950 lines
41 KiB
Python
950 lines
41 KiB
Python
from random import random
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import statistics
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from datetime import datetime
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from fastapi import APIRouter, Depends, HTTPException, status, BackgroundTasks
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from typing import Optional, List, Dict, Any
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import json
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import asyncio
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import time
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from app.controllers.user_valuation import user_valuation_controller
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from app.controllers.valuation import valuation_controller
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from app.schemas.valuation import ValuationAssessmentUpdate
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from app.schemas.valuation import (
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UserValuationCreate,
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UserValuationQuery,
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UserValuationList,
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UserValuationOut,
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UserValuationDetail
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)
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from app.schemas.base import Success, BasicResponse
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from app.utils.app_user_jwt import get_current_app_user_id, get_current_app_user
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from app.utils.calculation_engine import FinalValueACalculator
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# from app.utils.calculation_engine.cultural_value_b2.sub_formulas.living_heritage_b21 import cross_border_depth_dict
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from app.utils.calculation_engine.drp import DynamicPledgeRateCalculator
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# from app.utils.calculation_engine.economic_value_b1.sub_formulas.basic_value_b11 import calculate_popularity_score
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from app.utils.calculation_engine.economic_value_b1.sub_formulas.traffic_factor_b12 import calculate_search_index_s1
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from app.log.log import logger
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from app.models.esg import ESG
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from app.models.industry import Industry
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from app.models.policy import Policy
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from app.models.user import AppUser
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from app.utils.universal_api_manager import universal_api
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from app.utils.wechat_index_calculator import wechat_index_calculator
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app_valuations_router = APIRouter(tags=["用户端估值评估"])
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async def _perform_valuation_calculation(user_id: int, data: UserValuationCreate):
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"""
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后台任务：执行估值计算
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"""
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try:
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start_ts = time.monotonic()
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logger.info("valuation.calc_start user_id={} asset_name={} industry={}", user_id,
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getattr(data, 'asset_name', None), getattr(data, 'industry', None))
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# 根据行业查询 ESG 基准分（优先用行业名称匹配，如用的是行业代码就把 name 改成 code）
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esg_obj = None
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industry_obj = None
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policy_obj = None
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try:
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esg_obj = await ESG.filter(name=data.industry).first()
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except Exception as e:
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logger.warning("valuation.esg_fetch_timeout industry={} err={}", data.industry, repr(e))
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esg_score = float(getattr(esg_obj, 'number', 0.0) or 0.0)
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# 根据行业查询 行业修正系数与ROE
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try:
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industry_obj = await asyncio.wait_for(Industry.filter(name=data.industry).first(), timeout=2.0)
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except Exception as e:
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logger.warning("valuation.industry_fetch_timeout industry={} err={}", data.industry, repr(e))
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fix_num_score = getattr(industry_obj, 'fix_num', 0.0) or 0.0
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# 根据行业查询 政策匹配度
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try:
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policy_obj = await asyncio.wait_for(Policy.filter(name=data.industry).first(), timeout=2.0)
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except Exception as e:
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logger.warning("valuation.policy_fetch_timeout industry={} err={}", data.industry, repr(e))
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policy_match_score = getattr(policy_obj, 'score', 0.0) or 0.0
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# 提取 经济价值B1 计算参数
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input_data_by_b1 = await _extract_calculation_params_b1(
