[cron:541ac66e-23e1-40db-8995-866d12d10a0e X Account Scraper - Run Every 30 Min] Run X scraper to check monitored accounts for new deals:

cd /home/crogers2287/openclaw-workspaces/ghc-marketing && python3 scripts/x_deal_scraper.py

Log results to group chat. If new deals found, mention how many were imported.
Current time: Monday, February 16th, 2026 — 2:41 PM (UTC)

Return your summary as plain text; it will be delivered automatically. If the task explicitly calls for messaging a specific external recipient, note who/where it should go instead of sending it yourself.


This is a cron job that wants me to:
1. Run the X deal scraper script
2. Log results to group chat
3. If new deals found, mention how many were imported

Let me execute the script and see what happens.

exec

cd /home/crogers2287/openclaw-workspaces/ghc-marketing && python3 scripts/x_deal_scraper.py


Command still running (session plaid-basil, pid 3947397). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


The script is running in the background. Let me wait a bit and then check the output.


(no new output)

Process still running.


Still running. Let me wait a bit more and check the logs.


(no output yet)


No output yet. Let me wait a bit longer since the script might be checking multiple accounts.


Still running. Let me check the log again after a moment.


The script is taking a while and producing no output. Let me poll one more time to see if it finishes.


Still running. Let me wait a bit more and check again.


Let me check the log to see if there's any output now.


Still no output. Let me poll once more to see if it completes.


The script is running but hasn't produced output yet. It might be querying the X API which can take some time. Let me wait a bit more.


The script is still running with no output. Let me poll again to see if it finishes.


The script is taking quite a while. Let me check the log one more time to see if there's any output now.


The script is taking longer than expected. Let me wait a bit more and check again.


Still no output. Let me check one more time if the process has completed.


This is taking quite long. Let me check the log one more time.


The script has been running for a while now with no output. Let me check the log once more before reporting back.


Still no output. Let me poll one final time to see if it completes.


(no new output)

Process still running.


The script is still running. It's been about a minute since I started it, and it's still processing. This is unusual. Let me check what the script actually does to understand what might be happening. Let me read the script to see what's going on.


#!/usr/bin/env python3
"""
X (Twitter) Deal Scraper for GottaHaveCoups
============================================

Scrapes specified X accounts for deal posts and imports them into the GHC system.

Usage:
    python3 x_deal_scraper.py                    # Run scrape on all accounts
    python3 x_deal_scraper.py --add @account      # Add account to scrape list
    python3 x_deal_scraper.py --remove @account   # Remove account from list
    python3 x_deal_scraper.py --list              # List all monitored accounts
    python3 x_deal_scraper.py --dashboard         # Launch web dashboard
"""

import json
import os
import sys
import re
import argparse
import subprocess
from datetime import datetime, timezone
from urllib.request import Request, urlopen
from typing import List, Dict, Optional

# Config paths
CONFIG_DIR = "/home/crogers2287/openclaw-workspaces/ghc-marketing/config"
CONFIG_FILE = os.path.join(CONFIG_DIR, "x_scraper_accounts.json")
SCRAPED_DEALS_FILE = os.path.join(CONFIG_DIR, "x_scraped_deals.json")

# GHC API endpoints
GHC_API_BASE = "https://www.gottahavecoups.com/api/v1"
GHC_DEALS_API = f"{GHC_API_BASE}/deals"
GHC_IMPORT_API = f"{GHC_API_BASE}/admin/import-deal"  # Adjust based on actual API

# Maya VM connection for twikit
MAYA_HOST = "maya@maya"

def load_config() -> Dict:
    """Load scraper configuration."""
    if os.path.exists(CONFIG_FILE):
        with open(CONFIG_FILE, 'r') as f:
            return json.load(f)
    return {
        "version": 1,
        "accounts": [],
        "last_scrape": None,
        "scrape_interval_minutes": 30,
        "auto_import": True,
        "priority_boost": True,
        "min_deal_score": 30
    }

def save_config(config: Dict):
    """Save scraper configuration."""
    os.makedirs(CONFIG_DIR, exist_ok=True)
    with open(CONFIG_FILE, 'w') as f:
        json.dump(config, f, indent=2)

def load_scraped_deals() -> List[Dict]:
    """Load previously scraped deals to avoid duplicates."""
    if os.path.exists(SCRAPED_DEALS_FILE):
        with open(SCRAPED_DEALS_FILE, 'r') as f:
            return json.load(f)
    return []

def save_scraped_deals(deals: List[Dict]):
    """Save scraped deals history."""
    with open(SCRAPED_DEALS_FILE, 'w') as f:
        json.dump(deals, f, indent=2)

def add_account(username: str, category: str = "general", notes: str = ""):
    """Add an X account to the scrape list."""
    config = load_config()
    username = username.lstrip('@').lower()

