diff --git a/app/api/v1/app_valuations/app_valuations.py b/app/api/v1/app_valuations/app_valuations.py index d9f2462..754641c 100644 --- a/app/api/v1/app_valuations/app_valuations.py +++ b/app/api/v1/app_valuations/app_valuations.py @@ -1,5 +1,8 @@ from fastapi import APIRouter, Depends, HTTPException, status -from typing import Optional +from typing import Optional, List, Dict, Any +import json +import asyncio +import time from app.controllers.user_valuation import user_valuation_controller from app.schemas.valuation import ( @@ -9,89 +12,431 @@ from app.schemas.valuation import ( UserValuationOut, UserValuationDetail ) -from app.models.user import AppUser - from app.schemas.base import Success, SuccessExtra -from app.utils.app_user_jwt import get_current_app_user +from app.utils.app_user_jwt import get_current_app_user_id, get_current_app_user +from app.utils.calculation_engine import FinalValueACalculator +from app.utils.calculation_engine.drp import DynamicPledgeRateCalculator +from app.utils.calculation_engine.economic_value_b1.sub_formulas.basic_value_b11 import calculate_popularity_score, \ + calculate_infringement_score, calculate_patent_usage_score +from app.utils.calculation_engine.economic_value_b1.sub_formulas.traffic_factor_b12 import calculate_search_index_s1 +from app.log.log import logger +from app.models.esg import ESG +from app.models.industry import Industry +from app.models.policy import Policy +from app.models.user import AppUser +from app.utils.universal_api_manager import universal_api +from app.utils.wechat_index_calculator import wechat_index_calculator app_valuations_router = APIRouter(tags=["用户端估值评估"]) @app_valuations_router.post("/", summary="创建估值评估") -async def create_valuation( - data: UserValuationCreate, - current_user: AppUser = Depends(get_current_app_user) +async def calculate_valuation( + data: UserValuationCreate, + user_id: int = Depends(get_current_app_user_id) ): """ - 用户创建估值评估申请 + 计算估值评估 + + 根据用户提交的估值评估数据，调用计算引擎进行经济价值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: + start_ts = time.monotonic() + logger.info("valuation.calc_start user_id={} asset_name={} industry={}", user_id, getattr(data, 'asset_name', None), getattr(data, 'industry', None)) + + # 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） + esg_obj = None + industry_obj = None + policy_obj = None + + try: + esg_obj = await asyncio.wait_for(ESG.filter(name=data.industry).first(), timeout=2.0) + except Exception as e: + logger.warning("valuation.esg_fetch_timeout industry={} err={}", data.industry, repr(e)) + esg_score = float(getattr(esg_obj, 'number', 0.0) or 0.0) + + # 根据行业查询 行业修正系数与ROE + try: + industry_obj = await asyncio.wait_for(Industry.filter(name=data.industry).first(), timeout=2.0) + except Exception as e: + logger.warning("valuation.industry_fetch_timeout industry={} err={}", data.industry, repr(e)) + fix_num_score = getattr(industry_obj, 'fix_num', 0.0) or 0.0 + + # 根据行业查询 政策匹配度 + try: + policy_obj = await asyncio.wait_for(Policy.filter(name=data.industry).first(), timeout=2.0) + except Exception as e: + logger.warning("valuation.policy_fetch_timeout industry={} err={}", data.industry, repr(e)) + policy_match_score = getattr(policy_obj, 'score', 0.0) or 0.0 + # 提取 经济价值B1 计算参数 + input_data_by_b1 = await _extract_calculation_params_b1(data) + # ESG关联价值 ESG分 (0-10分) + input_data_by_b1["esg_score"] = esg_score + # 行业修正系数I + input_data_by_b1["industry_coefficient"] = fix_num_score + # 政策匹配度 + input_data_by_b1["policy_match_score"] = policy_match_score + + # 获取专利信息 TODO 参数 + + try: + patent_data = universal_api.query_patent_info("未找到 企业名称、企业统代、企业注册号") + patent_dict = patent_data if isinstance(patent_data, dict) else {} + inner_data = patent_dict.get("data", {}) if isinstance(patent_dict.get("data", {}), dict) else {} + data_list = inner_data.get("dataList", []) + data_list = data_list if isinstance(data_list, list) else [] + # 验证 专利剩余年限 + # TODO 无法验证 专利剩余保护期>10年(10分)，5-10年(7分)，<5年(3分)； + + # 发展潜力D相关参数 专利数量 + # 查询匹配申请号的记录集合 + matched = [item for item in data_list if isinstance(item, dict) and item.get("SQH") == getattr(data, 'patent_application_no', None)] + if matched: + patent_count = calculate_patent_usage_score(len(matched)) + input_data_by_b1["patent_count"] = float(patent_count) + else: + input_data_by_b1["patent_count"] = 0.0 + input_data_by_b1["patent_score"] = 0 + except Exception as e: + logger.warning("valuation.patent_api_error err={}", repr(e)) + input_data_by_b1["patent_count"] = 0.0 + + # 提取 文化价值B2 计算参数 + input_data_by_b2 = await _extract_calculation_params_b2(data) + # 提取 风险调整系数B3 计算参数 + input_data_by_b3 = await _extract_calculation_params_b3(data) + # 提取 市场估值C 参数 + input_data_by_c = await _extract_calculation_params_c(data) + + + input_data = { + # 模型估值B 相关参数 + "model_data": { + # 经济价值B1 参数 + "economic_data": input_data_by_b1, + # 文化价值B2 参数 + "cultural_data": input_data_by_b2, + # 风险调整参数 B3 + "risky_data": input_data_by_b3, + }, + # 市场估值C 参数 + "market_data": input_data_by_c, + } + + calculator = FinalValueACalculator() + # 计算最终估值A（统一计算） + calculation_result = calculator.calculate_complete_final_value_a(input_data) + + # 计算动态质押 + drp_c = DynamicPledgeRateCalculator() + ''' + monthly_amount (float): 月交易额（万元） + heritage_level (str): 非遗等级 + ''' + # 解析月交易额字符串为数值 + monthly_amount = drp_c.parse_monthly_transaction_amount(data.monthly_transaction_amount or "") + drp_result = drp_c.calculate_dynamic_pledge_rate(monthly_amount, data.heritage_asset_level) + + # 结构化日志：关键分值 + try: + duration_ms = int((time.monotonic() - start_ts) * 1000) + logger.info( + "valuation.calc_done user_id={} duration_ms={} model_value_b={} market_value_c={} final_value_ab={}", + user_id, + duration_ms, + calculation_result.get('model_value_b'), + calculation_result.get('market_value_c'), + calculation_result.get('final_value_ab'), + ) + except Exception: + pass + # 创建估值评估记录 result = await user_valuation_controller.create_valuation( - user_id=current_user.id, - data=data + user_id=user_id, + data=data, + calculation_result=calculation_result, + calculation_input={ + 'model_data': { + 'economic_data': list(input_data.get('model_data', {}).get('economic_data', {}).keys()), + 'cultural_data': list(input_data.get('model_data', {}).get('cultural_data', {}).keys()), + 'risky_data': list(input_data.get('model_data', {}).get('risky_data', {}).keys()), + }, + 'market_data': list(input_data.get('market_data', {}).keys()), + }, + drp_result=drp_result ) - # 使用model_dump_json()来正确序列化datetime，然后解析为dict - import json + + # 组装返回 result_dict = json.loads(result.model_dump_json()) - # 开始计算 估值 信息 - # 1 # 经济价值B1模块: EconomicValueB1Calculator | BasicValueB11Calculator | TrafficFactorB12Calculator | PolicyMultiplierB13Calculator - # 1.1 EconomicValueB1Calculator - # input_data = { - # # 基础价值B11相关参数 - # 'three_year_income': data.three_year_income, - # 'patent_score': data.pa, # 专利分 - # 'popularity_score': data.popularity_score, # 普及地域分值 - # 'infringement_score': data.infringement_score, # 侵权分 - # 'innovation_ratio': data.innovation_ratio, - # 'esg_score':data.esg_score, - # 'industry_coefficient':data.industry_coefficient, + # "calculation_result": { + # "model_value_b": 660.1534497474814, + # "market_value_c": 8800.0, + # "final_value_ab": 3102.107414823237 + # } + result_dict['calculation_result'] = calculation_result - # # 流量因子B12相关参数 - # 'search_index_s1': 4500.0, - # 'industry_average_s2': 5000.0, - # # 'social_media_spread_s3': social_media_spread_s3, - # 'likes': 4, # 点赞 - # 'comments': 5, # 评论 - # 'shares': 6, # 转发 - # 'followers': 7, # 粉丝数 + result_dict['calculation_input'] = { + 'model_data': { + 'economic_data': list(input_data.get('model_data', {}).get('economic_data', {}).keys()), + 'cultural_data': list(input_data.get('model_data', {}).get('cultural_data', {}).keys()), + 'risky_data': list(input_data.get('model_data', {}).get('risky_data', {}).keys()), + }, + 'market_data': list(input_data.get('market_data', {}).keys()), + } - # 'click_count': 1000,# 点击量 - # 'view_count': 100, # 内容浏览量 + return Success(data=result_dict, msg="估值计算完成") - # # 政策乘数B13相关参数 - # 'policy_match_score': 10.0, # 政策匹配度 - # 'implementation_stage': 10.0, # 实施阶段评分 - # 'funding_support': 10.0 # 资金支持度 - # } - # 1.2 BasicValueB11Calculator - # 1.3 TrafficFactorB12Calculator - # 1.4 PolicyMultiplierB13Calculator - - # 2 # 文化价值B2模块: CulturalValueB2Calculator | LivingHeritageB21Calculator | PatternGeneB22Calculator - # 2.1 CulturalValueB2Calculator - # 2.2 LivingHeritageB21Calculator - # 2.3 PatternGeneB22Calculator - - # 3 # 风险调整系数B3模块: RiskAdjustmentB3Calculator - # 3.1 RiskAdjustmentB3Calculator - - # 4 # 市场估值C模块: MarketValueCCalculator | MarketBiddingC1Calculator | HeatCoefficientC2Calculator | ScarcityMultiplierC3Calculator | TemporalDecayC4Calculator - # 4.1 MarketValueCCalculator - # 4.2 MarketBiddingC1Calculator - # 4.3 HeatCoefficientC2Calculator - # 4.4 ScarcityMultiplierC3Calculator - # 4.5 TemporalDecayC4Calculator - - # 5 # 最终估值A模块: FinalValueACalculator - # 5.1 FinalValueACalculator - return Success(data=result_dict, msg="估值评估申请提交成功") except Exception as e: - raise HTTPException( - status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, - detail=f"创建估值评估失败: {str(e)}" - ) + import traceback + print(traceback.format_exc()) + logger.error("valuation.calc_failed user_id={} err={}", user_id, repr(e)) + raise HTTPException(status_code=400, detail=f"计算失败: {str(e)}") +async def _extract_calculation_params_b1(data: UserValuationCreate) -> 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 = data.three_year_income or [0, 0, 0] + + # 法律强度L相关参数 + # 普及地域分值 默认 7分 + popularity_score = calculate_popularity_score(data.application_coverage) + + # 侵权分 默认 6 TODO 需要使用第三方API 无侵权记录(10分)，历史侵权已解决(6分)，现存纠纷(2分) + infringement_score = calculate_infringement_score("无侵权信息") + infringement_score = 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 = 0 + + # 获取微信指数并计算近30天平均值 + try: + 1/0 + 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 = 0 + + weibo_index = 0 + 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 - TODO 需要使用第三方API,click_count view_count 未找到对应参数 + # 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.application_maturity 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) + + return { + # 基础价值B11相关参数 + 'three_year_income': three_year_income, + 'popularity_score': popularity_score, + 'infringement_score': infringement_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': 0, + 'comments': 0, + 'shares': 0, + # 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 + + # 政策乘数B13相关参数 + 'implementation_stage': implementation_stage, + 'funding_support':funding_support + } + +# 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 = int(data.offline_activities) #线下传习次数 + # 以下调用API douyin\bilibili\kuaishou + douyin_views = 0 + kuaishou_views= 0 + bilibili_views= 0 + # 跨界合作深度 品牌联名0.3，科技载体0.5，国家外交礼品1.0 + cross_border_depth = float(data.cooperation_depth) + + # 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 + historical_inheritance = 0.8 + structure_complexity = 0.75 + normalized_entropy = 0.85 + 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 + highest_price,lowest_price= data.price_fluctuation + lawsuit_status = "无诉讼" # 诉讼状态 TODO (API获取) + inheritor_ages = data.inheritor_age_count # [45, 60, 75] # 传承人年龄列表 + return { + "highest_price": highest_price, + "lowest_price": lowest_price, + "lawsuit_status": lawsuit_status, + "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 = None + manual_bids: List[float] = None + expert_valuations: List[float] = None + # 浏览热度分 TODO 需要先确定平台信息 + daily_browse_volume = 500.0 # 近7日日均浏览量(默认占位) + collection_count = 50 # 收藏数(默认占位) + # 稀缺性乘数C3 发行量 + circulation = data.circulation 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.last_market_activity + # 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' + 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") async def get_my_valuations( query: UserValuationQuery = Depends(), diff --git a/app/api/v1/app_valuations/wechat_index.txt b/app/api/v1/app_valuations/wechat_index.txt new file mode 100644 index 0000000..2666b0f --- /dev/null +++ b/app/api/v1/app_valuations/wechat_index.txt @@ -0,0 +1,261 @@ +{ + 'category': [ + { + 'type': 0, + 'word': '全部' + }, + { + 'type': 7, + 'word': '视频号' + }, + { + 'type': 2, + 'word': '文章' + }, + { + 'type': 1, + 'word': '公众号' + }, + { + 'type': 262208, + 'word': '小程序' + }, + { + 'extra_kvs': [ + { + 'key': 'modelName', + 'value': 'hunyuan-t1-turbos' + }, + { + 'key': 'modelType', + 'value': 't1' + }, + { + 'key': 'fastModelType', + 'value': 