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data, esg_score=esg_score, industry_coefficient=fix_num_score, policy_match_score=policy_match_score
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)
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# ESG关联价值 ESG分 (0-10分)
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input_data_by_b1["esg_score"] = esg_score
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# 行业修正系数I
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input_data_by_b1["industry_coefficient"] = fix_num_score
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# 政策匹配度
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input_data_by_b1["policy_match_score"] = policy_match_score
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# 侵权分 默认 6
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try:
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judicial_data = universal_api.query_judicial_data(data.institution)
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_data = judicial_data["data"].get("target", None) # 诉讼标的
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if _data:
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infringement_score = 0.0
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else:
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infringement_score = 10.0
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except:
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infringement_score = 0.0
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input_data_by_b1["infringement_score"] = infringement_score
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# 获取专利信息 TODO 参数
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try:
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patent_data = universal_api.query_patent_info(data.industry)
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except Exception as e:
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logger.warning("valuation.patent_api_error err={}", repr(e))
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input_data_by_b1["patent_count"] = 0.0
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input_data_by_b1["patent_score"] = 0.0
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patent_dict = patent_data if isinstance(patent_data, dict) else {}
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inner_data = patent_dict.get("data", {}) if isinstance(patent_dict.get("data", {}), dict) else {}
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data_list = inner_data.get("dataList", [])
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data_list = data_list if isinstance(data_list, list) else []
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# 验证 专利剩余年限
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# 发展潜力D相关参数 专利数量
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# 查询匹配申请号的记录集合
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matched = [item for item in data_list if
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isinstance(item, dict) and item.get("SQH") == getattr(data, 'patent_application_no', None)]
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if matched:
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patent_count_score = min(len(matched) * 2.5, 10.0)
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input_data_by_b1["patent_count"] = float(patent_count_score)
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else:
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input_data_by_b1["patent_count"] = 0.0
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years_total = calculate_total_years(data_list)
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if years_total > 10:
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patent_score = 10.0
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elif years_total >= 5:
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patent_score = 7.0
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else:
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patent_score = 3.0
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input_data_by_b1["patent_score"] = patent_score
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# 提取 文化价值B2 计算参数
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input_data_by_b2 = await _extract_calculation_params_b2(data)
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# 提取 风险调整系数B3 计算参数
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input_data_by_b3 = await _extract_calculation_params_b3(data)
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input_data_by_b3["lawsuit_status"]=infringement_score
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# 提取 市场估值C 参数
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input_data_by_c = await _extract_calculation_params_c(data)
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input_data = {
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# 模型估值B 相关参数
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"model_data": {
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# 经济价值B1 参数
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"economic_data": input_data_by_b1,
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# 文化价值B2 参数
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"cultural_data": input_data_by_b2,
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# 风险调整参数 B3
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"risky_data": input_data_by_b3,
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},
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# 市场估值C 参数
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"market_data": input_data_by_c,
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}
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calculator = FinalValueACalculator()
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# 先创建估值记录以获取ID，方便步骤落库关联
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initial_detail = await user_valuation_controller.create_valuation(
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user_id=user_id,
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data=data,
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calculation_result=None,
