diff --git a/app/api/v1/calculation/calcuation.py b/app/api/v1/calculation/calcuation.py index 7d5d289..bd665e1 100644 --- a/app/api/v1/calculation/calcuation.py +++ b/app/api/v1/calculation/calcuation.py @@ -23,7 +23,7 @@ from app.utils.calculation_engine.risk_adjustment_b3 import RiskAdjustmentB3Calc from app.models.esg import ESG from app.models.industry import Industry from app.models.policy import Policy - +from app.utils.universal_api_manager import universal_api app_valuations_router = APIRouter(tags=["用户端估值评估"]) @@ -66,10 +66,33 @@ async def calculate_valuation( # 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") + # 解析专利数量 + patentData = patent_data.get("data", {"dataList":[]}) + patent_data_num = len(patentData["dataList"]) + + # 查询专利是否存在 + patent_data_al = list(filter(lambda x: x.get("SQH") == data.patent_application_no, patentData)) + if len(patent_data_al) > 0: + # 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 + patent_count = calculate_patent_usage_score(len(patent_data_al)) + input_data_by_b1["patent_count"] = patent_count + else: + input_data_by_b1["patent_count"] = 0 + except Exception as e: + input_data_by_b1["patent_count"] = 0 + # 提取 文化价值B2 计算参数 input_data_by_b2 = _extract_calculation_params_b2(data) # 提取 风险调整系数B3 计算参数 input_data_by_b3 = _extract_calculation_params_b3(data) + # 提取 市场估值C 参数 + input_data_by_c = _extract_calculation_params_c(data) # 调用 经济价值B1 计算引擎 calculation_result_by_b1 = calculator_by_b1.calculate_complete_economic_value_b1(input_data_by_b1) @@ -111,19 +134,11 @@ def _extract_calculation_params_b1(data: UserValuationCreate) -> Dict[str, Any]: # 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) - # TODO 专利剩余年限【专利证书】 需要使用第三方API - patent = data.patent_application_no - patent_score = 0 + # 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() + infringement_score = calculate_infringement_score("无侵权信息") infringement_score = 0 - - # 发展潜力D相关参数 - # 专利使用量 TODO 需要使用第三方API - patent_score = calculate_patent_usage_score(0) - - # 创新投入比 = (研发费用/营收) * 100 try: rd_investment = float(data.rd_investment or 0) @@ -132,10 +147,13 @@ def _extract_calculation_params_b1(data: UserValuationCreate) -> Dict[str, Any]: 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 - search_index_s1 = calculate_search_index_s1() # 默认值，实际应从API获取 + baidu_index = "暂无" + wechat_index = universal_api.wx_index(data.asset_name) # 通过资产信息获取微信指数 TODO 这里返回的没确认指数参数，有可能返回的图示是指数信息 + weibo_index = "暂无" + 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 TODO 系统内置 未找到相关内容 industry_average_s2 = 0.0 # 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 @@ -156,7 +174,6 @@ def _extract_calculation_params_b1(data: UserValuationCreate) -> Dict[str, Any]: return { # 基础价值B11相关参数 'three_year_income': three_year_income, - 'patent_score': patent_score, 'popularity_score': popularity_score, 'infringement_score': infringement_score, 'innovation_ratio': innovation_ratio, @@ -227,3 +244,13 @@ def _extract_calculation_params_b3(data: UserValuationCreate) -> Dict[str, Any]: "lawsuit_status": lawsuit_status, "inheritor_ages": inheritor_ages, } + + +# 获取 市场估值C 相关参数 +def _extract_calculation_params_c(data: UserValuationCreate) -> Dict[str, Any]: + + # 稀缺性乘数C3 发行量 + circulation = data.circulation\ + + # 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 + last_market_activity = data.last_market_activity diff --git a/app/utils/api_config.py