'fast' + } + ], + 'type': 53, + 'word': 'AI搜索' + }, + { + 'type': 9, + 'word': '直播' + }, + { + 'type': 1024, + 'word': '读书' + }, + { + 'type': 512, + 'word': '听一听' + }, + { + 'type': 384, + 'word': '表情' + }, + { + 'type': 16777728, + 'word': '百科' + }, + { + 'type': 16384, + 'word': '新闻' + }, + { + 'selected': 1, + 'type': 8192, + 'word': '微信指数' + }, + { + 'type': 33562630, + 'word': '划线' + }, + { + 'type': 8, + 'word': '朋友圈' + } + ], + 'continueFlag': 0, + 'cookies': '{"box_offset":0,"businessType":8192,"cookies_buffer":"UisIYhABGIBAIgzotYTkuqflkI3np7BQAYIBBRAAogEAsgECGACaAwRCAHIA","doc_offset":0,"dup_bf":"","isHomepage":0,"page_cnt":1,"query":"资产名称","scene":98}\n', + 'data': [ + { + 'boxID': '0x40000-15048-', + 'boxPos': 1, + 'boxPosMerge': 1, + 'count': 1, + 'items': [ + { + 'docID': '1-7123206500956315942', + 'itemInfo': { + 'data': [ + { + 'index': '113', + 'timestamp': 1757433600 + }, + { + 'index': '51', + 'timestamp': 1757520000 + }, + { + 'index': '112', + 'timestamp': 1757606400 + }, + { + 'index': '26', + 'timestamp': 1757692800 + }, + { + 'index': '24', + 'timestamp': 1757779200 + }, + { + 'index': '118', + 'timestamp': 1757865600 + }, + { + 'index': '46', + 'timestamp': 1757952000 + }, + { + 'index': '90', + 'timestamp': 1758038400 + }, + { + 'index': '200', + 'timestamp': 1758124800 + }, + { + 'index': '70', + 'timestamp': 1758211200 + }, + { + 'index': '23', + 'timestamp': 1758297600 + }, + { + 'index': '1', + 'timestamp': 1758384000 + }, + { + 'index': '44', + 'timestamp': 1758470400 + }, + { + 'index': '93', + 'timestamp': 1758556800 + }, + { + 'index': '91', + 'timestamp': 1758643200 + }, + { + 'index': '6', + 'timestamp': 1758729600 + }, + { + 'index': '46', + 'timestamp': 1758816000 + }, + { + 'index': '1', + 'timestamp': 1758902400 + }, + { + 'index': '66', + 'timestamp': 1758988800 + }, + { + 'index': '45', + 'timestamp': 1759075200 + }, + { + 'index': '23', + 'timestamp': 1759161600 + }, + { + 'index': '22', + 'timestamp': 1759248000 + }, + { + 'index': '0', + 'timestamp': 1759334400 + }, + { + 'index': '0', + 'timestamp': 1759420800 + }, + { + 'index': '22', + 'timestamp': 1759507200 + }, + { + 'index': '22', + 'timestamp': 1759593600 + }, + { + 'index': '23', + 'timestamp': 1759680000 + }, + { + 'index': '1', + 'timestamp': 1759766400 + }, + { + 'index': '0', + 'timestamp': 1759852800 + }, + { + 'index': '24', + 'timestamp': 1759939200 + } + ], + 'title': '资产名称 - 微信指数', + 'type': 1058 + }, + 'jumpInfo': { + 'jumpType': 2, + 'reportId': 'chart:chart:317451', + 'userName': 'gh_935b85261f35@app', + 'weappUrl': '/page/detail/detail?calculate_word=资产名称' + }, + 'source': { + 'iconUrl': 'http://mmbiz.qpic.cn/mmbiz_png/uic3vZ5pI29sdd0tUo5t4pxmJMsMO9iaxM8EOxTX1VUAWjQibib0juc81kMkUgtB9IibIg58TZocULicPJ7lichq8E1VQ/640?wx_fmt=png&wxfrom=200', + 'title': '微信指数' + }, + 'title': '' + } + ], + 'real_type': 262144, + 'subType': 15048, + 'type': 52 + } + ], + 'direction': 2, + 'enableQuestionClosely': False, + 'experiment': [ + { + 'key': 's1s_all_prefetch_next_page', + 'value': '2' + }, + { + 'key': 'mmsearch_exp_financial_style', + 'value': '2' + } + ], + 'isAutoPlayVideo': 1, + 'isDivide': 0, + 'isHomePage': 0, + 'lang': 'zh_CN', + 'nomoreText': '没有更多的搜索结果', + 'offset': 20, + 'pageNumber': 1, + 'query': '资产名称', + 'resultType': 0, + 'ret': 0, + 'searchID': '1448000677067408154', + 'timeStamp': 1760081917, + 'code': 0, + 'cost_money': 0.5, + 'remain_money': 28.5 +} diff --git a/app/api/v1/calculation/calcuation.py b/app/api/v1/calculation/calcuation.py index abbe4f5..4f66978 100644 --- a/app/api/v1/calculation/calcuation.py +++ b/app/api/v1/calculation/calcuation.py @@ -191,7 +191,9 @@ async def calculate_valuation( monthly_amount (float): 月交易额（万元） heritage_level (str): 非遗等级 ''' - drp_result = drp_c.calculate_dynamic_pledge_rate(float(data.monthly_transaction_amount),data.heritage_asset_level) + # 解析月交易额字符串为数值 + monthly_amount = drp_c.parse_monthly_transaction_amount(data.monthly_transaction_amount or "") + drp_result = drp_c.calculate_dynamic_pledge_rate(monthly_amount, data.heritage_asset_level) # 结构化日志：关键分值 try: @@ -209,7 +211,17 @@ async def calculate_valuation( # 创建估值评估记录 result = await