495 lines
18 KiB
Python
495 lines
18 KiB
Python
#!/usr/bin/env python3
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"""
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XTZH AI定价引擎服务
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NAC公链 - XTZH资产稳定币当日铸造价格计算
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基于NAC宪法权重模型：货币层40% + 黄金层10% + 商品层50%
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黄金信任锚覆盖率：125%
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"""
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import asyncio
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import json
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import logging
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import time
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import math
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from datetime import datetime, timezone
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from typing import Optional
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import urllib.request
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import urllib.error
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from http.server import HTTPServer, BaseHTTPRequestHandler
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import threading
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# ============================================================================
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# 日志配置
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# ============================================================================
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s [XTZH-AI] %(levelname)s %(message)s',
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handlers=[
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logging.FileHandler('/var/log/xtzh-pricing.log'),
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logging.StreamHandler()
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]
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)
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logger = logging.getLogger('xtzh-pricing')
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# ============================================================================
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# NAC宪法权重常量（来自constants.rs）
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# ============================================================================
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W_FX_BASE = 4000 # 货币层权重基准 40.00%
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W_AU_BASE = 1000 # 黄金层权重基准 10.00%
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W_COM_BASE = 5000 # 商品层权重基准 50.00%
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W_AU_MIN = 500 # 黄金层权重最小值 5.00%
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W_AU_MAX = 2000 # 黄金层权重最大值 20.00%
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WEIGHT_SUM = 10000 # 权重和 100.00%
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GOLD_TRUST_ANCHOR_COVERAGE = 12500 # 黄金信任锚覆盖率 125.00%
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# SDR货币篮子权重（IMF 2022-2026）
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SDR_BASKET = {
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'USD': 0.4332, # 43.32%
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'EUR': 0.2923, # 29.23%
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'CNY': 0.1059, # 10.59%
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'JPY': 0.0784, # 7.84%
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'GBP': 0.0802, # 8.02%
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# 其余0.1%忽略
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}
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# ============================================================================
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# 数据缓存
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# ============================================================================
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_cache = {
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'data': None,
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'timestamp': 0,
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'ttl': 300 # 5分钟缓存
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}
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# ============================================================================
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# 数据获取函数
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# ============================================================================
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def fetch_url(url, timeout=10):
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"""获取URL内容"""
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try:
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req = urllib.request.Request(url, headers={
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'User-Agent': 'Mozilla/5.0 (NAC-XTZH-Pricing/1.0)',
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'Accept': 'application/json'
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})
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with urllib.request.urlopen(req, timeout=timeout) as resp:
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return json.loads(resp.read().decode('utf-8'))
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except Exception as e:
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logger.warning(f"获取 {url} 失败: {e}")
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return None
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def fetch_yahoo_price(symbol):
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"""从Yahoo Finance获取价格"""
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import urllib.parse
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encoded = urllib.parse.quote(symbol)
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url = f"https://query1.finance.yahoo.com/v8/finance/chart/{encoded}?interval=1d&range=1d"
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data = fetch_url(url)
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if data and data.get('chart', {}).get('result'):
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return data['chart']['result'][0]['meta'].get('regularMarketPrice')
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return None
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def fetch_sdr_rates():
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"""获取SDR汇率（1 XDR = ? 各货币）"""
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data = fetch_url("https://open.er-api.com/v6/latest/XDR")
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if data and data.get('rates'):
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rates = data['rates']
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return {
