335 lines
11 KiB
Python
335 lines
11 KiB
Python
"""
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山寨币舆情监控模块 v1.1
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数据源：CoinGecko Trending API + Google News RSS (均免费)
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用途：检测山寨币的消息面热度+具体新闻内容，与PA技术面共振加权
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"""
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import os
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import sys
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import json
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import time
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import requests
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import xml.etree.ElementTree as ET
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from datetime import datetime, timedelta
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from collections import defaultdict
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from pathlib import Path
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from app.db.schema import get_conn
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sys.path.insert(0, os.path.dirname(__file__))
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COINGECKO_TRENDING_URL = "https://api.coingecko.com/api/v3/search/trending"
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GOOGLE_NEWS_RSS = "https://news.google.com/rss/search?q={query}&hl=en-US&gl=US&ceid=US:en"
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def _get_conn():
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return get_conn()
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def fetch_trending_coins():
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"""获取 CoinGecko Trending 榜单, 含价格+涨跌幅"""
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try:
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r = requests.get(COINGECKO_TRENDING_URL, timeout=15)
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if r.status_code != 200:
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return []
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data = r.json()
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coins = []
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for idx, c in enumerate(data.get("coins", [])):
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item = c.get("item", {})
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symbol = (item.get("symbol", "") or "").upper()
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price_data = item.get("data", {}) or {}
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price_usd = price_data.get("price", 0) or 0
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change_pct_dict = price_data.get("price_change_percentage_24h", {}) or {}
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change_usd = change_pct_dict.get("usd", 0) or 0
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coins.append({
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"symbol": symbol,
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"name": item.get("name", ""),
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"coingecko_id": item.get("id", ""),
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"trend_rank": idx + 1,
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"trend_score": item.get("score", 0),
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"market_cap_rank": item.get("market_cap_rank", 0) or 0,
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"price_usd": round(float(price_usd), 6),
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"change_24h_pct": round(float(change_usd), 2),
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"thumb": item.get("thumb", ""),
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})
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return coins
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except Exception as e:
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print(f"[sentiment] fetch_trending error: {e}")
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return []
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def fetch_news_for_coin(symbol, max_results=3):
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"""
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从 Google News RSS 抓取币种相关新闻标题
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返回: list of {title, source, published}
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"""
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try:
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query = f"{symbol}+crypto+coin"
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url = GOOGLE_NEWS_RSS.format(query=query)
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r = requests.get(url, timeout=10, headers={"User-Agent": "Mozilla/5.0"})
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if r.status_code != 200:
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return []
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root = ET.fromstring(r.text)
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items = root.findall(".//item")
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news = []
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for item in items[:max_results]:
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title_el = item.find("title")
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source_el = item.find("source")
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pubdate_el = item.find("pubDate")
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title = title_el.text if title_el is not None else ""
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source = source_el.text if source_el is not None else ""
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published = pubdate_el.text if pubdate_el is not None else ""
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# 清理标题: 去掉末尾的 " - SourceName"
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if " - " in title:
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parts = title.rsplit(" - ", 1)
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if len(parts) == 2 and len(parts[1]) < 30:
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title = parts[0]
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news.append({
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"title": title[:200],
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"source": source,
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"published": published,
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})
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return news
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except Exception as e:
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print(f"[sentiment] fetch_news error for {symbol}: {e}")
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return []
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def get_sentiment_scores(symbols=None, max_bonus=2):
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"""获取指定币种的舆情评分"""
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trending = fetch_trending_coins()
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if not trending:
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return {}
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trending_map = {}
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for t in trending:
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if t["symbol"]:
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trending_map[t["symbol"]] = t
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previous_trending = _get_previous_trending()
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prev_symbols = {r["symbol"] for r in previous_trending}
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scores = {}
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for t in trending:
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sym = t["symbol"]
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full_symbol = f"{sym}/USDT"
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if symbols and full_symbol not in symbols:
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continue
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bonus = 0.0
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details = []
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if t["trend_rank"] <= 5:
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bonus += 2.0
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details.append(f"Trending Top5(#{t['trend_rank']})")
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elif t["trend_rank"] <= 10:
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bonus += 1.0
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details.append(f"Trending Top10(#{t['trend_rank']})")
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elif t["trend_rank"] <= 15:
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bonus += 0.5
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details.append(f"Trending(#{t['trend_rank']})")
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if sym not in prev_symbols:
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bonus += 1.0
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details.append("new_entry")
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consecutive_hours = _get_consecutive_trending_hours(sym)
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if consecutive_hours > 6:
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decay = max(0.3, 1.0 - (consecutive_hours - 6) * 0.1)
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bonus *= decay
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bonus = min(bonus, max_bonus)
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bonus = round(bonus, 1)
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if bonus > 0:
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scores[full_symbol] = {
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"trending": True,
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"trend_rank": t["trend_rank"],
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"bonus": bonus,
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"details": ", ".join(details),
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"market_cap_rank": t["market_cap_rank"],
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"name": t["name"],
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"price_usd": t.get("price_usd", 0),
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"change_24h_pct": t.get("change_24h_pct", 0),
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"coingecko_id": t.get("coingecko_id", ""),
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}
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return scores
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def get_sentiment_alert(holdings=None):
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"""检测舆情异动"""
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trending = fetch_trending_coins()
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if not trending:
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return []
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previous_trending = _get_previous_trending()
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prev_symbols = {r["symbol"] for r in previous_trending}
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alerts = []
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holdings_set = set(holdings) if holdings else set()
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for t in trending[:10]:
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sym = t["symbol"]