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calculation_input=None,
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drp_result=None,
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status='pending'
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)
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valuation_id = initial_detail.id
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logger.info("valuation.init_created user_id={} valuation_id={}", user_id, valuation_id)
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# 步骤1：立即更新计算输入参数（不管后续是否成功）
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try:
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await valuation_controller.update(
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valuation_id,
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ValuationAssessmentUpdate(
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calculation_input=input_data,
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)
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)
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logger.info("valuation.input_updated valuation_id={}", valuation_id)
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except Exception as e:
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logger.warning("valuation.failed_to_update_input valuation_id={} err={}", valuation_id, repr(e))
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# 步骤1.5：更新内置API计算字段
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try:
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# 准备内置API计算字段的值
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api_calc_fields = {}
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# ESG关联价值
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api_calc_fields["esg_value"] = str(esg_score) if esg_score is not None else None
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# 政策匹配度
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api_calc_fields["policy_matching"] = str(policy_match_score) if policy_match_score is not None else None
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# 侵权记录/法律风险
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infringement_record_value = "有侵权记录" if infringement_score == 0.0 else "无侵权记录"
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api_calc_fields["infringement_record"] = infringement_record_value
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api_calc_fields["legal_risk"] = infringement_record_value
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# 专利使用量
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patent_count_value = input_data_by_b1.get("patent_count", 0.0)
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api_calc_fields["patent_count"] = str(patent_count_value) if patent_count_value is not None else None
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# 结构复杂度（纹样基因熵值B22）
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structure_complexity_value = input_data_by_b2.get("structure_complexity", 1.5)
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api_calc_fields["pattern_complexity"] = str(structure_complexity_value) if structure_complexity_value is not None else None
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# 归一化信息熵H
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normalized_entropy_value = input_data_by_b2.get("normalized_entropy", 9)
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api_calc_fields["normalized_entropy"] = str(normalized_entropy_value) if normalized_entropy_value is not None else None
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# 线上课程点击量（暂时没有计算逻辑，设为None或默认值）
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# api_calc_fields["online_course_views"] = None
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# 基础质押率和流量修正系数（暂时没有计算逻辑，设为None或默认值）
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# api_calc_fields["base_pledge_rate"] = None
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# api_calc_fields["flow_correction"] = None
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if api_calc_fields:
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await valuation_controller.update(
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valuation_id,
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ValuationAssessmentUpdate(**api_calc_fields)
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)
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logger.info("valuation.api_calc_fields_updated valuation_id={} fields={}", valuation_id, list(api_calc_fields.keys()))
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except Exception as e:
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logger.warning("valuation.failed_to_update_api_calc_fields valuation_id={} err={}", valuation_id, repr(e))
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# 计算最终估值A（统一计算），传入估值ID以关联步骤落库
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calculation_result = await calculator.calculate_complete_final_value_a(valuation_id, input_data)
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# 步骤2：更新计算结果字段（模型估值B、市场估值C、最终估值AB、完整计算结果）
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try:
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await valuation_controller.update(
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valuation_id,
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ValuationAssessmentUpdate(
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model_value_b=calculation_result.get('model_value_b'),
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market_value_c=calculation_result.get('market_value_c'),
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final_value_ab=calculation_result.get('final_value_ab'),
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calculation_result=calculation_result,
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status='pending',
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)
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)
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logger.info(
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"valuation.result_updated valuation_id={} model_b={} market_c={} final_ab={}",