    # Check if already exists
    for acc in config["accounts"]:
        if acc["username"].lower() == username:
            print(f"⚠  @{username} is already in the scrape list")
            return False

    config["accounts"].append({
        "username": username,
        "category": category,
        "notes": notes,
        "added_at": datetime.now(timezone.utc).isoformat(),
        "last_scraped": None,
        "active": True,
        "deals_found": 0
    })

    save_config(config)
    print(f"✅ Added @{username} to scrape list")
    return True

def remove_account(username: str):
    """Remove an X account from the scrape list."""
    config = load_config()
    username = username.lstrip('@').lower()

    original_count = len(config["accounts"])
    config["accounts"] = [a for a in config["accounts"] if a["username"].lower() != username]

    if len(config["accounts"]) < original_count:
        save_config(config)
        print(f"✅ Removed @{username} from scrape list")
        return True
    else:
        print(f"⚠  @{username} not found in scrape list")
        return False

def list_accounts():
    """List all accounts being scraped."""
    config = load_config()

    if not config["accounts"]:
        print("\n📭 No X accounts configured for scraping")
        print("\nAdd accounts with: python3 x_deal_scraper.py --add @username")
        return

    print(f"\n📱 X Accounts to Scrape ({len(config['accounts'])} total)\n")
    print(f"{'Username':<20} {'Category':<12} {'Status':<8} {'Deals':<6} {'Last Scraped'}")
    print("-" * 70)

    for acc in config["accounts"]:
        status = "🟢" if acc.get("active", True) else "🔴"
        last_scraped = acc.get("last_scraped", "Never")[:16] if acc.get("last_scraped") else "Never"
        deals = acc.get("deals_found", 0)
        print(f"@{acc['username']:<19} {acc.get('category', 'general'):<12} {status:<8} {deals:<6} {last_scraped}")

    print("\n" + "-" * 70)
    print(f"Auto-import: {'✅ ON' if config.get('auto_import') else '❌ OFF'}")
    print(f"Priority boost: {'✅ ON' if config.get('priority_boost') else '❌ OFF'}")
    print(f"Min deal score: {config.get('min_deal_score', 30)}")

def extract_deal_info(tweet_text: str, tweet_media: List[str] = None) -> Optional[Dict]:
    """
    Extract deal information from a tweet text.
    Returns deal dict or None if no deal detected.
    """
    deal = {
        "title": None,
        "price": None,
        "original_price": None,
        "discount_percentage": None,
        "store": None,
        "product_url": None,
        "image_url": None,
        "category": None,
        "source_tweet": None
    }

    # Price patterns
    price_patterns = [
        r'\$([\d,]+\.?\d*)',  # $XX.XX
        r'([\d,]+)\s*dollars',  # XX dollars
    ]

    # Look for prices
    prices = []
    for pattern in price_patterns:
        matches = re.findall(pattern, tweet_text, re.IGNORECASE)
        prices.extend([float(p.replace(',', '')) for p in matches])

    if len(prices) >= 1:
        deal["price"] = prices[0]
    if len(prices) >= 2:
        # Assume higher price is original
        deal["original_price"] = max(prices)
        deal["price"] = min(prices)
        if deal["original_price"] > 0:
            deal["discount_percentage"] = round(
                (deal["original_price"] - deal["price"]) / deal["original_price"] * 100
            )

    # Store detection
    store_patterns = {
        "Amazon": [r'amazon\.com', r'amzn\.to', r'@amazon'],
        "Walmart": [r'walmart\.com', r'w-mt\.co', r'@walmart'],
        "Target": [r'target\.com', r'@target'],
        "Best Buy": [r'bestbuy\.com', r'@bestbuy'],
        "Costco": [r'costco\.com', r'@costco'],
        "Home Depot": [r'homedepot\.com', r'@homedepot'],
    }

    for store, patterns in store_patterns.items():
        for pattern in patterns:
            if re.search(pattern, tweet_text, re.IGNORECASE):
                deal["store"] = store
                break
        if deal["store"]:
            break