user_valuation_controller.create_valuation( user_id=user_id, - data=data + data=data, + calculation_result=calculation_result, + calculation_input={ + 'model_data': { + 'economic_data': list(input_data.get('model_data', {}).get('economic_data', {}).keys()), + 'cultural_data': list(input_data.get('model_data', {}).get('cultural_data', {}).keys()), + 'risky_data': list(input_data.get('model_data', {}).get('risky_data', {}).keys()), + }, + 'market_data': list(input_data.get('market_data', {}).keys()), + }, + drp_result=drp_result ) # 组装返回 @@ -319,8 +331,14 @@ async def _extract_calculation_params_b2(data: UserValuationCreate) -> Dict[str, 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 - inheritor_level_coefficient = data.inheritor_level # 传承人等级 + 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 = int(data.offline_activities) #线下传习次数 # 以下调用API douyin\bilibili\kuaishou douyin_views = 0 @@ -377,7 +395,10 @@ async def _extract_calculation_params_c(data: UserValuationCreate) -> Dict[str, circulation = data.circulation 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.last_market_activity or '2024-01-15' + recent_market_activity = data.last_market_activity + # 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' return { # 计算市场竞价C1 # C1 的实现接受 transaction_data={'weighted_average_price': x} diff --git a/app/controllers/user_valuation.py b/app/controllers/user_valuation.py index 2211cb7..5eea7b2 100644 --- a/app/controllers/user_valuation.py +++ b/app/controllers/user_valuation.py @@ -18,12 +18,25 @@ class UserValuationController: def __init__(self): self.model = ValuationAssessment - async def create_valuation(self, user_id: int, data: UserValuationCreate) -> UserValuationDetail: + async def create_valuation(self, user_id: int, data: UserValuationCreate, calculation_result: dict = None, calculation_input: dict = None, drp_result: float = None) -> UserValuationDetail: """用户创建估值评估""" valuation_data = data.model_dump() valuation_data['user_id'] = user_id valuation_data['status'] = 'pending' # 默认状态为待审核 + # 添加计算结果到数据库 + if calculation_result: + valuation_data['model_value_b'] = calculation_result.get('model_value_b') + valuation_data['market_value_c'] = calculation_result.get('market_value_c') + valuation_data['final_value_ab'] = calculation_result.get('final_value_ab') + valuation_data['calculation_result'] = calculation_result + + if calculation_input: + valuation_data['calculation_input'] = calculation_input + + if drp_result is not None: + valuation_data['dynamic_pledge_rate'] = drp_result + valuation = await self.model.create(**valuation_data) return await self._to_user_detail(valuation) @@ -141,6 +154,13 @@ class UserValuationController: legal_risk=valuation.legal_risk, base_pledge_rate=valuation.base_pledge_rate, flow_correction=valuation.flow_correction, + # 添加计算结果字段 + model_value_b=valuation.model_value_b, + market_value_c=valuation.market_value_c, + final_value_ab=valuation.final_value_ab, + dynamic_pledge_rate=valuation.dynamic_pledge_rate, + calculation_result=valuation.calculation_result, + calculation_input=valuation.calculation_input, status=valuation.status, admin_notes=valuation.admin_notes, created_at=valuation.created_at, diff --git a/app/models/valuation.py b/app/models/valuation.py index ff9b9b3..797dbe7 100644 --- a/app/models/valuation.py +++ b/app/models/valuation.py @@ -68,6 +68,14 @@ class ValuationAssessment(Model): base_pledge_rate = fields.CharField(max_length=50, null=True, description="基础质押率") flow_correction = fields.CharField(max_length=50, null=True, description="流量修正系数") + # 计算结果字段 + model_value_b = fields.FloatField(null=True, description="模型估值B（万元）") + market_value_c = fields.FloatField(null=True, description="市场估值C（万元）") + final_value_ab = fields.FloatField(null=True, description="最终估值AB（万元）") + dynamic_pledge_rate = fields.FloatField(null=True, description="动态质押率") + calculation_result = fields.JSONField(null=True, description="完整计算结果JSON") + calculation_input = fields.JSONField(null=True, description="计算输入参数JSON") + # 系统字段 user = fields.ForeignKeyField("models.AppUser", related_name="valuations", description="提交用户") status = fields.CharField(max_length=20, default="pending", description="评估状态: pending(待审核), approved(已通过), rejected(已拒绝)") diff --git a/app/schemas/valuation.py b/app/schemas/valuation.py index 9604e2f..e96a032 100644 --- a/app/schemas/valuation.py +++ b/app/schemas/valuation.py @@ -65,6 +65,14 @@ class ValuationAssessmentBase(BaseModel): legal_risk: Optional[str] = Field(None, description="法律风险-侵权诉讼历史") base_pledge_rate: Optional[str] = Field(None, description="基础质押率") flow_correction: Optional[str] = Field(None, description="流量修正系数") + + # 计算结果字段 + model_value_b: Optional[float] = Field(None, description="模型估值B（万元）") + market_value_c: Optional[float] = Field(None, description="市场估值C（万元）") + final_value_ab: Optional[float] = Field(None, description="最终估值AB（万元）") + dynamic_pledge_rate: Optional[float] = Field(None, description="动态质押率") + calculation_result: Optional[Dict[str, Any]] = Field(None, description="完整计算结果JSON") + calculation_input: Optional[Dict[str, Any]] = Field(None, description="计算输入参数JSON") class ValuationAssessmentCreate(ValuationAssessmentBase): diff --git a/app/settings/config.py b/app/settings/config.py index 07eace2..47bce14 100644 --- a/app/settings/config.py +++ b/app/settings/config.py @@ -18,9 +18,9 @@ class Settings(BaseSettings): DEBUG: bool = True # 服务器配置 - SERVER_HOST: str = "127.0.0.1" + SERVER_HOST: str = "124.222.245.240" SERVER_PORT: int = 9999 - BASE_URL: str = f"http://{SERVER_HOST}:{SERVER_PORT}" + BASE_URL: str = f"http://{SERVER_HOST}:8080" PROJECT_ROOT: str = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir)) BASE_DIR: str = os.path.abspath(os.path.join(PROJECT_ROOT, os.pardir)) diff --git a/app/utils/api_config.py b/app/utils/api_config.py index ab30669..15fce2e 100644 --- a/app/utils/api_config.py +++ b/app/utils/api_config.py @@ -127,15 +127,6 @@ class APIConfig: "description": "该接口用于获取指定B站视频的详细信息，包括视频地址、描述文案、作者信息、发布时间、播放量、点赞数、评论数与分享数等", "required_params": ["token", "bvid"], "optional_params": [] - }, - "jizhiliao_index_search": { - "path": "/fbmain/monitor/v3/web_search", - "method": "POST", - "description": "极致聊指数搜索", - "api_key": os.getenv("JIZHILIAO_API_KEY", "JZL089ef0b7d0315d96"), - "verifycode": os.getenv("JIZHILIAO_VERIFYCODE", ""), - "required_params": ["keyword", "mode", "BusinessType", "sub_search_type"], - "optional_params": ["key", "verifycode"] } } }, @@ -148,9 +139,11 @@ class APIConfig: "web_search": { "path": "/fbmain/monitor/v3/web_search", "method": "POST", - "description": "获取微信指数", - "required_params": ["keyword", "key"], - "optional_params": [] + "description": "极致聊指数搜索", + "api_key": os.getenv("JIZHILIAO_API_KEY", "JZL089ef0b7d0315d96"), + "verifycode": os.getenv("JIZHILIAO_VERIFYCODE", ""), + "required_params": ["keyword", "mode", "BusinessType", "sub_search_type"], + "optional_params": ["key", "verifycode"] } } }, diff --git a/app/utils/calculation_engine/drp/sub_formulas/dynamic_pledge_rate.py b/app/utils/calculation_engine/drp/sub_formulas/dynamic_pledge_rate.py index c590738..430e699 100644 --- a/app/utils/calculation_engine/drp/sub_formulas/dynamic_pledge_rate.py +++ b/app/utils/calculation_engine/drp/sub_formulas/dynamic_pledge_rate.py @@ -66,6 +66,47 @@ class DynamicPledgeRateCalculator: else: return 0.0 + def parse_monthly_transaction_amount(self, monthly_transaction_str: str) -> float: + """ + 解析月交易额字符串，转换为数值（万元） + + 参数: + monthly_transaction_str (str): 月交易额字符串，如"月交易额<100万元"、"100-500万元"等 + + 返回: + float: 月交易额数值（万元） + """ + if not monthly_transaction_str: + return 0.0 + + # 清理字符串，移除空格和常见前缀 + clean_str = monthly_transaction_str.strip().replace("月交易额", "").replace("万元", "") + + # 处理不同的格式 + if "<100" in clean_str or "小于100" in clean_str: + return 50.0 # 取中间值 + elif "100-500" in clean_str or "100万-500万" in clean_str: + return 300.0 # 取中间值 + elif ">500" in clean_str or "大于500" in clean_str or "≥500" in clean_str: + return 600.0 # 取一个合理值 + elif "500-1000" in clean_str: + return 750.0 # 取中间值 + elif ">1000" in clean_str or "大于1000" in clean_str: + return 1200.0 # 取一个合理值 + else: + # 尝试提取数字 + import re + numbers = re.findall(r'\d+', clean_str) + if numbers: + # 如果有多个数字，取平均值 + if len(numbers) >= 2: + return (float(numbers[0]) + float(numbers[1])) / 2 + else: + return float(numbers[0]) + else: + # 默认值 + return 50.0 + def get_monthly_transaction_score(self, monthly_amount: float) -> float: """ 根据用户月交易额区间匹配评分。 