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valuation_id,
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calculation_result.get('model_value_b'),
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calculation_result.get('market_value_c'),
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calculation_result.get('final_value_ab'),
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)
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except Exception as e:
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logger.warning("valuation.failed_to_update_result valuation_id={} err={}", valuation_id, repr(e))
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# 计算动态质押
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drp_c = DynamicPledgeRateCalculator()
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'''
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monthly_amount (float): 月交易额（万元）
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heritage_level (str): 非遗等级
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'''
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# 解析月交易额字符串为数值
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monthly_amount = drp_c.parse_monthly_transaction_amount(data.monthly_transaction_amount or "")
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drp_start_ts = time.monotonic()
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drp_result = drp_c.calculate_dynamic_pledge_rate(monthly_amount, data.heritage_asset_level)
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drp_duration_ms = int((time.monotonic() - drp_start_ts) * 1000)
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# 记录动态质押率计算步骤
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await valuation_controller.log_formula_step(
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valuation_id,
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"DYNAMIC_PLEDGE_RATE",
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status="completed",
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input_params={
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"monthly_transaction_amount": data.monthly_transaction_amount,
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"monthly_amount": monthly_amount,
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"heritage_asset_level": data.heritage_asset_level,
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},
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output_result={
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"dynamic_pledge_rate": drp_result,
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"duration_ms": drp_duration_ms,
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},
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)
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logger.info("valuation.drp_calculated valuation_id={} drp={} duration_ms={}", valuation_id, drp_result, drp_duration_ms)
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# 步骤3：更新动态质押率及相关字段
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try:
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# 从动态质押率计算器中获取基础质押率和流量修正系数
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base_pledge_rate_value = "0.5" # 固定值：基础质押率 = 0.5
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flow_correction_value = "0.3" # 固定值：流量修正系数 = 0.3
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await valuation_controller.update(
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valuation_id,
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ValuationAssessmentUpdate(
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dynamic_pledge_rate=drp_result,
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base_pledge_rate=base_pledge_rate_value,
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flow_correction=flow_correction_value,
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)
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)
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logger.info("valuation.drp_updated valuation_id={} drp={} base_rate={} flow_correction={}",
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valuation_id, drp_result, base_pledge_rate_value, flow_correction_value)
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except Exception as e:
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logger.warning("valuation.failed_to_update_drp valuation_id={} err={}", valuation_id, repr(e))
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# 结构化日志：关键分值
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try:
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duration_ms = int((time.monotonic() - start_ts) * 1000)
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logger.info(
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"valuation.calc_done user_id={} duration_ms={} model_value_b={} market_value_c={} final_value_ab={}",
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user_id,
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duration_ms,
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calculation_result.get('model_value_b'),
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calculation_result.get('market_value_c'),
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calculation_result.get('final_value_ab'),
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)
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except Exception:
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pass
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# 步骤4：最后更新状态为成功
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try:
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result = await valuation_controller.update(
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valuation_id,
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ValuationAssessmentUpdate(
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status='success'
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)
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)
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logger.info("valuation.status_updated valuation_id={} status=success", valuation_id)
