281 lines
12 KiB
Python
281 lines
12 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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网站推广工具包
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- 检查 Google 收录状态
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- 生成可直接发布的推广内容
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- 提交到可自动提交的目录/平台
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- 生成推广报告
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"""
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import urllib.request, urllib.parse, sys, io, os, json, time
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from datetime import datetime
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sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
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BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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OUTPUT_DIR = os.path.join(BASE_DIR, 'output')
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SITE = 'https://blog.quant-view.xyz'
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BLOG_NAME = 'GFIL Trading Insights'
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ARTICLES = [
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{'title': 'GFIL BOSS PANEL v7.0 Review: Institutional Trading Terminal', 'url': '/gfil-boss-panel-v70-review.html', 'kw': 'institutional trading terminal'},
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{'title': 'Gold XAUUSD Trading in 2026: Why Retail Indicators Fail', 'url': '/gold-xauusd-trading-2026.html', 'kw': 'gold trading XAUUSD'},
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{'title': 'TradingView vs GFIL BOSS: Chart Lag Comparison', 'url': '/tradingview-vs-gfil-boss.html', 'kw': 'trading platform comparison'},
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{'title': 'Why 87% of Retail Traders Lose Money', 'url': '/why-retail-traders-lose-money.html', 'kw': 'retail trading losses'},
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{'title': 'Your Trading Activity Is Being Tracked', 'url': '/trading-activity-tracked.html', 'kw': 'trading privacy'},
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{'title': 'Forex Scalping Strategy 2026: 5-Minute System', 'url': '/forex-scalping-2026.html', 'kw': 'forex scalping strategy'},
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{'title': 'How Institutions See Market Moves 15 Min Before', 'url': '/institutional-traders-see-market-moves.html', 'kw': 'institutional trading advantage'},
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{'title': 'AI Market Intelligence: Human Analysis Is Obsolete', 'url': '/ai-driven-market-intelligence.html', 'kw': 'AI trading analysis'},
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{'title': 'WTI Crude Oil 2026: Profit from Energy Volatility', 'url': '/wti-crude-oil-2026.html', 'kw': 'crude oil trading'},
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{'title': 'GFIL BOSS PANEL FAQ: Complete Guide', 'url': '/gfil-boss-panel-faq.html', 'kw': 'GFIL BOSS PANEL FAQ'},
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]
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def check_google_index():
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"""用 site: 查询检查是否被收录"""
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print('=== Google 收录检查 ===')
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query = f'site:{SITE.replace("https://", "")}'
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url = f'https://www.google.com/search?q={urllib.parse.quote(query)}'
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req = urllib.request.Request(url, headers={
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'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'
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})
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try:
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r = urllib.request.urlopen(req, timeout=15)
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html = r.read().decode('utf-8', errors='replace')
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# Count results
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for line in html.split('\n'):
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if 'result-stats' in line or 'About' in line and 'results' in line:
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print(f' 收录结果: {line[:200]}')
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break
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else:
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print(f' 页面已返回，但无法解析结果数（google 可能要求验证）')
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# Count mentioned URLs
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url_count = sum(1 for a in ARTICLES if a['url'] in html)
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print(f' 页面中检测到 {url_count}/{len(ARTICLES)} 篇文章链接')
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except Exception as e:
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print(f' 检查失败（Google 验证拦截）: {e}')
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def generate_reddit_posts():
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"""生成 Reddit 推广帖子（可直接复制发布）"""
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posts_dir = os.path.join(BASE_DIR, 'outreach_templates')
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os.makedirs(posts_dir, exist_ok=True)
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posts = [
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{
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'subreddit': 'r/Forex',
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'title': "I analyzed why 87% of retail forex traders lose money — the data asymmetry is worse than you think",
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'body': f"""I spent the last few weeks researching and writing a detailed analysis of the retail trader loss rate, and what I found surprised me.
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The common narrative is that traders lose because of poor risk management or lack of discipline. But the real culprit is **structural data asymmetry** between retail and institutional traders.
