is_spoiler": False,
                "flair": "",
                "total_awards": 0,
                "has_media": False,
                "media_downloaded": False,
                "source": "Monitor-RSS"
            })
        
        dirs = setup_directories(target, prefix)
        save_posts_csv(posts, dirs["posts"])

    except Exception as e:
        print(f"❌ Monitor Error: {e}")

# --- CLI ---
def main():
    parser = argparse.ArgumentParser(
        description="🤖 Universal Reddit Scraper Suite",
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog="""
Commands:
  SCRAPING:
    python main.py <target> --mode full --limit 100
    python main.py <target> --mode history --limit 500
    python main.py <target> --mode monitor
    python main.py <target> --dry-run           # Test without saving
    python main.py <target> --plugins           # Enable post-processing
    
  SEARCH:
    python main.py --search "keyword" --subreddit delhi
    python main.py --search "keyword" --min-score 100
    
  DASHBOARD:
    python main.py --dashboard
    
  SCHEDULE:
    python main.py --schedule delhi --every 60
    
  ANALYTICS:
    python main.py --analyze delhi --sentiment
    python main.py --analyze delhi --keywords
    
  MAINTENANCE:
    python main.py --job-history                # View job history
    python main.py --backup                     # Backup database
    python main.py --vacuum                     # Optimize database
    python main.py --export-parquet python      # Export to Parquet
    python main.py --list-plugins               # List available plugins
    
  REST API:
    python main.py --api                        # Start REST API server
        """
    )
    
    # Scraping args
    parser.add_argument("target", nargs='?', help="Subreddit or username to scrape")
    parser.add_argument("--mode", choices=["monitor", "history", "full"], default="full")
    parser.add_argument("--user", action="store_true", help="Target is a user")
    parser.add_argument("--limit", type=int, default=100, help="Max posts to scrape")
    parser.add_argument("--no-media", action="store_true", help="Skip media download")
    parser.add_argument("--no-comments", action="store_true", help="Skip comments")
    
    # Dashboard
    parser.add_argument("--dashboard", action="store_true", help="Launch web dashboard")
    
    # Search
    parser.add_argument("--search", type=str, help="Search scraped data")
    parser.add_argument("--subreddit", type=str, help="Filter by subreddit")
    parser.add_argument("--min-score", type=int, help="Filter by minimum score")
    parser.add_argument("--author", type=str, help="Filter by author")
    
    # Analytics
    parser.add_argument("--analyze", type=str, help="Run analytics on subreddit")
    parser.add_argument("--sentiment", action="store_true", help="Run sentiment analysis")
    parser.add_argument("--keywords", action="store_true", help="Extract keywords")
    
    # Schedule
    parser.add_argument("--schedule", type=str, help="Schedule scraping for target")
    parser.add_argument("--every", type=int, help="Interval in minutes")
    
    # Alerts
    parser.add_argument("--alert", type=str, help="Set keyword alert")
    parser.add_argument("--discord-webhook", type=str, help="Discord webhook URL")
    parser.add_argument("--telegram-token", type=str, help="Telegram bot token")
    parser.add_argument("--telegram-chat", type=str, help="Telegram chat ID")
    
    # New: Observability & Maintenance
    parser.add_argument("--dry-run", action="store_true", help="Simulate scrape without saving data")
    parser.add_argument("--plugins", action="store_true", help="Enable post-processing plugins")
    parser.add_argument("--list-plugins", action="store_true", help="List available plugins")
    parser.add_argument("--job-history", action="store_true", help="View job history")
    parser.add_argument("--backup", action="store_true", help="Backup SQLite database")
    parser.add_argument("--vacuum", action="store_true", help="Optimize SQLite database")
    parser.add_argument("--export-parquet", type=str, help="Export subreddit to Parquet format")
    parser.add_argument("--api", action="store_true", help="Start REST API server (port 8000)")
    
    args = parser.parse_args()
    
    print("=" * 50)
    print("🤖 UNIVERSAL REDDIT SCRAPER SUITE")
    print("=" * 50)
    