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except Exception as e:
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logger.warning("valuation.failed_to_update_status valuation_id={} err={}", valuation_id, repr(e))
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# 即使状态更新失败，也尝试获取结果用于日志
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result = await valuation_controller.get_by_id(valuation_id)
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logger.info("valuation.background_calc_success user_id={} valuation_id={}", user_id, valuation_id)
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except Exception as e:
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import traceback
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print(traceback.format_exc())
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logger.error("valuation.background_calc_failed user_id={} err={}", user_id, repr(e))
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# 计算失败时更新记录为失败状态
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try:
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if 'valuation_id' in locals():
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# 准备失败时需要更新的字段
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fail_update_fields = {"status": "rejected"}
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# 如果 input_data 已经准备好，确保 calculation_input 被更新（即使计算失败）
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if 'input_data' in locals():
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fail_update_fields["calculation_input"] = input_data
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# 如果内置API计算字段已经准备好，也尝试更新（即使计算失败）
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# 这些字段在步骤1.5中计算，如果步骤1.5执行了，这些变量应该已经存在
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api_calc_fields = {}
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if 'esg_score' in locals():
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api_calc_fields["esg_value"] = str(esg_score) if esg_score is not None else None
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if 'policy_match_score' in locals():
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api_calc_fields["policy_matching"] = str(policy_match_score) if policy_match_score is not None else None
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if 'infringement_score' in locals():
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infringement_record_value = "有侵权记录" if infringement_score == 0.0 else "无侵权记录"
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api_calc_fields["infringement_record"] = infringement_record_value
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api_calc_fields["legal_risk"] = infringement_record_value
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if 'input_data_by_b1' in locals():
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patent_count_value = input_data_by_b1.get("patent_count", 0.0)
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api_calc_fields["patent_count"] = str(patent_count_value) if patent_count_value is not None else None
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if 'input_data_by_b2' in locals():
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structure_complexity_value = input_data_by_b2.get("structure_complexity", 1.5)
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api_calc_fields["pattern_complexity"] = str(structure_complexity_value) if structure_complexity_value is not None else None
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normalized_entropy_value = input_data_by_b2.get("normalized_entropy", 9)
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api_calc_fields["normalized_entropy"] = str(normalized_entropy_value) if normalized_entropy_value is not None else None
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# 合并所有需要更新的字段
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fail_update_fields.update(api_calc_fields)
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try:
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await valuation_controller.update(
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valuation_id,
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ValuationAssessmentUpdate(**fail_update_fields)
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)
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logger.info("valuation.failed_but_fields_saved valuation_id={} fields={}", valuation_id, list(fail_update_fields.keys()))
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except Exception as input_err:
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logger.warning("valuation.failed_to_save_fields_on_error valuation_id={} err={}", valuation_id, repr(input_err))
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# 如果保存失败，至少更新状态
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try:
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fail_update = ValuationAssessmentUpdate(status='rejected')
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await valuation_controller.update(valuation_id, fail_update)
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except Exception:
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pass
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else:
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# 如果 valuation_id 都不存在，说明在创建记录时就失败了，无法更新
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logger.warning("valuation.failed_before_creation user_id={}", user_id)
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except Exception as create_error:
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logger.error("valuation.failed_to_update_record user_id={} err={}", user_id, repr(create_error))
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@app_valuations_router.post("/", summary="创建估值评估", response_model=BasicResponse[dict])
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async def calculate_valuation(
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background_tasks: BackgroundTasks,
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data: UserValuationCreate,