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'USD': rates.get('USD', 1.374498),
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'EUR': rates.get('EUR', 1.166327),
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'GBP': rates.get('GBP', 1.017137),
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'JPY': rates.get('JPY', 215.268845),
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'CNY': rates.get('CNY', 9.444808),
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'updated': data.get('time_last_update_utc', '')
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}
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# 备用：使用最近已知值
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logger.warning("SDR汇率获取失败，使用备用数据")
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return {
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'USD': 1.374498, 'EUR': 1.166327, 'GBP': 1.017137,
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'JPY': 215.268845, 'CNY': 9.444808, 'updated': 'fallback'
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}
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def fetch_gold_price_usd():
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"""获取黄金价格（USD/盎司）"""
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# 主源：Yahoo Finance GC=F
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price = fetch_yahoo_price("GC=F")
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if price and price > 0:
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logger.info(f"黄金价格（Yahoo GC=F）: ${price}")
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return price, "Yahoo Finance GC=F"
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# 备源：Binance PAXG（黄金代币）
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data = fetch_url("https://api.binance.com/api/v3/ticker/price?symbol=PAXGUSDT")
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if data and data.get('price'):
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price = float(data['price'])
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logger.info(f"黄金价格（Binance PAXG）: ${price}")
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return price, "Binance PAXG"
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# 备源：CoinGecko
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data = fetch_url("https://api.coingecko.com/api/v3/simple/price?ids=pax-gold&vs_currencies=usd")
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if data and data.get('pax-gold', {}).get('usd'):
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price = float(data['pax-gold']['usd'])
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logger.info(f"黄金价格（CoinGecko PAXG）: ${price}")
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return price, "CoinGecko PAXG"
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# 最终备用
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logger.warning("黄金价格获取失败，使用备用值")
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return 2650.0, "fallback"
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def fetch_market_indicators():
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"""获取市场指标（VIX、DXY、WTI等）"""
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indicators = {}
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# VIX波动率指数
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vix = fetch_yahoo_price("^VIX")
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indicators['vix'] = vix if vix else 20.0
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# DXY美元指数
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dxy = fetch_yahoo_price("DX-Y.NYB")
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if not dxy:
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dxy = fetch_yahoo_price("DX=F")
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indicators['dxy'] = dxy if dxy else 104.0
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# WTI原油
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wti = fetch_yahoo_price("CL=F")
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indicators['wti'] = wti if wti else 75.0
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# 铜期货
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copper = fetch_yahoo_price("HG=F")
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indicators['copper'] = copper if copper else 4.2
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logger.info(f"市场指标: VIX={indicators['vix']}, DXY={indicators['dxy']}, WTI={indicators['wti']}, 铜={indicators['copper']}")
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return indicators
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# ============================================================================
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# XTZH AI定价引擎（核心计算）
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# ============================================================================
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def calculate_fx_layer(sdr_rates):
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"""
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计算货币层价值（FX Layer）
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1 XTZH 对应的 SDR 价值的货币层部分
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使用SDR货币篮子权重计算
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"""
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# 1 SDR = 1 XTZH（基础锚定）
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# 货币层价值 = SDR在各货币中的加权价值
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# 以USD计价：1 SDR = 1.374 USD
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sdr_in_usd = sdr_rates['USD']
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# 货币篮子验证：各货币权重之和应接近1
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# USD 43.32% + EUR 29.23% + CNY 10.59% + JPY 7.84% + GBP 8.02% = 99%
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fx_value_usd = sdr_in_usd # 货币层直接等于SDR的USD价值
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logger.info(f"货币层: 1 SDR = ${sdr_in_usd:.4f} USD")
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return fx_value_usd
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def calculate_gold_layer(gold_price_usd, sdr_rates):
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"""
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计算黄金层价值（Gold Layer）
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黄金信任锚覆盖率125%，黄金层权重10%（可在5%-20%动态调整）
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黄金层价值 = 黄金价格 / 标准黄金单位 * 黄金覆盖率
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标准：1 SDR ≈ 0.0005 盎司黄金（历史锚定）
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"""
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sdr_in_usd = sdr_rates['USD']
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# 黄金层价值：以黄金价格调整SDR价值
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# 黄金覆盖率125%意味着每1 XTZH背后有1.25倍的黄金价值支撑
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# 黄金调整因子 = 当前黄金价格 / 基准黄金价格（2020年基准 $1800/oz）
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gold_base_price = 1800.0 # 2020年基准价格
