项目结构# encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:09 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : settings.py 业务全局配置统一管理阈值、权重避免代码硬编码 # 钻石综合评分权重 DIAMOND_WEIGHT_CARAT 0.5 DIAMOND_WEIGHT_COLOR 0.3 DIAMOND_WEIGHT_CLARITY 0.2 # 定价迭代默认步长 PRICE_ITER_STEP 0.01 # 加价区间默认边界 MIN_MARKUP_COEFF 1.3 MAX_MARKUP_COEFF 2.2 # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:10 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : diamond.py from dataclasses import dataclass dataclass(frozenFalse) class Diamond: 钻石裸石领域模型 stone_id: str carat: float color: str clarity: str cost_price: float # 成本价 def calc_comprehensive_score(self) - float: 计算钻石综合品级分数 :return: from Iterative.config.settings import DIAMOND_WEIGHT_CARAT, DIAMOND_WEIGHT_COLOR, DIAMOND_WEIGHT_CLARITY color_map {D: 100, E:96, F:92, G:88, H:84, I:78} clarity_map {FL:100, VVS1:95, VVS2:90, VS1:85, VS2:80, SI1:70} c_score self.carat * 100 col_score color_map.get(self.color, 60) cla_score clarity_map.get(self.clarity, 60) total (c_score * DIAMOND_WEIGHT_CARAT col_score * DIAMOND_WEIGHT_COLOR cla_score * DIAMOND_WEIGHT_CLARITY) return round(total, 2) # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:12 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : ring_mount.py from dataclasses import dataclass dataclass class RingMount: 戒托模型 mount_id: str material: str # 18K, 铂金 cost_price: float # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:13 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : jade_blank.py from dataclasses import dataclass dataclass class JadeBlank: 翡翠毛料实体 blank_id: str length: float width: float thick: float cost_price: float usable_rate: float # 成品利用率 # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:14 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : request.py from dataclasses import dataclass dataclass class DiamondRecommendRequest: 钻戒推荐入参 budget: float material: str dataclass class JadeMatchRequest: 翡翠定制匹配入参 min_l: float max_l: float min_w: float max_w: float min_t: float max_t: float price_min: float price_max: float dataclass class PriceOptRequest: 定价演算入参 base_cost: float min_coeff: float max_coeff: float step: float # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:14 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : response.py from dataclasses import dataclass from Iterative.models.diamond import Diamond from Iterative.models.ring_mount import RingMount from Iterative.models.jade_blank import JadeBlank dataclass class DiamondComboResult: diamond: Diamond mount: RingMount total_cost: float score: float dataclass class JadeMatchResult: blank: JadeBlank dataclass class PriceOptResult: best_coeff: float best_sell_price: float max_gross_profit: float # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:35 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : iterative_matcher.py from typing import Callable, Optional, TypeVar T TypeVar(T) class IterativeMatcher: 通用迭代匹配器迭代遍历候选集筛选并保留最优对象 staticmethod def find_optimal( candidates: list[T], filter_func: Callable[[T], bool], score_func: Callable[[T], float] ) - Optional[T]: :param candidates: :param filter_func: :param score_func: :return: best_item: Optional[T] None best_value -1.0 for item in candidates: if not filter_func(item): continue current_score score_func(item) if current_score best_value: best_value current_score best_item item return best_item # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:36 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : iterative_optimizer.py from typing import Callable, Tuple class IterativeOptimizer: 连续数值区间迭代寻优通用组件 staticmethod def optimize( start: float, end: float, step: float, eval_func: Callable[[float], float] ) - Tuple[float, float]: :return: (最优参数, 最大目标值) best_param start max_target -float(inf) current start while current end: value eval_func(current) if value max_target: max_target value best_param current current step return round(best_param, 2), round(max_target, 2) # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:36 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : base_repo.py from abc import ABC, abstractmethod from typing import List, TypeVar T TypeVar(T) class BaseRepository(ABC): abstractmethod def list_all(self) - List[T]: pass # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:37 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : diamond_repo.py from Iterative.repository.base_repo import BaseRepository from Iterative.models.diamond import Diamond from typing import List class DiamondRepository(BaseRepository): def __init__(self): # 模拟数据库生产环境替换为SQL查询 self._storage: List[Diamond] [ Diamond(D001, 0.52, H, VS1, 24800), Diamond(D002, 0.48, G, VS2, 22100), Diamond(D003, 