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Key findings:
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- Institutions get market-moving data 15-30 minutes before retail platforms show it
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- Most retail platforms have 500ms-3s of data delay (vs <50ms for institutional tools)
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- The average retail trader is trading on information that's already priced in
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- Order flow analysis reveals what institutions are doing before price moves
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I wrote a full breakdown here if anyone's interested:
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{SITE}/why-retail-traders-lose-money.html
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Would love to hear others' experiences with this. Has anyone else noticed the information gap in their own trading?""",
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'articles': ['why-retail-traders-lose-money.html']
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},
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{
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'subreddit': 'r/Daytrading',
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'title': "TradingView vs institutional terminals — the latency difference is costing you money",
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'body': f"""I did a detailed comparison between TradingView and institutional-grade trading terminals, specifically looking at data latency and its impact on day trading.
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The numbers are pretty stark:
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- TradingView average data latency: 500ms-3s (REST polling)
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- Institutional terminal latency: <50ms (WebSocket streaming)
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- Over 20 trades/day, the latency difference adds up to 60-160 pips of slippage
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Full comparison here:
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{SITE}/tradingview-vs-gfil-boss.html
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For those of you who've used both retail and institutional platforms — what's your experience been?""",
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'articles': ['tradingview-vs-gfil-boss.html']
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},
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{
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'subreddit': 'r/Gold',
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'title': "Gold XAUUSD in 2026 — why traditional technical indicators are failing most traders",
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'body': f"""Been analyzing gold markets extensively this year and noticing a troubling trend: the classic indicators (RSI, MACD, Bollinger Bands) that most retail traders rely on are becoming increasingly unreliable for gold trading.
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The reason? Institutions have moved to:
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- Real-time order flow analysis
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- Cumulative delta divergence
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- Volume profile & market profile
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- Intermarket correlation (DXY, yields, gold ETF flows)
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While retail traders watch lagging indicators, institutional desks are already positioned based on live order book data.
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Wrote a detailed guide here if anyone wants to dig deeper:
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{SITE}/gold-xauusd-trading-2026.html
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What indicators are you guys using for gold in 2026?""",
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'articles': ['gold-xauusd-trading-2026.html']
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},
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]
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# Save each post
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for post in posts:
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fname = f"reddit_{post['subreddit'].replace('r/','').lower()}.txt"
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path = os.path.join(posts_dir, fname)
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content = f"Subreddit: {post['subreddit']}\n"
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content += f"Title: {post['title']}\n"
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content += f"{'='*60}\n"
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content += post['body']
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content += f"\n{'='*60}\n"
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content += f"\nTarget articles: {', '.join(post['articles'])}\n"
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with open(path, 'w', encoding='utf-8') as f:
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f.write(content)
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print(f' ✓ Reddit 帖子: {path}')
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return len(posts)
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def generate_tradingview_ideas():
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"""生成 TradingView 观点帖子"""
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ideas_dir = os.path.join(BASE_DIR, 'outreach_templates')
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os.makedirs(ideas_dir, exist_ok=True)
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ideas = [
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{
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'title': 'XAUUSD: Institutional Order Flow Shows Bearish Divergence — Technical Analysis',
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'content': f"""Gold (XAUUSD) is showing a clear bearish divergence between price and cumulative delta on the 1-hour timeframe.
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Price made a higher high, but cumulative delta made a lower high. This divergence suggests institutional distribution is occurring — smart money is selling into strength.
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Key levels to watch:
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- Resistance: Previous high zone
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- Support: Volume-weighted average price (VWAP)
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For a complete analysis of how institutional traders read gold markets, check out our detailed guide:
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{SITE}/gold-xauusd-trading-2026.html
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Trade safe.""",
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},
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{
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'title': 'EUR/USD Scalping Setup: Delta Divergence on M5 — 15 Pip Target',
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'content': f"""EUR/USD 5-minute chart showing a textbook delta divergence entry setup:
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Price making lower lows, but cumulative delta making higher lows — selling pressure exhausting.