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gold_adjustment = gold_price_usd / gold_base_price
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# 黄金层贡献值（以USD计）
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# 黄金层权重10%，覆盖率125%
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gold_coverage_ratio = GOLD_TRUST_ANCHOR_COVERAGE / 10000.0 # 1.25
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gold_layer_value = sdr_in_usd * gold_adjustment * gold_coverage_ratio
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logger.info(f"黄金层: 价格=${gold_price_usd:.2f}, 调整因子={gold_adjustment:.4f}, 层价值=${gold_layer_value:.4f}")
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return gold_layer_value
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def calculate_commodity_layer(indicators, sdr_rates):
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"""
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计算商品层价值（Commodity Layer）
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商品层权重50%，包含原油、铜、农产品等大宗商品
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商品层价值 = SDR价值 * 商品综合调整因子
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"""
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sdr_in_usd = sdr_rates['USD']
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# 商品调整因子计算
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# WTI原油：基准$75，权重30%
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wti = indicators.get('wti', 75.0)
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wti_base = 75.0
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wti_factor = wti / wti_base
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# 铜价：基准$4.2/磅，权重25%
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copper = indicators.get('copper', 4.2)
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copper_base = 4.2
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copper_factor = copper / copper_base
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# DXY美元指数：基准104，反向关系（美元强则商品弱）
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dxy = indicators.get('dxy', 104.0)
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dxy_base = 104.0
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dxy_factor = dxy_base / dxy # 反向
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# VIX风险调整：基准20，高VIX降低商品层价值
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vix = indicators.get('vix', 20.0)
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vix_base = 20.0
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vix_factor = vix_base / max(vix, 10.0) # 防止除零
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# 综合商品调整因子（加权平均）
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commodity_adjustment = (
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wti_factor * 0.30 +
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copper_factor * 0.25 +
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dxy_factor * 0.30 +
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vix_factor * 0.15
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)
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commodity_layer_value = sdr_in_usd * commodity_adjustment
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logger.info(f"商品层: WTI因子={wti_factor:.4f}, 铜因子={copper_factor:.4f}, DXY因子={dxy_factor:.4f}, VIX因子={vix_factor:.4f}")
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logger.info(f"商品层综合调整={commodity_adjustment:.4f}, 层价值=${commodity_layer_value:.4f}")
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return commodity_layer_value
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def calculate_dynamic_weights(indicators, gold_price_usd):
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"""
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计算动态权重（AI调整）
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基于市场状态动态调整三层权重
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约束：w_fx + w_au + w_com = 10000（基点）
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黄金层：500 <= w_au <= 2000
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"""
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vix = indicators.get('vix', 20.0)
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dxy = indicators.get('dxy', 104.0)
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# 风险情绪调整：高VIX时增加黄金权重
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# VIX > 30: 高风险，黄金权重上调
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# VIX < 15: 低风险，黄金权重下调
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if vix > 30:
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w_au = min(W_AU_MAX, W_AU_BASE + int((vix - 30) * 30))
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elif vix < 15:
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w_au = max(W_AU_MIN, W_AU_BASE - int((15 - vix) * 25))
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else:
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w_au = W_AU_BASE
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# 美元强弱调整：DXY高时货币层权重下调
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if dxy > 110:
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fx_adjustment = -200
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elif dxy < 95:
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fx_adjustment = 200
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else:
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fx_adjustment = int((104 - dxy) * 15)
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w_fx = W_FX_BASE + fx_adjustment
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w_fx = max(2000, min(6000, w_fx)) # 限制在20%-60%
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# 商品层补足剩余权重
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w_com = WEIGHT_SUM - w_fx - w_au
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w_com = max(2000, min(7000, w_com)) # 限制在20%-70%
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# 重新归一化确保总和=10000
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total = w_fx + w_au + w_com
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if total != WEIGHT_SUM:
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diff = WEIGHT_SUM - total
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w_com += diff
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logger.info(f"动态权重: FX={w_fx/100:.1f}%, AU={w_au/100:.1f}%, COM={w_com/100:.1f}%")
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return w_fx, w_au, w_com
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def calculate_xtzh_mint_price():
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"""
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计算XTZH当日铸造价格（核心函数）
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价格公式：
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P_XTZH = (w_fx * V_fx + w_au * V_au + w_com * V_com) / WEIGHT_SUM
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其中：
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- V_fx: 货币层价值（SDR USD等价）