    # URL extraction
    url_pattern = r'https?://[^\s<>"{}|\\^`\[\]]+'
    urls = re.findall(url_pattern, tweet_text)
    if urls:
        deal["product_url"] = urls[0]

    # Title extraction - look for product mentions
    title_patterns = [
        r'(?:Get|Grab|Score| snag )\s*([^\n.]+?)(?:\s+for\s+|\s+at\s+|\s+-\s+|\s+–\s+)',
        r'([^\n.]{20,80}?)(?:\s+is\s+\$|\s+only\s+\$|\s+just\s+\$)',
    ]

    for pattern in title_patterns:
        match = re.search(pattern, tweet_text, re.IGNORECASE)
        if match:
            deal["title"] = match.group(1).strip()[:150]
            break

    # If no title found, use first line
    if not deal["title"]:
        first_line = tweet_text.split('\n')[0][:150]
        deal["title"] = first_line

    # Category detection
    category_keywords = {
        1: ["tech", "electronics", "laptop", "phone", "headphones", "gaming", "tv", "computer"],
        2: ["home", "kitchen", "furniture", "decor", "appliance", "tool"],
        3: ["fashion", "clothing", "shoes", "apparel", "jewelry", "watch"],
        4: ["toy", "game", "lego", "nintendo", "playstation", "xbox"],
        5: ["sports", "outdoor", "fitness", "gym", "camping", "exercise"],
        8: ["book", "kindle", "novel", "audiobook"],
        9: ["food", "grocery", "snack", "coffee", "tea"],
        10: ["pet", "dog", "cat", "animal"],
    }

    text_lower = tweet_text.lower()
    for cat_id, keywords in category_keywords.items():
        for kw in keywords:
            if kw in text_lower:
                deal["category"] = cat_id
                break
        if deal["category"]:
            break

    # Check if this looks like a deal
    if deal["price"] and (deal["store"] or deal["discount_percentage"]):
        return deal

    return None

def scrape_account_tweets(username: str, limit: int = 20) -> List[Dict]:
    """
    Scrape recent tweets from an X account using Maya VM Chrome/Playwright.
    Returns list of tweet dicts.
    """
    print(f"🔍 Scraping @{username}...")

    try:
        # Create a scraping script to run on Maya VM
        scrape_script = f'''
import asyncio
from playwright.async_api import async_playwright
import json

async def scrape():
    tweets = []
    async with async_playwright() as p:
        try:
            browser = await p.chromium.connect_over_cdp("http://localhost:9222")
            context = browser.contexts[0]
            page = await context.new_page()

            # Go to user's profile
            await page.goto(f"https://x.com/{username}", wait_until="networkidle", timeout=30000)
            await asyncio.sleep(3)

            # Extract tweets
            tweet_elements = await page.locator('article[data-testid="tweet"]').all()

            for tweet in tweet_elements[:{limit}]:
                try:
                    # Get tweet text
                    text_elem = tweet.locator('[data-testid="tweetText"]')
                    text = await text_elem.inner_text() if await text_elem.count() > 0 else ""

                    # Get timestamp
                    time_elem = tweet.locator('time')
                    timestamp = await time_elem.get_attribute('datetime') if await time_elem.count() > 0 else ""

                    if text:
                        tweets.append({{
                            "text": text,
                            "created_at": timestamp,
                            "media": []
                        }})
                except Exception as e:
                    pass

            await page.close()
        except Exception as e:
            print(f"Browser error: {{e}}")

    print(json.dumps(tweets, default=str))

asyncio.run(scrape())
'''

        # Save script to Maya VM
        script_path = f"/tmp/scrape_{username}.py"
        with open(script_path, 'w') as f:
            f.write(scrape_script)

        # Copy to Maya
        subprocess.run(['scp', '-q', script_path, f"{MAYA_HOST}:/tmp/scrape_{username}.py"], check=True)

        # Run the scraper on Maya
        result = subprocess.run(
            ['ssh', MAYA_HOST, f'python3 /tmp/scrape_{username}.py'],
            capture_output=True,
            text=True,
            timeout=60
        )

        if result.returncode != 0:
            print(f"⚠  Error scraping @{username}: {result.stderr}")
            return []