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user_id: int = Depends(get_current_app_user_id)
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):
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"""
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创建估值评估任务
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根据用户提交的估值评估数据，启动后台计算任务进行经济价值B1计算
|
||
|
||
请求示例JSON (仅包含用户填写部分):
|
||
{
|
||
"asset_name": "传统刺绣工艺",
|
||
"institution": "某文化传承机构",
|
||
"industry": "传统手工艺",
|
||
|
||
// 财务状况 (用户填写)
|
||
"annual_revenue": "500", // 近12个月机构营收/万元
|
||
"rd_investment": "50", // 近12个月机构研发投入/万元
|
||
"three_year_income": [400, 450, 500], // 近三年机构收益/万元
|
||
|
||
// 非遗等级与技术 (用户填写)
|
||
"inheritor_level": "国家级传承人", // 非遗传承人等级
|
||
"inheritor_ages": [45, 60, 75], // 传承人年龄列表
|
||
"heritage_level": "国家级", // 非遗等级
|
||
"patent_application_no": "CN202310123456.7", // 专利申请号
|
||
"patent_remaining_years": "15", // 专利剩余年限
|
||
"historical_evidence": { // 历史证明证据及数量
|
||
"历史文献": 3,
|
||
"考古发现": 2,
|
||
"传承谱系": 5
|
||
},
|
||
"pattern_images": ["demo.jpg"], // 非遗纹样图片
|
||
|
||
// 非遗应用与推广 (用户填写)
|
||
"application_maturity": "成熟应用", // 应用成熟度
|
||
"application_coverage": "全国覆盖", // 应用覆盖范围
|
||
"cooperation_depth": "0.5", // 跨界合作深度
|
||
"offline_activities": "12", // 近12个月线下宣讲活动次数
|
||
"online_accounts": [ // 线上宣传账号信息
|
||
{"platform": "抖音", "account": "传统刺绣大师"},
|
||
{"platform": "微博", "account": "非遗传承人"}
|
||
],
|
||
|
||
// 市场信息 (用户填写)
|
||
"sales_volume": "1000", // 近12个月销售量
|
||
"link_views": "5000", // 近12个月链接浏览量
|
||
"circulation": "限量", // 发行量
|
||
"last_market_activity": "2024-01-15", // 最近一次市场活动时间
|
||
"price_fluctuation": [95.0, 105.0], // 近30天价格波动区间
|
||
"manual_bids": [48000.0, 50000.0, 52000.0], // 手动收集的竞价列表
|
||
|
||
// 政策相关 (用户填写)
|
||
"funding_status": "国家级资助", // 资金支持情况
|
||
"implementation_stage": "成熟应用" // 实施阶段
|
||
}
|
||
|
||
API获取参数 (系统自动获取，无需用户填写):
|
||
- 搜索指数: 百度、微信、微博搜索指数
|
||
- 社交媒体数据: 点赞数、评论数、转发数、粉丝数
|
||
- 交易数据: 近3个月加权平均价格
|
||
- 热度数据: 近7日日均浏览量、收藏数
|
||
- ESG评分: 根据行业自动匹配
|
||
- 行业系数: 根据行业ROE计算
|
||
- 政策匹配度: 根据行业自动匹配
|
||
- 专利验证: 通过API验证专利有效性
|
||
- 侵权记录: 通过API查询侵权诉讼历史
|
||
"""
|
||
|
||
try:
|
||
from app.models.user import AppUser, AppUserQuotaLog
|
||
user = await AppUser.filter(id=user_id).first()
|
||
if not user:
|
||
raise HTTPException(status_code=404, detail="用户不存在")
|
||
if (user.remaining_quota or 0) < 1:
|
||
raise HTTPException(status_code=400, detail="估值次数不足")
|
||
before = user.remaining_quota or 0
|
||
user.remaining_quota = before - 1
|
||
await user.save()
|
||
try:
|
||
await AppUserQuotaLog.create(
|
||
app_user_id=user_id,
|
||
operator_id=user_id,
|
||
operator_name=user.alias or user.username or user.phone or "",
|
||
before_count=before,
|
||
after_count=before - 1,
|
||
remark="发起估值"
|
||
)
|
||
except Exception:
|
||
pass
|
||
|
||
background_tasks.add_task(_perform_valuation_calculation, user_id, data)
|
||
|
||
logger.info("valuation.task_queued user_id={} asset_name={} industry={}",
|
||
user_id, getattr(data, 'asset_name', None), getattr(data, 'industry', None))
|
||
|
||
return Success(
|
||
data={
|
||
"task_status": "queued",
|
||
"message": "估值计算任务已提交，正在后台处理中",
|
||
"user_id": user_id,
|
||
"asset_name": getattr(data, 'asset_name', None)
|
||
}
|
||
)
|
||
|
||
except Exception as e:
|
||
logger.error("valuation.task_queue_failed user_id={} err={}", user_id, repr(e))
|
||
raise HTTPException(status_code=500, detail=f"任务提交失败: {str(e)}")
|
||
|
||
|
||
async def _extract_calculation_params_b1(
|
||
data: UserValuationCreate,
|
||
esg_score: float = 0.0,
|
||
industry_coefficient: float = 0.0,
|
||
policy_match_score: float = 0.0,
|
||
) -> Dict[str, Any]:
|
||
"""
|
||
从用户提交的数据中提取计算所需的参数
|
||
|
||
Args:
|
||
data: 用户提交的估值评估数据
|
||
|
||
Returns:
|
||
Dict: 计算所需的参数字典
|
||
"""
|
||
# 基础价值B11相关参数
|
||
# 财务价值所需数据 从近三年收益计算
|
||
three_year_income = [safe_float(income) for income in data.three_year_income]
|
||
|
||
# 法律强度L相关参数
|
||
# 普及地域分值 默认 7分
|
||
# 普及地域分：全球覆盖(10)、全国覆盖(7)、区域覆盖(4)，默认全国覆盖(7)
|
||
try:
|
||
coverage = data.application_coverage or "全国覆盖"
|
||
mapping = {"全球覆盖": 10.0, "全国覆盖": 7.0, "区域覆盖": 4.0}
|
||
popularity_score = mapping.get(coverage, 7.0)
|
||
except Exception:
|
||
popularity_score = 7.0
|
||
|
||
# 创新投入比 = (研发费用/营收) * 100
|
||
try:
|
||
rd_investment = float(data.rd_investment) or 0
|
||
annual_revenue = float(data.annual_revenue) or 1 # 避免除零
|
||
innovation_ratio = (rd_investment / annual_revenue) * 100 if annual_revenue > 0 else 0
|
||
except (ValueError, TypeError):
|
||
innovation_ratio = 0.0
|
||
|
||
# 流量因子B12相关参数
|
||
# 近30天搜索指数S1 - 从社交媒体数据计算 TODO 需要使用第三方API
|
||
baidu_index = 1
|
||
|
||
# 获取微信指数并计算近30天平均值
|
||
try:
|
||
wechat_index_response = universal_api.wx_index(data.asset_name)
|
||
wechat_index = wechat_index_calculator.process_wechat_index_response(wechat_index_response)
|
||
logger.info(f"资产 '{data.asset_name}' 的微信指数近30天平均值: {wechat_index}")
|
||
except Exception as e:
|
||
logger.error(f"获取微信指数失败: {e}")
|
||
wechat_index = 1
|
||
|
||
weibo_index = 1
|
||
search_index_s1 = calculate_search_index_s1(baidu_index, wechat_index, weibo_index) # 默认值，实际应从API获取
|
||
|
||
# 行业均值S2 - 从数据库查询行业数据计算
|
||
from app.utils.industry_calculator import calculate_industry_average_s2
|
||
industry_average_s2 = await calculate_industry_average_s2(data.industry)
|
||
# 社交媒体传播度S3
|
||
# likes: 点赞数(API获取)
|
||
# comments: 评论数(API获取)
|
||
# shares: 转发数(API获取)
|
||
# followers: 粉丝数
|
||
# click_count: 商品链接点击量(用户填写) sales_volume 使用 sales_volume 销售量
|
||
# view_count: 内容浏览量(用户填写) link_views
|
||
|
||
# 政策乘数B13相关参数
|
||
# 政策契合度评分P - 根据行业和资助情况计算
|
||
# 实施阶段 - 需要转换为对应的评分
|
||
implementation_stage_str = data.implementation_stage or "成熟应用"
|
||
# 资金支持 - 需要转换为对应的评分
|
||
funding_support_str = data.funding_status or "无资助"
|
||
|
||
# 使用PolicyMultiplierB13Calculator来计算评分
|
||
from app.utils.calculation_engine.economic_value_b1.sub_formulas.policy_multiplier_b13 import \
|
||
PolicyMultiplierB13Calculator
|
||
policy_calculator = PolicyMultiplierB13Calculator()
|
||
implementation_stage = policy_calculator.calculate_implementation_stage_score(implementation_stage_str)
|
||
funding_support = policy_calculator.calculate_funding_support_score(funding_support_str)
|
||
|
||