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- V_au: 黄金层价值（黄金调整后）
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- V_com: 商品层价值（大宗商品调整后）
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- w_fx, w_au, w_com: 动态权重（基点，总和10000）
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"""
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logger.info("=== 开始计算XTZH当日铸造价格 ===")
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# 1. 获取实时数据
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sdr_rates = fetch_sdr_rates()
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gold_price_usd, gold_source = fetch_gold_price_usd()
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indicators = fetch_market_indicators()
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# 2. 计算三层价值
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v_fx = calculate_fx_layer(sdr_rates)
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v_au = calculate_gold_layer(gold_price_usd, sdr_rates)
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v_com = calculate_commodity_layer(indicators, sdr_rates)
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# 3. 计算动态权重
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w_fx, w_au, w_com = calculate_dynamic_weights(indicators, gold_price_usd)
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# 4. 加权计算最终价格（USD）
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price_usd = (w_fx * v_fx + w_au * v_au + w_com * v_com) / WEIGHT_SUM
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# 5. 计算各货币价格
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sdr_in_usd = sdr_rates['USD']
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price_sdr = price_usd / sdr_in_usd # XTZH/SDR
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price_cny = price_usd / sdr_rates['USD'] * sdr_rates['CNY'] # 通过SDR换算
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price_eur = price_usd / sdr_rates['USD'] * sdr_rates['EUR']
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# 6. 计算铸造比例（1 USD = ? XTZH）
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mint_ratio = 1.0 / price_usd # 1 USD可以铸造多少XTZH
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# 7. 计算黄金储备支撑（每1 XTZH背后的黄金价值）
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gold_backing_per_xtzh = (w_au / WEIGHT_SUM) * v_au * (GOLD_TRUST_ANCHOR_COVERAGE / 10000.0)
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result = {
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"price_usd": round(price_usd, 6),
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"price_sdr": round(price_sdr, 6),
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"price_cny": round(price_cny, 6),
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"price_eur": round(price_eur, 6),
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"mint_ratio": round(mint_ratio, 6),
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"gold_backing_usd": round(gold_backing_per_xtzh, 6),
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"weights": {
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"fx_layer": round(w_fx / 100, 2),
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"gold_layer": round(w_au / 100, 2),
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"commodity_layer": round(w_com / 100, 2)
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},
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"components": {
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"fx_value_usd": round(v_fx, 6),
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"gold_value_usd": round(v_au, 6),
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"commodity_value_usd": round(v_com, 6)
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},
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"market_data": {
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"gold_price_usd": round(gold_price_usd, 2),
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"gold_source": gold_source,
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"sdr_rates": {
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"usd": round(sdr_rates['USD'], 6),
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"eur": round(sdr_rates['EUR'], 6),
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"gbp": round(sdr_rates['GBP'], 6),
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"jpy": round(sdr_rates['JPY'], 6),
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"cny": round(sdr_rates['CNY'], 6)
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},
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"vix": round(indicators.get('vix', 0), 2),
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"dxy": round(indicators.get('dxy', 0), 3),
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"wti_oil": round(indicators.get('wti', 0), 2),
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"copper": round(indicators.get('copper', 0), 4)
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},
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"model_info": {
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"version": "1.0.0",
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"algorithm": "NAC Constitutional Weighted Pricing",
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"gold_trust_anchor_coverage": "125%",
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"weight_constraint": "w_fx + w_au + w_com = 10000bp",
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"gold_weight_range": "5.00% - 20.00%"
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},
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"timestamp": datetime.now(timezone.utc).isoformat(),
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"next_update": "每5分钟更新一次"
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}
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logger.info(f"=== XTZH铸造价格计算完成 ===")
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logger.info(f" 价格: ${price_usd:.6f} USD / {price_sdr:.6f} SDR")
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logger.info(f" 权重: FX={w_fx/100:.1f}% AU={w_au/100:.1f}% COM={w_com/100:.1f}%")
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logger.info(f" 黄金支撑: ${gold_backing_per_xtzh:.6f} USD/XTZH")
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return result
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# ============================================================================
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# HTTP服务器
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# ============================================================================
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def get_cached_price():
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"""获取缓存的价格数据"""
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now = time.time()
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if _cache['data'] is None or (now - _cache['timestamp']) > _cache['ttl']:
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logger.info("缓存过期，重新计算XTZH价格...")