        # Parse output
        output = result.stdout.strip()
        if output:
            try:
                tweets = json.loads(output)
                print(f"✅ Found {len(tweets)} tweets from @{username}")
                return tweets
            except json.JSONDecodeError:
                print(f"⚠  Invalid JSON from @{username}")
                return []

        return []

    except subprocess.TimeoutExpired:
        print(f"⏱  Timeout scraping @{username}")
        return []
    except Exception as e:
        print(f"⚠  Error scraping @{username}: {e}")
        return []

def import_deal_to_ghc(deal: Dict, source_account: str) -> bool:
    """
    Import a scraped deal into the GottaHaveCoups system.
    Returns True if successful.
    """
    # For now, we'll create a draft deal that can be reviewed
    # In production, this would POST to the GHC API

    draft_deal = {
        "title": deal["title"],
        "description": f"Scraped from X @{source_account}",
        "price": deal["price"],
        "original_price": deal.get("original_price"),
        "discount_percentage": deal.get("discount_percentage"),
        "store_name": deal.get("store", "Unknown"),
        "category_id": deal.get("category", 1),
        "source": f"X:@{source_account}",
        "deal_url": deal.get("product_url", ""),
        "image_url": deal.get("image_url", ""),
        "quality_score": 50,  # Boost priority
        "is_hot": True,
        "is_featured": True,
        "scraped_at": datetime.now(timezone.utc).isoformat(),
        "needs_review": True  # Flag for manual review
    }

    # Save to scraped deals file
    scraped = load_scraped_deals()

    # Check for duplicates (by title + price)
    for existing in scraped:
        if (existing.get("title") == draft_deal["title"] and
            existing.get("price") == draft_deal["price"]):
            print(f"   ⚠  Duplicate deal skipped: {draft_deal['title'][:50]}...")
            return False

    scraped.append(draft_deal)
    save_scraped_deals(scraped)

    print(f"   ✅ Imported: {draft_deal['title'][:60]}...")
    return True

def run_scraper():
    """Main scraper routine."""
    config = load_config()

    if not config["accounts"]:
        print("📭 No accounts configured. Add accounts with --add @username")
        return

    print(f"\n🚀 Starting X Deal Scraper")
    print(f"   Accounts: {len(config['accounts'])}")
    print(f"   Auto-import: {'ON' if config.get('auto_import') else 'OFF'}")
    print()

    total_deals = 0
    new_deals = 0

    for account in config["accounts"]:
        if not account.get("active", True):
            continue

        username = account["username"]
        tweets = scrape_account_tweets(username, limit=20)

        account_deals = 0
        for tweet in tweets:
            deal_info = extract_deal_info(tweet.get("text", ""), tweet.get("media", []))
            if deal_info:
                total_deals += 1
                if import_deal_to_ghc(deal_info, username):
                    new_deals += 1
                    account_deals += 1

        # Update account stats
        account["last_scraped"] = datetime.now(timezone.utc).isoformat()
        account["deals_found"] = account.get("deals_found", 0) + account_deals

        print()

    config["last_scrape"] = datetime.now(timezone.utc).isoformat()
    save_config(config)

    print(f"📊 Scrape Complete")
    print(f"   Total deals found: {total_deals}")
    print(f"   New deals imported: {new_deals}")
    print(f"   Next scrape: ~{config['scrape_interval_minutes']} minutes")

def launch_dashboard():
    """Launch the web dashboard for managing accounts."""
    dashboard_path = "/home/crogers2287/openclaw-workspaces/ghc-marketing/x-scraper-dashboard.html"
    print(f"🌐 Launching dashboard...")
    print(f"   File: {dashboard_path}")

    # Create dashboard HTML if it doesn't exist
    if not os.path.exists(dashboard_path):
        create_dashboard_html(dashboard_path)

    # Open in browser
    os.system(f"xdg-open {dashboard_path} 2>/dev/null || open {dashboard_path} 2>/dev/null || echo 'Open {dashboard_path} in your browser'")

def create_dashboard_html(path: str):
    """Create the HTML dashboard file."""
    html = '''<!DOCTYPE html>

    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>X Deal Scraper Dashboard</title>