b/app/utils/api_config.py index 987adfb..3fabdd2 100644 --- a/app/utils/api_config.py +++ b/app/utils/api_config.py @@ -60,7 +60,7 @@ class APIConfig: "base_url": "https://api.justoneapi.com", "timeout": 30, "retries": 3, - "endpoints": { + "endpoints": { "xiaohongshu_note_detail": { "path": "/api/xiaohongshu/get-note-detail/v7", "method": "GET", @@ -84,8 +84,25 @@ class APIConfig: } } }, + # 微信指数 + "dajiala": { + "api_key": "", + "base_url": "https://www.dajiala.com", + "timeout": 30, + "retries": 3, + "endpoints": { + "web_search":{ + "path": "/fbmain/monitor/v3/web_search", + "method": "POST", + "description": "获取微信指数", + "required_params": ["keyword","key"], + "optional_params": [] + } + } + }, "other_apis": { # 可以添加其他第三方API配置 + "example_api": { "api_key": os.getenv("EXAMPLE_API_KEY", ""), "base_url": "https://api.example.com", diff --git a/app/utils/calculation_engine/economic_value_b1/economic_value_b1.py b/app/utils/calculation_engine/economic_value_b1/economic_value_b1.py index 3cce041..58ccc81 100644 --- a/app/utils/calculation_engine/economic_value_b1/economic_value_b1.py +++ b/app/utils/calculation_engine/economic_value_b1/economic_value_b1.py @@ -72,12 +72,12 @@ class EconomicValueB1Calculator: input_data["infringement_score"], ) - # 发展潜力 patent_score: 专利分 (0-10分) (用户填写) + # 发展潜力 patent_count: 专利分 (0-10分) (用户填写) # esg_score: ESG分 (0-10分) (用户填写) # innovation_ratio: 创新投入比 (研发费用/营收) * 100 (用户填写) development_potential = self.basic_value_calculator.calculate_development_potential_d( input_data["esg_score"], - input_data["patent_score"], + input_data["patent_count"], input_data["innovation_ratio"], ) # 计算行业系数I target_industry_roe: 目标行业平均ROE (系统配置) diff --git a/app/utils/calculation_engine/market_value_c/__init__.py b/app/utils/calculation_engine/market_value_c/__init__.py new file mode 100644 index 0000000..2f78925 --- /dev/null +++ b/app/utils/calculation_engine/market_value_c/__init__.py @@ -0,0 +1,16 @@ +from .market_value_c import MarketValueCCalculator +from .sub_formulas import ( + MarketBiddingC1Calculator, + HeatCoefficientC2Calculator, + ScarcityMultiplierC3Calculator, + TemporalDecayC4Calculator +) + +__all__ = [ + "MarketValueCCalculator", + "MarketBiddingC1Calculator", + "HeatCoefficientC2Calculator", + "ScarcityMultiplierC3Calculator", + "TemporalDecayC4Calculator" +] + diff --git a/app/utils/calculation_engine/market_value_c/market_value_c.py b/app/utils/calculation_engine/market_value_c/market_value_c.py new file mode 100644 index 0000000..2cc5b43 --- /dev/null +++ b/app/utils/calculation_engine/market_value_c/market_value_c.py @@ -0,0 +1,145 @@ +from typing import Dict, List, Optional +try: + # 相对导入（当作为包使用时） + from .sub_formulas.market_bidding_c1 import MarketBiddingC1Calculator + from .sub_formulas.heat_coefficient_c2 import HeatCoefficientC2Calculator + from .sub_formulas.scarcity_multiplier_c3 import ScarcityMultiplierC3Calculator + from .sub_formulas.temporal_decay_c4 import TemporalDecayC4Calculator +except ImportError: + # 绝对导入（当直接运行时） + from sub_formulas.market_bidding_c1 import MarketBiddingC1Calculator + from sub_formulas.heat_coefficient_c2 import HeatCoefficientC2Calculator + from sub_formulas.scarcity_multiplier_c3 import ScarcityMultiplierC3Calculator + from sub_formulas.temporal_decay_c4 import TemporalDecayC4Calculator + + +class MarketValueCCalculator: + """市场估值C计算器""" + + def __init__(self): + """初始化计算器""" + self.market_bidding_calculator = MarketBiddingC1Calculator() + self.heat_coefficient_calculator = HeatCoefficientC2Calculator() + self.scarcity_multiplier_calculator = ScarcityMultiplierC3Calculator() + self.temporal_decay_calculator = TemporalDecayC4Calculator() + + def calculate_market_value_c(self, + market_bidding_c1: float, + heat_coefficient_c2: float, + scarcity_multiplier_c3: float, + temporal_decay_c4: float) -> float: + """ + 计算市场估值C + + + 市场估值C = 市场竞价C1 × 热度系数C2 × 稀缺性乘数C3 × 时效性衰减C4 + + args: + market_bidding_c1: 市场竞价C1 (系统计算) + heat_coefficient_c2: 热度系数C2 (系统计算) + scarcity_multiplier_c3: 稀缺性乘数C3 (系统计算) + temporal_decay_c4: 时效性衰减C4 (系统计算) + + return: + float: 市场估值C + """ + market_value = (market_bidding_c1 * heat_coefficient_c2 * + scarcity_multiplier_c3 * temporal_decay_c4) + + return market_value + + def calculate_complete_market_value_c(self, input_data: Dict) -> Dict: + """ + 计算完整的市场估值C，包含所有子公式 + + args: + input_data: 输入数据字典，包含所有必要的参数 + 参数来源标记（用户填写/系统配置/API获取/系统计算）： + - average_transaction_price: 系统计算(基于用户填写/API获取) + - market_activity_coefficient: 系统计算(基于用户填写) + - daily_browse_volume: API获取/系统估算 + - collection_count: API获取/系统估算 + - issuance_level: 用户填写 + - recent_market_activity: 用户填写 + - issuance_scarcity/circulation_scarcity/uniqueness_scarcity: 系统配置/系统计算（保留向后兼容） + + return: + Dict: 包含所有中间计算结果和最终结果的字典 + """ + # 计算市场竞价C1 + market_bidding_c1 = self.market_bidding_calculator.calculate_market_bidding_c1( + transaction_data={'weighted_average_price': input_data.get('average_transaction_price', 50000.0)}, + manual_bids=[input_data.get('average_transaction_price', 50000.0)], + expert_valuations=[input_data.get('average_transaction_price', 50000.0)] + ) + + # 计算热度系数C2 + heat_coefficient_c2 = self.heat_coefficient_calculator.calculate_heat_coefficient_c2( + input_data.get('daily_browse_volume', 500.0), + input_data.get('collection_count', 50) + ) + + # 计算稀缺性乘数C3 + scarcity_multiplier_c3 = self.scarcity_multiplier_calculator.calculate_scarcity_multiplier_c3( + input_data.get('issuance_level', '限量发行') + ) + + # 计算时效性衰减C4 + temporal_decay_c4 = self.temporal_decay_calculator.calculate_temporal_decay_c4( + input_data.get('recent_market_activity', '近一月') + ) + + # 计算市场估值C + market_value_c = self.calculate_market_value_c( + market_bidding_c1, + heat_coefficient_c2, + scarcity_multiplier_c3, + temporal_decay_c4 + ) + + return { + 'market_bidding_c1': market_bidding_c1, + 'heat_coefficient_c2': heat_coefficient_c2, + 'scarcity_multiplier_c3': scarcity_multiplier_c3, + 'temporal_decay_c4': temporal_decay_c4, + 'market_value_c': market_value_c + } + + +# 示例使用 +if __name__ == "__main__": + # 创建计算器实例 + calculator = MarketValueCCalculator() + + # 示例数据 + input_data = { + # 市场竞价C1相关参数 + 'average_transaction_price': 50000.0, # 平均交易价格 + 'market_activity_coefficient': 0.8, # 市场活跃度系数 + + # 热度系数C2相关参数 + 'search_heat': 0.7, # 搜索热度 + 'social_media_heat': 0.6, # 社交媒体热度 + 'media_coverage_heat': 0.5, # 媒体报道热度 + + # 稀缺性乘数C3相关参数 + 'issuance_scarcity': 0.8, # 发行量稀缺性 + 'circulation_scarcity': 0.7, # 流通率稀缺性 + 'uniqueness_scarcity': 0.9, # 独特性稀缺性 + + # 时效性衰减C4相关参数 + 'time_decay_coefficient': 0.3, # 时间衰减系数 + 'market_activity_decay': 0.2 # 市场活跃度衰减 + } + + # 计算市场估值C + result = calculator.calculate_complete_market_value_c(input_data) + + print("市场估值C计算结果:") + print(f"市场竞价C1: {result['market_bidding_c1']:.2f}") + print(f"热度系数C2: {result['heat_coefficient_c2']:.4f}") + print(f"稀缺性乘数C3: {result['scarcity_multiplier_c3']:.4f}") + print(f"时效性衰减C4: {result['temporal_decay_c4']:.4f}") + print(f"市场估值C: {result['market_value_c']:.2f}") + + diff --git a/app/utils/calculation_engine/market_value_c/sub_formulas/__init__.py b/app/utils/calculation_engine/market_value_c/sub_formulas/__init__.py new file mode 100644 index 0000000..4ea27e3 --- /dev/null +++ b/app/utils/calculation_engine/market_value_c/sub_formulas/__init__.py @@ -0,0 +1,13 @@ +from .market_bidding_c1 import MarketBiddingC1Calculator +from .heat_coefficient_c2 import HeatCoefficientC2Calculator +from .scarcity_multiplier_c3 import ScarcityMultiplierC3Calculator +from .temporal_decay_c4 import TemporalDecayC4Calculator + +__all__ = [ + "MarketBiddingC1Calculator", + "HeatCoefficientC2Calculator", + "ScarcityMultiplierC3Calculator", + "TemporalDecayC4Calculator" +] + + diff --git a/app/utils/calculation_engine/market_value_c/sub_formulas/heat_coefficient_c2.py b/app/utils/calculation_engine/market_value_c/sub_formulas/heat_coefficient_c2.py new file mode 100644 index 0000000..6adef1d --- /dev/null +++ b/app/utils/calculation_engine/market_value_c/sub_formulas/heat_coefficient_c2.py @@ -0,0 +1,87 @@ +class HeatCoefficientC2Calculator: + """热度系数C2计算器""" + + def __init__(self): + """初始化计算器""" + pass + + def calculate_heat_coefficient_c2(self, + daily_browse_volume: float, + collection_count: int) -> float: + """ + 计算热度系数C2 + + + 热度系数C2 = 1 + 浏览热度分 + + args: + daily_browse_volume: 近7日日均浏览量 (API获取) + collection_count: 收藏数 (API获取) + + return: + float: 热度系数C2 + """ + # 计算浏览热度分 + browse_heat_score = self.calculate_browse_heat_score(daily_browse_volume, collection_count) + + + heat_coefficient = 1 + browse_heat_score + + return heat_coefficient + + def calculate_browse_heat_score(self, daily_browse_volume: float, collection_count: int) -> float: + """ + 计算浏览热度分 + + 根据所查询到的浏览量匹配热度分： + 高热度 近7日日均浏览量 > 1000，或收藏数 > 100 1.0 + 中热度 近7日日均浏览量 ∈ [100, 1000]，或收藏数 ∈ [20, 100] 0.6 + 低热度 近7日日均浏览量 < 100，且收藏数 < 20 0.2 + 无数据 无任何浏览与互动数据 0.0（默认值） + + + args: + daily_browse_volume: 近7日日均浏览量 (API获取) + collection_count: 收藏数 (API获取) + + return: + float: 浏览热度分 + """ + # 高热度条件 + if daily_browse_volume > 1000 or collection_count > 100: + return 1.0 + + # 中热度条件 + elif (daily_browse_volume >= 100 and daily_browse_volume <= 1000) or \ + (collection_count >= 20 and collection_count <= 100): + return 0.6 + + # 低热度条件 + elif daily_browse_volume < 100 and collection_count < 20: + return 0.2 + + # 无数据 + else: + return 0.0 + + + +# 示例使用 +if __name__ == "__main__": + # 创建计算器实例 + calculator = HeatCoefficientC2Calculator() + + + # 示例数据 + daily_browse_volume = 500.0 # 近7日日均浏览量 (API获取) + collection_count = 50 # 收藏数 (API获取) + + # 计算热度系数C2 + heat_coefficient_c2 = calculator.calculate_heat_coefficient_c2( + daily_browse_volume, collection_count + ) + + print(f"近7日日均浏览量: {daily_browse_volume}") + print(f"收藏数: {collection_count}") + print(f"浏览热度分: {calculator.calculate_browse_heat_score(daily_browse_volume, collection_count):.1f}") + print(f"热度系数C2: {heat_coefficient_c2:.4f}") diff --git a/app/utils/calculation_engine/market_value_c/sub_formulas/market_bidding_c1.py b/app/utils/calculation_engine/market_value_c/sub_formulas/market_bidding_c1.py new file mode 100644 index 0000000..0a5f447 --- /dev/null +++ b/app/utils/calculation_engine/market_value_c/sub_formulas/market_bidding_c1.py @@ -0,0 +1,92 @@ + +from typing import Dict, List + + + +class MarketBiddingC1Calculator: + """市场竞价C1计算器""" + + def __init__(self): + """初始化计算器""" + pass + + def calculate_market_bidding_c1(self, + transaction_data: Dict = None, + manual_bids: List[float] = None, + expert_valuations: List[float] = None) -> float: + """ + 计算市场竞价C1 + 1)取同一资产或同品类、同等级资产最近3个月内成功交易的加权平均价格。 + 2)人工采集主流文化产权交易所、拍卖平台（如阿里拍卖、京东拍卖）上相似资产的当前报价或起拍价，取其中位数。 + 3)若以上数据均缺失，由系统内置专家库中随机指派3位专家独立给出估值，取平均值。 + + + args: + 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) + + retusn: + float: 市场竞价C1 + """ + # 优先级1：近3个月交易数据 + if transaction_data and transaction_data.get('weighted_average_price'): + return transaction_data['weighted_average_price'] + + # 优先级2：手动收集的竞价数据 + if manual_bids and len(manual_bids) > 0: + # 取中位数 + sorted_bids = sorted(manual_bids) + n = len(sorted_bids) + if n % 2 == 0: + return (sorted_bids[n//2-1] + sorted_bids[n//2]) / 2 + else: + return sorted_bids[n//2] + + # 优先级3：专家估值 + if expert_valuations and len(expert_valuations) > 0: + return sum(expert_valuations) / len(expert_valuations) + + # 默认值 + return 0.0 + +# 示例使用 +if __name__ == "__main__": + # 创建计算器实例 + calculator = MarketBiddingC1Calculator() + + # 示例数据 + asset_type = "传统工艺" # 资产类型 (用户填写) + time_period = "近一年" # 时间周期 (用户填写) + transaction_volume = 500 # 交易量 (API获取) + transaction_frequency = "中频" # 交易频率 (用户填写) + market_liquidity = "中" # 市场流动性 (用户填写) + + # 获取平均交易价格 + average_transaction_price = calculator.get_average_transaction_price(asset_type, time_period) + + # 计算市场活跃度系数 + market_activity_coefficient = calculator.calculate_market_activity_coefficient( + transaction_volume, transaction_frequency, market_liquidity + ) + + # 示例数据 + # 优先级1：近3个月交易数据 + transaction_data = {"weighted_average_price": 1000.0} # API获取 + + # 优先级2：手动收集的竞价数据 + manual_bids = [950.0, 1000.0, 1050.0, 1100.0] # 用户填写 + + # 优先级3：专家估值 + expert_valuations = [980.0, 1020.0, 990.0] # 系统配置 + + # 计算市场竞价C1 + market_bidding_c1 = calculator.calculate_market_bidding_c1( + transaction_data, manual_bids, expert_valuations + ) + + print(f"近3个月交易数据: {transaction_data}") + print(f"手动收集竞价: {manual_bids}") + print(f"专家估值: {expert_valuations}") + print(f"市场竞价C1: {market_bidding_c1:.2f}") + diff --git a/app/utils/calculation_engine/market_value_c/sub_formulas/scarcity_multiplier_c3.py b/app/utils/calculation_engine/market_value_c/sub_formulas/scarcity_multiplier_c3.py new file mode 100644 index 0000000..fa5ea79 --- /dev/null +++ b/app/utils/calculation_engine/market_value_c/sub_formulas/scarcity_multiplier_c3.py @@ -0,0 +1,71 @@ + +class ScarcityMultiplierC3Calculator: + """稀缺性乘数C3计算器""" + + def __init__(self): + """初始化计算器""" + pass + + def calculate_scarcity_multiplier_c3(self, issuance_level: str) -> float: + """ + 计算稀缺性乘数C3 + + + 稀缺性乘数C3 = 1 + 稀缺等级分 + + args: + issuance_level: 资产发行等级 (用户选择) + + Returns: + float: 稀缺性乘数C3 + """ + # 计算稀缺等级分 + scarcity_level_score = self.calculate_scarcity_level_score(issuance_level) + + + scarcity_multiplier = 1 + scarcity_level_score + + return scarcity_multiplier + + def calculate_scarcity_level_score(self, issuance_level: str) -> float: + """ + 计算稀缺等级分 + + 根据用户所选择的资产发行量匹配稀缺等级： + 孤品 全球唯一，不可复制（如特定版权、唯一实物） 1.0 + 限量 总发行份数 ≤ 100份 0.7 + 稀有 总发行份数 ∈ (100, 1000]份，或二级市场流通率 < 5% 0.4 + 流通 总发行份数 > 1000份，或二级市场流通率 ≥ 5% 0.1 + + + args: + issuance_level: 资产发行等级 (用户选择) + + Returns: + float: 稀缺等级分 + """ + scarcity_scores = { + "孤品": 1.0, + "限量": 0.7, + "稀有": 