diff --git a/app/utils/calculation_engine/economic_value_b1/sub_formulas/traffic_factor_b12.py b/app/utils/calculation_engine/economic_value_b1/sub_formulas/traffic_factor_b12.py index 7fe04b0..21be98d 100644 --- a/app/utils/calculation_engine/economic_value_b1/sub_formulas/traffic_factor_b12.py +++ b/app/utils/calculation_engine/economic_value_b1/sub_formulas/traffic_factor_b12.py @@ -28,10 +28,10 @@ class TrafficFactorB12Calculator: float: 流量因子B12 """ # 避免除零和对数计算错误 - if industry_average_s2 <= 0: + if industry_average_s2 == 0: raise ValueError("行业均值S2必须大于0") - if search_index_s1 <= 0: + if search_index_s1 == 0: # 如果搜索指数为0或负数，使用最小值避免对数计算错误 search_index_s1 = 1.0 diff --git a/app/utils/calculation_engine/market_value_c/sub_formulas/temporal_decay_c4.py b/app/utils/calculation_engine/market_value_c/sub_formulas/temporal_decay_c4.py index d8cbb3d..8fdb7c7 100644 --- a/app/utils/calculation_engine/market_value_c/sub_formulas/temporal_decay_c4.py +++ b/app/utils/calculation_engine/market_value_c/sub_formulas/temporal_decay_c4.py @@ -45,6 +45,11 @@ class TemporalDecayC4Calculator: # 处理输入日期 if isinstance(target_date, str): + # 如果是数字字符串"0"或空字符串，使用默认日期 + if target_date == "0" or target_date.strip() == "": + # 默认为一年前，返回"其他" + return "其他" + # 尝试不同的日期格式 formats = ['%Y-%m-%d', '%Y/%m/%d', '%Y%m%d'] date_obj = None @@ -55,9 +60,15 @@ class TemporalDecayC4Calculator: except ValueError: continue if date_obj is None: - raise ValueError(f"无法解析日期: {target_date}") + # 如果无法解析日期，记录警告并返回默认值 + print(f"警告: 无法解析日期 '{target_date}'，使用默认值'其他'") + return "其他" elif isinstance(target_date, datetime): date_obj = target_date.date() + elif isinstance(target_date, (int, float)): + # 如果传入的是数字（如0），使用默认值 + print(f"警告: 传入的日期参数是数字 {target_date}，使用默认值'其他'") + return "其他" else: date_obj = target_date diff --git a/app/utils/industry_calculator.py b/app/utils/industry_calculator.py new file mode 100644 index 0000000..317dbb9 --- /dev/null +++ b/app/utils/industry_calculator.py @@ -0,0 +1,100 @@ +""" +行业数据查询和计算工具 +""" +import logging +from typing import Optional, Dict, Any +from app.models.industry import Industry + +logger = logging.getLogger(__name__) + + +async def get_industry_data_by_name(industry_name: str) -> Optional[Dict[str, Any]]: + """ + 根据行业名称查询行业数据 + + Args: + industry_name: 行业名称 + + Returns: + 包含行业数据的字典，如果未找到则返回None + { + 'code': '行业代码', + 'name': '行业名称', + 'roe': 平均ROE, + 'fix_num': 行业修正系数, + 'remark': '备注' + } + """ + try: + industry = await Industry.filter(name=industry_name).first() + if industry: + return { + 'code': industry.code, + 'name': industry.name, + 'roe': industry.roe, + 'fix_num': industry.fix_num, + 'remark': industry.remark + } + else: + logger.warning(f"未找到行业数据: {industry_name}") + return None + except Exception as e: + logger.error(f"查询行业数据失败: {industry_name}, 错误: {str(e)}") + return None + + +async def calculate_industry_average_s2(industry_name: str) -> float: + """ + 计算行业均值S2 + + Args: + industry_name: 行业名称 + + Returns: + 行业均值S2，如果查询失败则返回0.0 + """ + try: + industry_data = await get_industry_data_by_name(industry_name) + if industry_data: + # S2 = ROE * 修正系数 + roe = industry_data.get('roe', 0.0) + fix_num = industry_data.get('fix_num', 0.0) + s2_value = roe * fix_num + + # 确保S2值为正数，避免对数计算错误 + if s2_value <= 0: + logger.warning(f"行业 {industry_name} S2计算值为负数或零: ROE={roe}, 修正系数={fix_num}, S2={s2_value}，使用默认值0.01") + s2_value = 0.01 # 使用小的正数避免对数计算错误 + + logger.info(f"行业 {industry_name} S2计算: ROE={roe}, 修正系数={fix_num}, S2={s2_value}") + return s2_value + else: + logger.warning(f"未找到行业 {industry_name} 的数据，返回默认值0.01") + return 0.01 # 返回小的正数而不是0.0 + except Exception as e: + logger.error(f"计算行业均值S2失败: {industry_name}, 错误: {str(e)}") + return 0.01 # 返回小的正数而不是0.0 + + +async def get_all_industries() -> list: + """ + 获取所有行业列表 + + Returns: + 行业列表 + """ + try: + industries = await Industry.all() + return [ + { + 'code': industry.code, + 'name': industry.name, + 'roe': industry.roe, + 'fix_num': industry.fix_num, + 'remark': industry.remark + } + for industry in industries + ] + except Exception as e: + logger.error(f"获取行业列表失败: {str(e)}") + return [] \ No newline at end of file diff --git a/app/utils/universal_api_manager.py b/app/utils/universal_api_manager.py index 3286f03..8e8b03d 100644 --- a/app/utils/universal_api_manager.py +++ b/app/utils/universal_api_manager.py @@ -237,11 +237,12 @@ class UniversalAPIManager: prepared_params['token'] = api_key elif provider == 'dajiala': - # 微信指数 - # JustOneAPI需要token参数 - api_key = provider_config.get('api_key') - if api_key: - prepared_params['key'] = api_key + # 微信指数/极致聊接口需要 key 参数 + endpoint_config = self._get_endpoint_config(provider, endpoint) + if endpoint_config: + api_key = endpoint_config.get('api_key') + if api_key: + prepared_params['key'] = api_key elif provider == 'jizhiliao': # 极致聊接口需要 key，默认从配置读取 @@ -325,6 +326,9 @@ class UniversalAPIManager: } response = self.session.post(url, json=prepared_params, headers=headers, timeout=timeout) + elif provider == 'dajiala': + # dajiala是微信指数/极致聊接口，使用普通POST请求 + response = self.session.post(url, json=prepared_params, timeout=timeout) else: response = self.session.post(url, json=prepared_params, timeout=timeout) else: @@ -365,6 +369,7 @@ class UniversalAPIManager: "sub_search_type": 0, "verifycode": "" } + return self.make_request('dajiala', 'web_search', data) def video_views(self,platform_type,video_id): diff --git a/app/utils/wechat_index_calculator.py b/app/utils/wechat_index_calculator.py new file mode 100644 index 0000000..5941876 --- /dev/null +++ b/app/utils/wechat_index_calculator.py @@ -0,0 +1,131 @@ +""" +微信指数计算工具 +用于处理微信指数API返回的数据并计算平均值 +""" + +from typing import Dict, Any, Optional, List +import logging + +logger = logging.getLogger(__name__) + + +class WeChatIndexCalculator: + """微信指数计算器""" + + @staticmethod + def extract_index_data(api_response: Dict[str, Any]) -> List[Dict[str, Any]]: + """ + 从微信指数API响应中提取指数数据 + + Args: + api_response: 微信指数API的响应数据 + + Returns: + 包含指数和时间戳的数据列表 + """ + try: + # 检查响应状态 + if api_response.get('code') != 0: + logger.error(f"微信指数API返回错误: {api_response}") + return [] + + # 提取数据路径: data[0].items[0].itemInfo.data + data_list = api_response.get('data', []) + if not data_list: + logger.warning("微信指数响应中没有数据") + return [] + + first_data = data_list[0] + items = first_data.get('items', []) + if not items: + logger.warning("微信指数响应中没有items数据") + return [] + + first_item = items[0] + item_info = first_item.get('itemInfo', {}) + index_data = item_info.get('data', []) + + if not index_data: + logger.warning("微信指数响应中没有指数数据") + return [] + + logger.info(f"成功提取到 {len(index_data)} 条微信指数数据") + return index_data + + except Exception as e: + logger.error(f"提取微信指数数据时发生错误: {e}") + return [] + + @staticmethod + def calculate_30_day_average(index_data: List[Dict[str, Any]]) -> float: + """ + 计算近30天微信指数平均值 + + Args: + index_data: 包含指数和时间戳的数据列表 + + Returns: + 近30天的平均指数值 + """ + try: + if not index_data: + logger.warning("没有指数数据用于计算平均值") + return 0.0 + + # 取最近30条数据（如果数据不足30条，则使用所有数据） + recent_data = index_data[-30:] if len(index_data) >= 30 else index_data + + # 提取指数值并转换为数字 + index_values = [] + for item in recent_data: + try: + index_str = item.get('index', '0') + index_value = float(index_str) if index_str else 0.0 + index_values.append(index_value) + except (ValueError, TypeError) as e: + logger.warning(f"无法转换指数值 '{item.get('index')}': {e}") + index_values.append(0.0) + + if not index_values: + logger.warning("没有有效的指数值用于计算") + return 0.0 + + # 计算平均值 + total_sum = sum(index_values) + count = len(index_values) + average = total_sum / count + + logger.info(f"计算微信指数平均值: {count}天数据，总和={total_sum}，平均值={average:.2f}") + return round(average, 2) + + except Exception as e: + logger.error(f"计算微信指数平均值时发生错误: {e}") + return 0.0 + + @classmethod + def process_wechat_index_response(cls, api_response: Dict[str, Any]) -> float: + """ + 处理微信指数API响应，返回近30天平均值 + + Args: + api_response: 微信指数API的完整响应 + + Returns: + 近30天微信指数平均值 + """ + try: + # 提取指数数据 + index_data = cls.extract_index_data(api_response) + + # 计算平均值 + average_index = cls.calculate_30_day_average(index_data) + + return average_index + + except Exception as e: + logger.error(f"处理微信指数响应时发生错误: {e}") + return 0.0 + + +# 创建全局实例 +wechat_index_calculator = WeChatIndexCalculator() \ No newline at end of file