# 获取线下账号 转发 点赞 评论信息 {kuaishou: {account: "123456789", likes: "33", comments: "33", shares: "33"}}
|
||
platform_accounts_data = data.platform_accounts
|
||
platform_key = next(iter(platform_accounts_data)) # 或 list(data.keys())[0]
|
||
info = platform_accounts_data[platform_key]
|
||
|
||
return {
|
||
# 基础价值B11相关参数
|
||
'three_year_income': three_year_income,
|
||
'popularity_score': popularity_score,
|
||
|
||
'innovation_ratio': innovation_ratio,
|
||
|
||
# 流量因子B12相关参数
|
||
'search_index_s1': search_index_s1,
|
||
'industry_average_s2': industry_average_s2,
|
||
# 'social_media_spread_s3': 0.0,
|
||
# 这些社交数据暂未来源，置为0，后续接入API再填充
|
||
'likes': safe_float(info["likes"]),
|
||
'comments': safe_float(info["comments"]),
|
||
'shares': safe_float(info["shares"]),
|
||
# followers 非当前计算用键，先移除避免干扰
|
||
|
||
# click_count 与 view_count 目前未参与计算，先移除
|
||
'sales_volume': safe_float(data.sales_volume),#
|
||
'link_views': safe_float(data.link_views),
|
||
# 政策乘数B13相关参数
|
||
'implementation_stage': implementation_stage,
|
||
'funding_support': funding_support,
|
||
'esg_score': safe_float(esg_score),
|
||
'industry_coefficient': safe_float(industry_coefficient),
|
||
'policy_match_score': safe_float(policy_match_score),
|
||
}
|
||
|
||
|
||
# 获取 文化价值B2 相关参数
|
||
async def _extract_calculation_params_b2(data: UserValuationCreate) -> Dict[str, Any]:
|
||
"""
|
||
argrg:
|
||
data: 用户提交的估值评估数据
|
||
|
||
retus:
|
||
Dict: 计算所需的参数字典
|
||
"""
|
||
# 导入计算器来转换传承人等级
|
||
from app.utils.calculation_engine.cultural_value_b2.sub_formulas.living_heritage_b21 import \
|
||
LivingHeritageB21Calculator
|
||
|
||
# 活态传承系数B21 县官参数
|
||
living_heritage_calculator = LivingHeritageB21Calculator()
|
||
inheritor_level = data.inheritor_level or "市级传承人" # 设置默认值
|
||
inheritor_level_coefficient = living_heritage_calculator.calculate_inheritor_level_coefficient(inheritor_level)
|
||
|
||
offline_sessions = safe_float(data.offline_activities) # 线下传习次数
|
||
platform_accounts_data = data.platform_accounts
|
||
rs = {}
|
||
for platform, info in platform_accounts_data.items():
|
||
rs[platform] = {
|
||
"likes": safe_float(info.get("likes")),
|
||
}
|
||
# 以下调用API douyin\bilibili\kuaishou
|
||
douyin_views = safe_float(rs.get("douyin", None).get("likes", 0)) if rs.get("douyin", None) else 0
|
||
kuaishou_views = safe_float(rs.get("kuaishou", None).get("likes", 0)) if rs.get("kuaishou", None) else 0
|
||
bilibili_views = safe_float(rs.get("bilibili", None).get("likes", 0)) if rs.get("bilibili", None) else 0
|
||
|
||
# 跨界合作深度：将枚举映射为项目数；若为数值字符串则直接取数值
|
||
try:
|
||
val = getattr(data, 'cooperation_depth', None)
|
||
mapping = {
|
||
"品牌联名": 3.0,
|
||
"科技载体": 5.0,
|
||
"国家外交礼品": 10.0,
|
||
}
|
||
if isinstance(val, str):
|
||
cross_border_depth = mapping.get(val, safe_float(val))
|
||
else:
|
||
cross_border_depth = safe_float(val)
|
||
except Exception:
|
||
cross_border_depth = 0.0
|
||
|
||
# 纹样基因值B22相关参数
|
||
|
||
# 以下三项需由后续模型/服务计算；此处提供默认可计算占位
|
||
#
|
||
# 历史传承度HI(用户填写)
|
||
historical_inheritance = 0.0
|
||
try:
|
||
if isinstance(data.historical_evidence, dict):
|
||
historical_inheritance = sum([safe_float(v) for v in data.historical_evidence.values()])
|
||
elif isinstance(data.historical_evidence, (list, tuple)):
|
||
historical_inheritance = sum([safe_float(i) for i in data.historical_evidence])
|
||
except Exception:
|
||
historical_inheritance = 0.0
|
||
structure_complexity = 1.5 # 默认值 纹样基因熵值B22(系统计算)
|
||
normalized_entropy = 9 # 默认值 归一化信息熵H(系统计算)
|
||
|
||
logger.info(
|
||
"b2.params inheritor_level_coefficient={} offline_sessions={} douyin_views={} kuaishou_views={} bilibili_views={} cross_border_depth={} historical_inheritance={} structure_complexity={} normalized_entropy={}",
|
||
inheritor_level_coefficient,
|
||
offline_sessions,
|
||
douyin_views,
|
||
kuaishou_views,
|
||
bilibili_views,
|
||
cross_border_depth,
|
||
historical_inheritance,
|
||
structure_complexity,
|
||
normalized_entropy,
|
||
)
|
||
|
||
return {
|
||
"inheritor_level_coefficient": inheritor_level_coefficient,
|
||
"offline_sessions": offline_sessions,
|
||
"douyin_views": douyin_views,
|
||
"kuaishou_views": kuaishou_views,
|
||
"bilibili_views": bilibili_views,
|
||
"cross_border_depth": cross_border_depth,
|
||
"historical_inheritance": historical_inheritance,
|
||
"structure_complexity": structure_complexity,
|
||
"normalized_entropy": normalized_entropy,
|
||
}
|
||
|
||
|
||
# 获取 文化价值B2 相关参数
|
||
async def _extract_calculation_params_b3(data: UserValuationCreate) -> Dict[str, Any]:
|
||
# 过去30天最高价格 过去30天最低价格 TODO 需要根据字样进行切分获取最高价和最低价 转换成 float 类型
|
||
price_fluctuation = [float(i) for i in data.price_fluctuation]
|
||
highest_price, lowest_price = max(price_fluctuation), min(price_fluctuation)
|
||
# lawsuit_status = "无诉讼" # 诉讼状态 TODO (API获取)
|
||
inheritor_ages = [float(i) for i in data.inheritor_age_count] # [45, 60, 75] # 传承人年龄列表
|
||
return {
|
||
"highest_price": highest_price,
|
||
"lowest_price": lowest_price,
|
||
|
||
"inheritor_ages": inheritor_ages,
|
||
}
|
||
|
||
|
||
# 获取 市场估值C 相关参数
|
||
async def _extract_calculation_params_c(data: UserValuationCreate) -> Dict[str, Any]:
|
||
# 市场竞价C1 TODO 暂无
|
||
# transaction_data: 交易数据字典(API获取)
|
||
# manual_bids: 手动收集的竞价列表(用户填写)
|
||
# expert_valuations: 专家估值列表(系统配置)
|
||
transaction_data: Dict = {}
|
||
manual_bids: List[float] = []
|
||
|
||
# 处理月交易额波动区间的三个关键数值：最高价、最低价、中位数
|
||
# 已实现：从data.price_fluctuation中提取并计算三个数值
|
||
price_fluctuation_median = 0 # 中位数
|
||
price_fluctuation_max = 0 # 最高价
|
||
price_fluctuation_min = 0 # 最低价
|
||
|
||
if hasattr(data, 'price_fluctuation') and data.price_fluctuation:
|
||
try:
|
||
# 将price_fluctuation转换为浮点数列表
|
||
price_values = [float(i) for i in data.price_fluctuation if i is not None]
|
||
if price_values:
|
||
price_fluctuation_max = max(price_values)
|
||
manual_bids.append(price_fluctuation_max)
|
||
price_fluctuation_min = min(price_values)
|
||
manual_bids.append(price_fluctuation_min)
|
||
price_fluctuation_median = statistics.median(price_values)
|
||
manual_bids.append(price_fluctuation_median)
|
||
|
||
except (ValueError, TypeError) as e:
|
||
# 如果转换失败，记录日志但不中断程序
|
||
logger.warning(f"价格波动区间数据转换失败: {e}")
|
||
|
||
expert_valuations = []
|
||
# 浏览热度分 - 优化数据获取逻辑
|
||
daily_browse_volume = 0 # 默认值
|