0.4, + "流通": 0.1 + } + + return scarcity_scores.get(issuance_level, 0.1) + + +# 示例使用 +if __name__ == "__main__": + # 创建计算器实例 + calculator = ScarcityMultiplierC3Calculator() + + # 示例数据 + issuance_level = "限量" # 资产发行等级 (用户选择) + + # 计算稀缺性乘数C3 + scarcity_multiplier_c3 = calculator.calculate_scarcity_multiplier_c3(issuance_level) + + print(f"资产发行等级: {issuance_level}") + print(f"稀缺等级分: {calculator.calculate_scarcity_level_score(issuance_level):.1f}") + print(f"稀缺性乘数C3: {scarcity_multiplier_c3:.4f}") + 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 new file mode 100644 index 0000000..d8cbb3d --- /dev/null +++ b/app/utils/calculation_engine/market_value_c/sub_formulas/temporal_decay_c4.py @@ -0,0 +1,89 @@ +from datetime import datetime, timedelta + +class TemporalDecayC4Calculator: + """时效性衰减C4计算器""" + + def __init__(self): + """初始化计算器""" + pass + + def calculate_temporal_decay_c4(self, time_elapsed: str) -> float: + """ + 计算时效性衰减C4 + + 近一周：1.0 + 近一月：0.7 + 近一年：0.4 + 其他：0.1 + 基于最近一次市场活动（交易、报价、鉴定）距今天数 + + args: + time_elapsed: 距离最近市场活动的时间 (用户选择) + + retuen: + float: 时效性衰减C4 + """ + timeliness_coefficients = { + "近一周": 1.0, + "近一月": 0.7, + "近一年": 0.4, + "其他": 0.1 + } + + return timeliness_coefficients.get(self.classify_date_distance(time_elapsed), 0.1) + @staticmethod + def classify_date_distance(target_date): + """ + 计算日期距离今天是近一周、近一月、近一年还是其他 + + target_date: 目标日期，可以是字符串或datetime对象 + 字符串格式支持：'YYYY-MM-DD', 'YYYY/MM/DD', 'YYYYMMDD' + + """ + # 获取当前日期 + today = datetime.now().date() + + # 处理输入日期 + if isinstance(target_date, str): + # 尝试不同的日期格式 + formats = ['%Y-%m-%d', '%Y/%m/%d', '%Y%m%d'] + date_obj = None + for fmt in formats: + try: + date_obj = datetime.strptime(target_date, fmt).date() + break + except ValueError: + continue + if date_obj is None: + raise ValueError(f"无法解析日期: {target_date}") + elif isinstance(target_date, datetime): + date_obj = target_date.date() + else: + date_obj = target_date + + # 计算日期差 + delta = today - date_obj + + # 分类判断 + if delta.days <= 7: + return "近一周" + elif delta.days <= 30: + return "近一月" + elif delta.days <= 365: + return "近一年" + else: + return "其他" +# 示例使用 +if __name__ == "__main__": + # 创建计算器实例 + calculator = TemporalDecayC4Calculator() + + # 示例数据 + time_elapsed = "2024-01-15" # 距离最近市场活动的时间 (用户选择) + + # 计算时效性衰减C4 + temporal_decay_c4 = calculator.calculate_temporal_decay_c4(time_elapsed) + + print(f"距离最近市场活动时间: {time_elapsed}") + print(f"时效性衰减C4: {temporal_decay_c4:.4f}") + diff --git a/app/utils/universal_api_manager.py b/app/utils/universal_api_manager.py index 65a1da7..47067a8 100644 --- a/app/utils/universal_api_manager.py +++ b/app/utils/universal_api_manager.py @@ -152,6 +152,12 @@ class UniversalAPIManager: api_key = provider_config.get('api_key') if api_key: prepared_params['token'] = api_key + + elif provider == 'dajiala': + # JustOneAPI需要token参数 + api_key = provider_config.get('api_key') + if api_key: + prepared_params['key'] = api_key return prepared_params @@ -224,6 +230,20 @@ class UniversalAPIManager: 'endpoint': endpoint } time.sleep(2 ** attempt) # 指数退避 + + def wx_index(self,keyword): + """ + 微信指数 + """ + data = { + "keyword": keyword, + "mode": 2, + "BusinessType": 8192, + "sub_search_type": 0, + "verifycode": "" + } + return self.make_request('dajiala', 'web_search', data) + # 站长之家API的便捷方法 def query_copyright_software(self, company_name: str, chinaz_ver: str = "1") -> Dict[str, Any]: