feat: 完整采集采购尺码候选 (#256)
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@@ -6,9 +6,128 @@
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from __future__ import annotations
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import hashlib
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from abc import ABC, abstractmethod
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from dataclasses import dataclass, field
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from typing import Mapping
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from typing import Mapping, Sequence
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def _hash_frame(value: str) -> str:
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"""按接口契约生成带 UTF-8 字节长度的哈希片段。"""
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return f"{len(value.encode('utf-8'))}:{value}"
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@dataclass(frozen=True)
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class PurchaseSizeObservation:
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"""完整遍历时看到的一条第二规格,包含不可购买项。"""
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raw_text: str
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available: bool
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@dataclass(frozen=True)
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class PurchaseSpecCandidate:
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"""可以交给 Admin 解析的一条可购买尺码候选。"""
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candidate_id: str
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raw_text: str
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options: Mapping[str, str]
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def to_dict(self) -> dict[str, object]:
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return {
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"candidate_id": self.candidate_id,
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"raw_text": self.raw_text,
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"options": dict(self.options),
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}
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@dataclass(frozen=True)
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class PurchaseSpecCandidateSnapshot:
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"""当前商品、已选颜色下,一次完整且稳定的尺码候选观察。"""
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goods_id: str
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selected_color: str
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target_size: str
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dimension_name: str
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observations: tuple[PurchaseSizeObservation, ...]
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candidates: tuple[PurchaseSpecCandidate, ...]
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candidate_snapshot_hash: str
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observed_at: str
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@classmethod
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def build(
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cls,
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*,
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goods_id: str,
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selected_color: str,
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target_size: str,
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dimension_name: str,
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observations: Sequence[PurchaseSizeObservation],
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observed_at: str,
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) -> "PurchaseSpecCandidateSnapshot":
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"""按页面顺序生成候选短编号和 spec-resolution-v1 哈希。"""
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checked_observations = tuple(observations)
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candidates = tuple(
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PurchaseSpecCandidate(
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candidate_id=f"c{index}",
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raw_text=item.raw_text,
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options={"color": selected_color, "size": item.raw_text},
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)
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for index, item in enumerate(
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(item for item in checked_observations if item.available),
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start=1,
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)
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)
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material = "".join(
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(
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_hash_frame("spec-resolution-v1"),
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_hash_frame(goods_id),
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_hash_frame(selected_color),
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_hash_frame(str(len(candidates))),
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*(
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"".join(
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(
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_hash_frame(item.candidate_id),
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_hash_frame(item.raw_text),
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_hash_frame(str(item.options["color"])),
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_hash_frame(str(item.options["size"])),
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)
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)
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for item in candidates
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),
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)
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)
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return cls(
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goods_id=goods_id,
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selected_color=selected_color,
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target_size=target_size,
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dimension_name=dimension_name,
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observations=checked_observations,
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candidates=candidates,
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candidate_snapshot_hash=hashlib.sha256(
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material.encode("utf-8")
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).hexdigest(),
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observed_at=observed_at,
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)
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def to_dict(self) -> dict[str, object]:
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"""返回确定顺序的内存结构;调用方不得把它直接写入日志。"""
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return {
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"goods_id": self.goods_id,
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"selected_color": self.selected_color,
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"target_size": self.target_size,
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"dimension_name": self.dimension_name,
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"observations": [
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{"raw_text": item.raw_text, "available": item.available}
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for item in self.observations
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],
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"candidates": [item.to_dict() for item in self.candidates],
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"candidate_snapshot_hash": self.candidate_snapshot_hash,
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"observed_at": self.observed_at,
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}
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@dataclass(frozen=True)
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@@ -46,6 +165,24 @@ class PddPurchaseError(RuntimeError):
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self.diagnostics = dict(diagnostics or {})
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class PddPurchaseSpecResolutionRequired(PddPurchaseError):
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"""本地无法精确匹配,但已得到完整可购买候选快照。"""
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def __init__(self, snapshot: PurchaseSpecCandidateSnapshot) -> None:
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super().__init__(
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"PURCHASE_SPEC_RESOLUTION_REQUIRED",
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f"目标尺码无法精确匹配,需要解析候选:{snapshot.target_size}",
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step="purchase_select_options",
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diagnostics={
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"selection_failure": "target_not_visible",
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"candidate_count": len(snapshot.candidates),
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"candidate_snapshot_hash": snapshot.candidate_snapshot_hash,
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"dimension_name": snapshot.dimension_name,
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},
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)
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self.snapshot = snapshot
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class PddPurchaseAdapter(ABC):
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"""一台设备的一次采购演练会话;只能由创建它的工作线程使用。"""
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