    # Dashboard mode
    if args.dashboard:
        print("\n🌐 Launching Dashboard...")
        print("   Open: http://localhost:8501")
        os.system("streamlit run dashboard/app.py")
        return
    
    # REST API mode
    if args.api:
        print("\n🚀 Starting REST API server...")
        print("   📖 Docs: http://localhost:8000/docs")
        print("   📊 Connect Metabase/Grafana to http://localhost:8000")
        try:
            import uvicorn
            from api.server import app
            uvicorn.run(app, host="0.0.0.0", port=8000)
        except ImportError:
            print("❌ Install dependencies: pip install fastapi uvicorn")
        return
    
    # --- NEW: Maintenance & Observability Commands ---
    
    # Job history
    if args.job_history:
        from export.database import print_job_history
        print_job_history()
        return
    
    # Backup database
    if args.backup:
        from export.database import backup_database
        backup_database()
        return
    
    # Vacuum/optimize database
    if args.vacuum:
        from export.database import vacuum_database
        vacuum_database()
        return
    
    # Export to Parquet
    if args.export_parquet:
        from export.parquet import export_to_parquet
        prefix = "u" if args.user else "r"
        export_to_parquet(args.export_parquet, prefix=prefix)
        return
    
    # List plugins
    if args.list_plugins:
        from plugins import list_plugins
        list_plugins()
        return
    
    # Search mode
    if args.search:
        print(f"\n🔍 Searching for: {args.search}")
        from search.query import search_all_data, print_search_results
        
        results = search_all_data(
            query=args.search,
            min_score=args.min_score,
            author=args.author
        )
        print_search_results(results)
        return
    
    # Analytics mode
    if args.analyze:
        print(f"\n📊 Analyzing: {args.analyze}")
        
        # Load data
        data_dir = Path(f"data/r_{args.analyze}")
        if not data_dir.exists():
            print(f"❌ No data found for r/{args.analyze}")
            return
        
        posts_file = data_dir / "posts.csv"
        if not posts_file.exists():
            print(f"❌ No posts data found")
            return
        
        import pandas as pd
        df = pd.read_csv(posts_file)
        posts = df.to_dict('records')
        
        if args.sentiment:
            from analytics.sentiment import analyze_posts_sentiment
            analyzed, counts = analyze_posts_sentiment(posts)
            print(f"\n😀 Sentiment Analysis:")
            print(f"   Positive: {counts['positive']}")
            print(f"   Neutral:  {counts['neutral']}")
            print(f"   Negative: {counts['negative']}")
        
        if args.keywords:
            from analytics.sentiment import extract_keywords
            texts = [str(p.get('title', '') or '') + ' ' + str(p.get('selftext', '') or '') for p in posts]
            keywords = extract_keywords(texts, top_n=20)
            print(f"\n☁️ Top Keywords:")
            for word, count in keywords:
                print(f"   {word}: {count}")
        
        return
    
    # Schedule mode
    if args.schedule:
        if not args.every:
            print("❌ Please specify --every <minutes>")
            return
        
        from scheduler.cron import run_scheduled
        run_scheduled(args.schedule, args.every, args.mode, args.limit, args.user)
        return
    
    # Regular scraping mode
    if not args.target:
        parser.print_help()
        return
    
    if args.mode == "monitor":
        prefix = "u" if args.user else "r"
        dirs = setup_directories(args.target, prefix)
        load_history(dirs["posts"])
        print(f"🔄 Monitoring {prefix}/{args.target} every 5 mins...")
        while True:
            run_monitor(args.target, args.user)
            time.sleep(300)
    elif args.mode == "history":
        run_full_history(args.target, args.limit, args.user, 
                        download_media_flag=False, scrape_comments_flag=False,
                        dry_run=args.dry_run, use_plugins=args.plugins)
    else:
        run_full_history(args.target, args.limit, args.user,
                        download_media_flag=not args.no_media,
                        scrape_comments_flag=not args.no_comments,
                        dry_run=args.dry_run, use_plugins=args.plugins)

if __name__ == "__main__":
    main()