||
|
||
# 第一优先级：使用用户填写的该商品近12个月的链接浏览量
|
||
if hasattr(data, 'link_views') and data.link_views:
|
||
try:
|
||
# 尝试将字符串转换为浮点数
|
||
daily_browse_volume = float(data.link_views)
|
||
except (ValueError, TypeError):
|
||
# 如果转换失败，继续使用其他数据源
|
||
pass
|
||
|
||
# 第二优先级：如果没有link_views，尝试从平台账户数据中获取
|
||
if daily_browse_volume == 0 and hasattr(data, 'platform_accounts') and data.platform_accounts:
|
||
try:
|
||
platform_accounts_data = data.platform_accounts
|
||
# 获取第一个平台的数据
|
||
first_platform_key = next(iter(platform_accounts_data))
|
||
first_platform_data = platform_accounts_data[first_platform_key]
|
||
# 尝试获取浏览量
|
||
platform_views = first_platform_data.get("views", "0")
|
||
daily_browse_volume = float(platform_views)
|
||
except (ValueError, TypeError, StopIteration, AttributeError):
|
||
# 如果获取失败，保持默认值
|
||
daily_browse_volume = 0
|
||
|
||
# 收藏数 - 尝试从平台账户数据中获取
|
||
collection_count = 0 # 默认值
|
||
|
||
if hasattr(data, 'platform_accounts') and data.platform_accounts:
|
||
try:
|
||
platform_accounts_data = data.platform_accounts
|
||
# 获取第一个平台的数据
|
||
first_platform_key = next(iter(platform_accounts_data))
|
||
first_platform_data = platform_accounts_data[first_platform_key]
|
||
# 尝试获取收藏数
|
||
platform_likes = first_platform_data.get("likes", "0")
|
||
collection_count = int(platform_likes)
|
||
except (ValueError, TypeError, StopIteration, AttributeError):
|
||
# 如果获取失败，保持默认值
|
||
collection_count = 0
|
||
# 稀缺性乘数C3 发行量
|
||
circulation = data.scarcity_level or '限量'
|
||
|
||
# 时效性衰减C4 参数 用户选择距离最近一次市场活动（交易、报价、评估）的相距时间
|
||
recent_market_activity = data.market_activity_time
|
||
# 如果为空、None或"0"，设置默认值
|
||
if not recent_market_activity or recent_market_activity == "0":
|
||
# recent_market_activity = '2024-01-15'
|
||
recent_market_activity = '近一月'
|
||
return {
|
||
# 计算市场竞价C1
|
||
# C1 的实现接受 transaction_data={'weighted_average_price': x}
|
||
"weighted_average_price": transaction_data,
|
||
"manual_bids": manual_bids, # 手动收集的竞价列表 (用户填写)
|
||
"expert_valuations": expert_valuations, # 专家估值列表 (系统配置)
|
||
# 计算热度系数C2
|
||
"daily_browse_volume": daily_browse_volume, # 近7日日均浏览量 (API获取)
|
||
"collection_count": collection_count, # 收藏数
|
||
"issuance_level": circulation, # 默认 限量发行 计算稀缺性乘数C3
|
||
"recent_market_activity": recent_market_activity, # 默认 '近一月' 计算市场估值C
|
||
}
|
||
|
||
|
||
@app_valuations_router.get("/", summary="获取我的估值评估列表", response_model=BasicResponse[dict])
|
||
async def get_my_valuations(
|
||
query: UserValuationQuery = Depends(),
|
||
current_user: AppUser = Depends(get_current_app_user)
|
||
|
||
):
|
||
"""
|
||
获取当前用户的估值评估列表
|
||
"""
|
||
try:
|
||
result = await user_valuation_controller.get_user_valuations(
|
||
user_id=current_user.id,
|
||
query=query
|
||
)
|
||
# 使用model_dump_json()来正确序列化datetime，然后解析为dict列表
|
||
import json
|
||
serialized_items = [json.loads(item.model_dump_json()) for item in result.items]
|
||
return Success(
|
||
data={
|
||
"items": serialized_items,
|
||
"total": result.total,
|
||
"page": result.page,
|
||
"page_size": result.size,
|
||
"pages": result.pages,
|
||
}
|
||
)
|
||
except Exception as e:
|
||
raise HTTPException(
|
||
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
|
||
detail=f"获取估值评估列表失败: {str(e)}"
|
||
)
|
||
|
||
|
||
@app_valuations_router.get("/{valuation_id}", summary="获取估值评估详情", response_model=BasicResponse[dict])
|
||
async def get_valuation_detail(
|
||
valuation_id: int,
|
||
current_user: AppUser = Depends(get_current_app_user)
|
||
):
|
||
"""
|
||
获取指定估值评估的详细信息
|
||
"""
|
||
try:
|
||
result = await user_valuation_controller.get_user_valuation_detail(
|
||
user_id=current_user.id,
|
||
valuation_id=valuation_id
|
||
)
|
||
|
||
if not result:
|
||
raise HTTPException(
|
||
status_code=status.HTTP_404_NOT_FOUND,
|
||
detail="估值评估记录不存在"
|
||
)
|
||
|
||
# 使用model_dump_json()来正确序列化datetime，然后解析为dict
|
||
import json
|
||
result_dict = json.loads(result.model_dump_json())
|
||
return Success(data=result_dict)
|
||
except HTTPException:
|
||
raise
|
||
except Exception as e:
|
||
raise HTTPException(
|
||
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
|
||
detail=f"获取估值评估详情失败: {str(e)}"
|
||
)
|
||
|
||
|
||
@app_valuations_router.get("/statistics/overview", summary="获取我的估值评估统计", response_model=BasicResponse[dict])
|
||
async def get_my_valuation_statistics(
|
||
current_user: AppUser = Depends(get_current_app_user)
|
||
):
|
||
"""
|
||
获取当前用户的估值评估统计信息
|
||
"""
|
||
try:
|
||
result = await user_valuation_controller.get_user_valuation_statistics(
|
||
user_id=current_user.id
|
||
)
|
||
return Success(data=result)
|
||
except Exception as e:
|
||
raise HTTPException(
|
||
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
|
||
detail=f"获取统计信息失败: {str(e)}"
|
||
)
|
||
|
||
|
||
@app_valuations_router.delete("/{valuation_id}", summary="删除估值评估", response_model=BasicResponse[dict])
|
||
async def delete_valuation(
|
||
valuation_id: int,
|
||
current_user: AppUser = Depends(get_current_app_user)
|
||
):
|
||
"""
|
||
删除指定的估值评估记录（软删除）
|
||
"""
|
||
try:
|
||
result = await user_valuation_controller.delete_user_valuation(
|
||
user_id=current_user.id,
|
||
valuation_id=valuation_id
|
||
)
|
||
|
||
if not result:
|
||
raise HTTPException(
|
||
status_code=status.HTTP_404_NOT_FOUND,
|
||
detail="估值评估记录不存在或已被删除"
|
||
)
|
||
|
||
return Success(data={"deleted": True})
|
||
except HTTPException:
|
||
raise
|
||
except Exception as e:
|
||
raise HTTPException(
|
||
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
|
||
detail=f"删除估值评估失败: {str(e)}"
|
||
)
|
||
|
||
|
||
def calculate_total_years(data_list):
|
||
current_date = datetime.now().date()
|
||
total_years = 0
|
||
date_count = 0
|
||
for item in data_list:
|
||
if "SQRQ" in item and item["SQRQ"]:
|
||
try:
|
||
# 解析日期字符串
|
||
sqrq_date = datetime.strptime(item["SQRQ"], "%Y-%m-%d").date()
|
||
|
||
# 计算与当前日期的差值（年，包含小数）
|
||
date_diff = current_date - sqrq_date
|
||
years_diff = date_diff.days / 365.25
|
||
|
||
total_years += years_diff
|
||
date_count += 1
|
||
|
||
except ValueError as e:
|
||
return 0
|
||
|
||
return total_years
|
||
|
||
|
||
def safe_float(v):
|
||
try:
|
||
return float(v)
|
||
except (ValueError, TypeError):
|
||
return 0.0
|
||
from app.log.log import logger
|