0.55, I, SI1, 21300), ] def list_all(self) - List[Diamond]: return self._storage.copy() # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:38 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : ring_mount_repo.py from Iterative.repository.base_repo import BaseRepository from Iterative.models.ring_mount import RingMount from typing import List class RingMountRepository(BaseRepository): def __init__(self): self._storage: List[RingMount] [ RingMount(M001, 18K, 4200), RingMount(M002, 铂金, 5600), ] def list_all(self) - List[RingMount]: return self._storage.copy() # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:39 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : jade_repo.py from Iterative.repository.base_repo import BaseRepository from Iterative.models.jade_blank import JadeBlank from typing import List class JadeRepository(BaseRepository): def __init__(self): self._storage: List[JadeBlank] [ JadeBlank(J001, 32.5, 21.2, 7.3, 6800, 0.86), JadeBlank(J002, 30.1, 19.8, 6.9, 6200, 0.91), JadeBlank(J003, 36.0, 24.1, 8.2, 7500, 0.79), ] def list_all(self) - List[JadeBlank]: return self._storage.copy() # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:40 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : recommend_service.py from typing import Optional from Iterative.models.diamond import Diamond from Iterative.models.ring_mount import RingMount from Iterative.repository.diamond_repo import DiamondRepository from Iterative.repository.ring_mount_repo import RingMountRepository from Iterative.schemas.request import DiamondRecommendRequest from Iterative.schemas.response import DiamondComboResult class DiamondRecommendService: 钻戒组合推荐服务 def __init__( self, diamond_repo: DiamondRepository, mount_repo: RingMountRepository ): self.diamond_repo diamond_repo self.mount_repo mount_repo def find_best_combo(self, req: DiamondRecommendRequest) - Optional[DiamondComboResult]: :param req: :return: diamonds self.diamond_repo.list_all() mounts self.mount_repo.list_all() best_result: Optional[DiamondComboResult] None best_score -1.0 # 业务迭代逻辑 for dia in diamonds: for mount in mounts: if mount.material ! req.material: continue total dia.cost_price mount.cost_price if total req.budget: continue score dia.calc_comprehensive_score() if score best_score: best_score score best_result DiamondComboResult( diamonddia, mountmount, total_costtotal, scorescore ) return best_result # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:41 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : jade_custom_service.py from typing import Optional from Iterative.repository.jade_repo import JadeRepository from Iterative.schemas.request import JadeMatchRequest from Iterative.schemas.response import JadeMatchResult from Iterative.models.jade_blank import JadeBlank from Iterative.algorithms.iterative_matcher import IterativeMatcher class JadeCustomService: 翡翠毛料匹配服务 def __init__(self, jade_repo: JadeRepository): self.jade_repo jade_repo def match_optimal_blank(self, req: JadeMatchRequest) - Optional[JadeMatchResult]: :param req: :return: blanks self.jade_repo.list_all() def filter_rule(item: JadeBlank) - bool: cond_size (req.min_l item.length req.max_l and req.min_w item.width req.max_w and req.min_t item.thick req.max_t) cond_price req.price_min item.cost_price req.price_max return cond_size and cond_price def score_rule(item: JadeBlank) - float: return item.usable_rate best IterativeMatcher.find_optimal(blanks, filter_rule, score_rule) if not best: return None return JadeMatchResult(blankbest) # encoding: utf-8 # 版权所有 2026 ©涂聚文有限公司™ ® # 许可信息查看言語成了邀功盡責的功臣還需要行爲每日來值班嗎 # 描述Iterative Algorithms # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2024.3.6 python 3.11 # os : windows 10 # database : mysql 9.0 sql server 2019, postgreSQL 17.0 Oracle 21c Neo4j # Datetime : 2026/7/24 22:42 # User : geovindu # Product : PyCharm # Project : PyAlgorithms # File : pricing_service.py from Iterative.schemas.request import PriceOptRequest from Iterative.schemas.response import PriceOptResult from Iterative.algorithms.iterative_optimizer import IterativeOptimizer class ProductPricingService: 动态定价演算服务 def calc_optimal_price(self, req: PriceOptRequest) - PriceOptResult: :param req: :return: base_cost req.base_cost def profit_evaluator(coeff: float) - float: sell_price base_cost * coeff volume max(0, round(120 - sell_price / 45)) profit (sell_price - base_cost) * volume return profit best_coeff, max_profit IterativeOptimizer.optimize( startreq.min_coeff, endreq.max_coeff, stepreq.step, eval_funcprofit_evaluator ) best_price round(base_cost * best_coeff, 2) return PriceOptResult( best_coeffbest_coeff, best_sell_pricebest_price, max_gross_profitmax_profit )输出