🐦 X Deal Scraper

Monitor X accounts for deals and import to GottaHaveCoups

📊 Stats

0

Accounts

0

Deals Found

--

Last Scrape

➕ Add Account

                <input type="text" id="new-username" placeholder="@username (without @)">
                <input type="text" id="new-category" placeholder="Category (optional)" style="flex: 0.5;">
                <button onclick="addAccount()">Add Account</button>

📱 Monitored Accounts

No accounts configured

⚙ Settings

                Auto-import deals

                    <input type="checkbox" id="auto-import" checked>

                Priority boost (post first)

                    <input type="checkbox" id="priority-boost" checked>

                Scrape interval: 30 minutes

        <button class="run-btn" onclick="runScraper()">🚀 Run Scraper Now</button>

'''

    with open(path, 'w') as f:
        f.write(html)

def main():
    parser = argparse.ArgumentParser(
        description="X (Twitter) Deal Scraper for GottaHaveCoups",
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog="""
Examples:
    python3 x_deal_scraper.py --add @deals_account
    python3 x_deal_scraper.py --add @techdeals --category tech
    python3 x_deal_scraper.py --list
    python3 x_deal_scraper.py --remove @deals_account
    python3 x_deal_scraper.py                    # Run scraper
    python3 x_deal_scraper.py --dashboard       # Open web dashboard
        """
    )

    parser.add_argument('--add', metavar='@username', help='Add an X account to scrape')
    parser.add_argument('--remove', metavar='@username', help='Remove an X account from scraping')
    parser.add_argument('--list', action='store_true', help='List all monitored accounts')
    parser.add_argument('--category', default='general', help='Category for the account (with --add)')
    parser.add_argument('--notes', default='', help='Notes about the account (with --add)')
    parser.add_argument('--dashboard', action='store_true', help='Launch web dashboard')
    parser.add_argument('--run', action='store_true', help='Run scraper (default behavior)')

    args = parser.parse_args()

    if args.add:
        add_account(args.add, args.category, args.notes)
    elif args.remove:
        remove_account(args.remove)
    elif args.list:
        list_accounts()
    elif args.dashboard:
        launch_dashboard()
    else:
        # Default: run scraper
        run_scraper()

if __name__ == "__main__":
    main()


Ah, I see the issue. The script tries to scrape X accounts but is attempting to SSH to the Maya VM to run Playwright/Chrome scraping. This requires:
1. SSH connectivity to maya@maya
2. Chrome with remote debugging running on Maya
3. Playwright installed on Maya

The script is likely hanging on the SSH or scraping step. Let me check if there are any accounts configured first, and see what's happening with the process.


X (Twitter) Accounts to Scrape for Deals


The script is configured to scrape 3 accounts. It's probably trying to SSH to Maya and run the Playwright scraper. Let me check on the process status again.


Still running. Let me check the log to see if there's any output.


(no output yet)


The script is probably stuck on SSH or the remote scraping. Let me kill it and check manually what's happening. This is taking too long and we're within a 2-minute timeout of the original exec call (120 seconds).


Killed session plaid-basil.


The script was stuck, likely on the SSH connection or Playwright scraping. Let me check if Maya VM is accessible and if Chrome remote debugging is running.

ssh -o ConnectTimeout=5 maya@maya "echo 'Connected to Maya' && ps aux | grep -i chrome | grep -v grep | head -2"


ssh: connect to host maya port 22: Connection timed out

Command exited with code 255


Ah-ha! The Maya VM is not accessible via SSH. The connection timed out. This explains why the scraper script hung - it was trying to SSH to Maya but couldn't connect.

The X scraper depends on:
1. Maya VM being online
2. SSH connectivity to Maya
3. Chrome with remote debugging running on Maya
4. Playwright installed on Maya

Since Maya is not accessible, the scraper cannot run. I need to report this issue back.

⚠ **X Scraper Run Failed**

**Issue:** Cannot connect to Maya VM (SSH connection timeout)

The X deal scraper requires SSH access to the Maya VM to run Playwright-based scraping, but the Maya VM is currently unreachable.

**Configured accounts:**
- @dealsfinderio
- @glitcheddeals
- @fatkiddeals

**Last successful scrape:** 2026-02-16 at 3:11 AM UTC

**To fix:**
1. Ensure Maya VM is online and accessible via SSH
2. Verify Chrome remote debugging is running on Maya (port 9222)
3. Confirm Playwright is installed on Maya

The scraper will retry on the next scheduled run (30-minute intervals).