|
||
try:
|
||
_cache['data'] = calculate_xtzh_mint_price()
|
||
_cache['timestamp'] = now
|
||
except Exception as e:
|
||
logger.error(f"价格计算失败: {e}")
|
||
if _cache['data'] is None:
|
||
# 返回基础值
|
||
_cache['data'] = {
|
||
"price_usd": 1.374498,
|
||
"price_sdr": 1.0,
|
||
"price_cny": 9.444808,
|
||
"price_eur": 1.166327,
|
||
"error": str(e),
|
||
"timestamp": datetime.now(timezone.utc).isoformat()
|
||
}
|
||
return _cache['data']
|
||
|
||
class XTZHPricingHandler(BaseHTTPRequestHandler):
|
||
def log_message(self, format, *args):
|
||
logger.info(f"HTTP {args[0]} {args[1]} {args[2]}")
|
||
|
||
def send_cors_headers(self):
|
||
self.send_header('Access-Control-Allow-Origin', '*')
|
||
self.send_header('Access-Control-Allow-Methods', 'GET, OPTIONS')
|
||
self.send_header('Access-Control-Allow-Headers', 'Content-Type, Authorization')
|
||
self.send_header('Content-Type', 'application/json; charset=utf-8')
|
||
|
||
def do_OPTIONS(self):
|
||
self.send_response(200)
|
||
self.send_cors_headers()
|
||
self.end_headers()
|
||
|
||
def do_GET(self):
|
||
path = self.path.split('?')[0]
|
||
|
||
if path == '/health':
|
||
self.send_response(200)
|
||
self.send_cors_headers()
|
||
self.end_headers()
|
||
resp = json.dumps({"status": "ok", "service": "xtzh-pricing", "version": "1.0.0"})
|
||
self.wfile.write(resp.encode())
|
||
|
||
elif path in ['/price', '/api/xtzh/price', '/api/v1/xtzh/price']:
|
||
data = get_cached_price()
|
||
self.send_response(200)
|
||
self.send_cors_headers()
|
||
self.end_headers()
|
||
resp = json.dumps({"success": True, "data": data}, ensure_ascii=False)
|
||
self.wfile.write(resp.encode('utf-8'))
|
||
|
||
elif path in ['/price/simple', '/api/xtzh/price/simple']:
|
||
data = get_cached_price()
|
||
simple = {
|
||
"price_usd": data.get("price_usd"),
|
||
"price_sdr": data.get("price_sdr"),
|
||
"price_cny": data.get("price_cny"),
|
||
"price_eur": data.get("price_eur"),
|
||
"gold_price_usd": data.get("market_data", {}).get("gold_price_usd"),
|
||
"timestamp": data.get("timestamp")
|
||
}
|
||
self.send_response(200)
|
||
self.send_cors_headers()
|
||
self.end_headers()
|
||
resp = json.dumps({"success": True, "data": simple}, ensure_ascii=False)
|
||
self.wfile.write(resp.encode('utf-8'))
|
||
|
||
elif path in ['/price/refresh', '/api/xtzh/price/refresh']:
|
||
# 强制刷新缓存
|
||
_cache['timestamp'] = 0
|
||
data = get_cached_price()
|
||
self.send_response(200)
|
||
self.send_cors_headers()
|
||
self.end_headers()
|
||
resp = json.dumps({"success": True, "data": data, "refreshed": True}, ensure_ascii=False)
|
||
self.wfile.write(resp.encode('utf-8'))
|
||
|
||
else:
|
||
self.send_response(404)
|
||
self.send_cors_headers()
|
||
self.end_headers()
|
||
resp = json.dumps({"error": "Not found", "endpoints": ["/health", "/price", "/price/simple", "/price/refresh"]})
|
||
self.wfile.write(resp.encode())
|
||
|
||
def run_server(port=8709):
|
||
"""启动HTTP服务器"""
|
||
server = HTTPServer(('0.0.0.0', port), XTZHPricingHandler)
|
||
logger.info(f"XTZH AI定价服务启动，端口: {port}")
|
||
logger.info(f"API端点: http://0.0.0.0:{port}/price")
|
||
|
||
# 启动时预热缓存
|
||
logger.info("预热缓存，首次计算XTZH价格...")
|
||
get_cached_price()
|
||
|
||
server.serve_forever()
|
||
|
||
if __name__ == '__main__':
|
||
run_server(8709)
|