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full_symbol = f"{sym}/USDT"
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if full_symbol in holdings_set and t["trend_rank"] <= 3:
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alerts.append({
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"type": "holding_trending",
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"symbol": full_symbol,
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"name": t["name"],
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"trend_rank": t["trend_rank"],
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"alert": f"持仓币 {sym} 进入 CoinGecko Trending Top{t['trend_rank']}",
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})
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elif sym not in prev_symbols and t["trend_rank"] <= 10:
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alerts.append({
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"type": "new_trending",
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"symbol": full_symbol,
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"name": t["name"],
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"trend_rank": t["trend_rank"],
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"alert": f"{sym}({t['name']}) 新进 Trending #{t['trend_rank']}",
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})
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return alerts
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def collect_and_store():
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"""采集舆情数据+新闻，写入DB"""
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trending = fetch_trending_coins()
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if not trending:
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return {"status": "error", "message": "Failed to fetch trending"}
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conn = _get_conn()
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now = datetime.now().isoformat()
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# 获取活跃持仓币种，用于新闻优先级
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active_recs = conn.execute(
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"SELECT DISTINCT symbol FROM recommendation WHERE status='active'"
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).fetchall()
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active_bases = {r["symbol"].split("/")[0].upper() for r in active_recs}
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stored = 0
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for i, t in enumerate(trending):
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# 只对 Top10 + 持仓重叠的币拉新闻 (控制请求量)
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should_fetch_news = (t["trend_rank"] <= 10 or t["symbol"] in active_bases)
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news = []
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if should_fetch_news:
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news = fetch_news_for_coin(t["symbol"], max_results=3)
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if i < 9: # 控制频率，每个请求间隔0.5秒
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time.sleep(0.5)
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try:
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conn.execute("""
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INSERT INTO sentiment_events
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(symbol, name, source, event_type, trend_rank, trend_score,
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market_cap_rank, extra_json, detected_at)
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VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
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""", (
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t["symbol"], t["name"], "coingecko", "trending",
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t["trend_rank"], t["trend_score"], t["market_cap_rank"],
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json.dumps({
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"price_usd": t.get("price_usd", 0),
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"change_24h_pct": t.get("change_24h_pct", 0),
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"thumb": t.get("thumb", ""),
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"news": news,
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}),
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now,
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))
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stored += 1
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except Exception as e:
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print(f"[sentiment] DB insert error for {t['symbol']}: {e}")
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conn.commit()
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conn.close()
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print(f"[sentiment] Stored {stored} trending coins at {now}")
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return {"status": "ok", "stored": stored, "time": now}
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def _get_previous_trending():
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"""获取上一次采集的 trending 记录"""
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try:
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conn = _get_conn()
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row = conn.execute(
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"SELECT MAX(detected_at) FROM sentiment_events WHERE source='coingecko'"
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).fetchone()
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if not row or not row[0]:
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conn.close()
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return []
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latest_time = row[0]
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rows = conn.execute(
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"SELECT symbol, trend_rank FROM sentiment_events WHERE detected_at = %s",
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(latest_time,)
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).fetchall()
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conn.close()
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return [{"symbol": r["symbol"], "trend_rank": r["trend_rank"]} for r in rows]
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except Exception:
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return []
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def _get_consecutive_trending_hours(symbol):
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"""计算连续在榜小时数"""
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try:
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conn = _get_conn()
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rows = conn.execute("""
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SELECT detected_at FROM sentiment_events
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WHERE symbol = %s AND source = 'coingecko'
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ORDER BY detected_at DESC LIMIT 20
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""", (symbol,)).fetchall()
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conn.close()
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if not rows:
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return 0
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consecutive = 1
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max_gap = 3600
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prev = datetime.fromisoformat(rows[0]["detected_at"])
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for r in rows[1:]:
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curr = datetime.fromisoformat(r["detected_at"])
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if (prev - curr).total_seconds() <= max_gap:
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consecutive += 1
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prev = curr
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else:
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break
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return consecutive * 0.5
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except Exception:
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return 0
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def get_active_holdings():
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"""获取当前活跃推荐币种"""
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try:
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conn = _get_conn()
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rows = conn.execute(
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"SELECT DISTINCT symbol FROM recommendation WHERE status='active'"
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).fetchall()
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conn.close()
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return [r["symbol"] for r in rows]
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except Exception:
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return []
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def main():
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import argparse
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parser = argparse.ArgumentParser(description="山寨币舆情监控")
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parser.add_argument("--collect", action="store_true", help="采集并存储")
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parser.add_argument("--check", action="store_true", help="检测异动")
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parser.add_argument("--scores", action="store_true", help="输出评分")
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args = parser.parse_args()
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if args.collect:
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result = collect_and_store()
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print(json.dumps(result, ensure_ascii=False))
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elif args.scores:
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scores = get_sentiment_scores()
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print(json.dumps(scores, ensure_ascii=False, indent=2))
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else:
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holdings = get_active_holdings()
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alerts = get_sentiment_alert(holdings=holdings)
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if args.check:
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print(json.dumps(alerts, ensure_ascii=False, indent=2))
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else:
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scores = get_sentiment_scores()
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output = {
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"alerts": alerts,
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"sentiment_scores": scores,
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"holdings_count": len(holdings),
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"check_time": datetime.now().isoformat(),
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}
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print(json.dumps(output, ensure_ascii=False, indent=2))
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if __name__ == "__main__":
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main()
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