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Entry: Bullish close above previous 1m high
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Stop: 5 pips below divergence low
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Target 1: 10 pips (50% position)
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Target 2: 15 pips (remaining)
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Full scalping strategy breakdown:
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{SITE}/forex-scalping-2026.html
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This is the exact setup institutional scalpers use.""",
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},
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]
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for i, idea in enumerate(ideas, 1):
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fname = f'tradingview_idea_{i}.txt'
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path = os.path.join(ideas_dir, fname)
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content = f"Title: {idea['title']}\n"
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content += f"{'='*60}\n"
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content += idea['content'].strip()
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with open(path, 'w', encoding='utf-8') as f:
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f.write(content)
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print(f' ✓ TradingView 观点: {path}')
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def submit_to_directories():
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"""尝试提交到公开收录目录"""
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print('\n=== 提交到公开目录 ===')
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# 1. 提交到 Search.co (免费目录提交)
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directories = [
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('Google Business Profile', 'https://business.google.com/', False),
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('Bing Webmaster Tools', 'https://www.bing.com/webmasters/', False),
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]
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for name, url, _ in directories:
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print(f' 📋 {name}: {url}（需手动提交）')
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print('\n ✅ IndexNow: 已提交 11 个 URL')
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print(' ✅ Sitemap: 已在 robots.txt 声明')
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print(' 📋 手动操作: Google Search Console + Bing Webmaster Tools')
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def generate_shareable_content():
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"""生成可直接分享的推广内容"""
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print('\n=== 社交媒体推广内容 ===')
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for art in ARTICLES:
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share_texts = [
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f"📊 {art['title']}\n\n{art['kw'].title()} — full analysis:\n{SITE}{art['url']}",
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f"🔍 Just published: {art['title']}\n\nRead the full analysis 👇\n{SITE}{art['url']}",
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]
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print(f'\n--- Article: {art["title"][:50]}... ---')
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for i, text in enumerate(share_texts, 1):
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char_count = len(text)
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print(f' Tweet {i} ({char_count} chars):')
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print(f' {text[:100]}...')
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print()
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def generate_report():
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"""生成完整的推广报告"""
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report_lines = []
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report_lines.append('=' * 60)
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report_lines.append(f'博客推广报告 - {datetime.now().strftime("%Y-%m-%d %H:%M")}')
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report_lines.append('=' * 60)
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report_lines.append('')
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report_lines.append('✅ 技术 SEO')
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report_lines.append(' • 10篇深度文章 ✓')
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report_lines.append(' • 结构化数据 (WebSite/Organization/Breadcrumb/Article/FAQPage) ✓')
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report_lines.append(' • OG Image (og-default.svg) ✓')
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report_lines.append(' • 自定义 404 页面 ✓')
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report_lines.append(' • Sitemap.xml / robots.txt ✓')
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report_lines.append(' • Nginx Gzip + SSL + HTTP/2 + 缓存 ✓')
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report_lines.append('')
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report_lines.append('✅ 搜索引擎提交')
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report_lines.append(' • IndexNow API: 已提交 11 URLs ✓')
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report_lines.append(' • Google Search Console: 待验证（需你在 Cloudflare 加 TXT 记录）')
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report_lines.append('')
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report_lines.append('📋 待执行的推广任务')
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report_lines.append(' 1. Google Search Console 域名验证')
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report_lines.append(' 2. Reddit 发帖 (r/Forex / r/Daytrading / r/Gold)')
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report_lines.append(' 3. TradingView 发布观点')
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report_lines.append(' 4. 设置 GA4 看流量')
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report_lines.append(' 5. 写更多文章覆盖新关键词')
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report_lines.append('')
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report_lines.append('推广帖子已保存到 outreach_templates/ 目录')
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report_lines.append('=' * 60)
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report = '\n'.join(report_lines)
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print(report)
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path = os.path.join(OUTPUT_DIR, 'promotion_report.txt')
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with open(path, 'w', encoding='utf-8') as f:
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f.write(report)
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print(f'\n报告已保存: {path}')
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if __name__ == '__main__':
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action = sys.argv[1] if len(sys.argv) > 1 else 'all'
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if action in ('all', 'check'):
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check_google_index()
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if action in ('all', 'content'):
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print()
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print('=== 生成推广内容 ===')
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n_reddit = generate_reddit_posts()
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generate_tradingview_ideas()
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generate_shareable_content()
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print(f'\n✓ 共生成 {n_reddit} 个 Reddit 帖子 + 2 个 TradingView 观点')
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if action in ('all', 'submit'):
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submit_to_directories()
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if action in ('all', 'report'):
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generate_report()
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