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① D11 HTML 报告 RustFS 单源化（TECH_DEBT P2 清偿）：可视化产物写任务临时目录后
裸传报告键 html/reports/{filename}（文件名寻址），/html StaticFiles 挂载删除，
新增 html_report_router 根路径代理（报告键→遗留 JSON 包装→本地卷兜底→404，
防穿越）；URL 形状 /html/{filename} 不变，持久化引用零迁移；celery 摘除
html_data 卷，镜像不再烤入陈旧报告；顺带删除 get_stp_file_with_data 死数据块
② OCC 方案 B（D10 清偿）：run_occ(op_name, payload) 契约 + 常驻工作进程池
（occ_process_pool + occ_worker 操作注册表），超时/崩溃 terminate 换新补位、
任务级超时 recover 整体重建，残留线程泄漏根治；TopoDS 不跨进程（generate_cavity
分模 + 方案 STEP 持久化全在子进程内，返回 export_manifest）；删除内存形状缓存链、
CADExporter.export_mold_results、shape_loader（→ stp_materializer）
③ OCC 方案 A 部署参数：CELERY_CONCURRENCY / CELERY_MAX_TASKS_PER_CHILD 进
Dockerfile.celery + compose + .env.example
④ D2 诚实标注：铝价响应带 source: "simulated"，前端按来源渲染标注（原硬编码
"上海期货交易所"属虚假声明），死代码 getAluminumPrice 删除
⑤ CI 门禁：.gitea/workflows/ci.yml 三 job（pytest / 前端构建含 vue-tsc /
openapi 漂移检测）
接口变更三件套随批完成（openapi 76→77 paths + gen:api + 前端构建通过；方案 B
接口面零变化）。测试基线 143 passed, 0 skipped（新增 16 项）。文档六处同步。
Co-Authored-By: Claude Code <noreply@anthropic.com>
98 lines
3.0 KiB
Python
98 lines
3.0 KiB
Python
"""
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铝金属价格数据服务
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提供铝金属的当前价格和历史价格走势数据。
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数据来源优先级：
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1. 外部API（预留接口）
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2. 模拟真实走势数据（当前使用）
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数据基于上海期货交易所(SHFE)铝期货价格走势特征生成。
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"""
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import random
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import hashlib
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from datetime import datetime, timedelta
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from typing import List, Dict, Optional
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BASE_PRICE = 18950.0
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PRICE_VOLATILITY = 120.0
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TREND_DRIFT = 0.3
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def _daily_seed(date_str: str) -> float:
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h = hashlib.md5(date_str.encode()).hexdigest()
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seed = int(h[:8], 16) / (16 ** 8)
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return seed
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def get_aluminum_current_price() -> Dict:
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today = datetime.now().strftime("%Y-%m-%d")
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seed = _daily_seed(today)
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random.seed(int(seed * 1_000_000))
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price = BASE_PRICE + (seed - 0.5) * PRICE_VOLATILITY * 2
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price = round(price, 0)
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yesterday = (datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d")
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prev_seed = _daily_seed(yesterday)
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prev_price = BASE_PRICE + (prev_seed - 0.5) * PRICE_VOLATILITY * 2
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prev_price = round(prev_price, 0)
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change = price - prev_price
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change_percent = round((change / prev_price) * 100, 2)
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week_ago = (datetime.now() - timedelta(days=7)).strftime("%Y-%m-%d")
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week_seed = _daily_seed(week_ago)
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week_price = BASE_PRICE + (week_seed - 0.5) * PRICE_VOLATILITY * 2
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random.seed()
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return {
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"price": price,
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"unit": "元/吨",
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"currency": "CNY",
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"date": today,
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"change": round(change, 0),
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"change_percent": change_percent,
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"open": round(price - random.uniform(10, 50), 0),
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"high": round(price + random.uniform(10, 60), 0),
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"low": round(price - random.uniform(10, 60), 0),
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"prev_close": prev_price,
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"week_ago_price": round(week_price, 0),
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# D2：数据为模拟走势（见模块 docstring），必须显式声明来源，
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# 前端按此字段展示"模拟/参考"标注，防止被当作实时行情
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"source": "simulated",
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}
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def get_aluminum_price_history(days: int = 30) -> List[Dict]:
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history = []
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random.seed(42)
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price_line = BASE_PRICE
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for i in range(days, -1, -1):
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date = (datetime.now() - timedelta(days=i)).strftime("%Y-%m-%d")
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date_seed = _daily_seed(date)
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drift = (date_seed - 0.5) * TREND_DRIFT
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noise = (date_seed - 0.5) * PRICE_VOLATILITY * 1.5
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price_line = price_line + drift + noise * 0.3
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price_line = max(18200, min(19800, price_line))
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open_price = round(price_line + (date_seed - 0.5) * 80, 0)
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high_price = round(open_price + abs(date_seed - 0.5) * 160, 0)
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low_price = round(open_price - abs(date_seed - 0.5) * 140, 0)
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close_price = round(price_line, 0)
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history.append({
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"date": date,
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"open": open_price,
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"high": high_price,
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"low": low_price,
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"close": close_price,
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"source": "simulated", # D2：与 current 一致，逐项显式声明模拟来源
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})
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random.seed()
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return history
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