forked from erp-dev/erp
160 lines
4.5 KiB
Python
160 lines
4.5 KiB
Python
from __future__ import annotations
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import json
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from typing import Any
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from .mappings import plate_order_related_field_definitions, plate_order_relation_control_map
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def _json_loads_safe(value: str) -> Any:
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try:
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return json.loads(value)
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except Exception:
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return value
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def normalize_mdy_value(value: Any) -> Any:
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"""尽量把明道云返回的字符串 JSON 规范化为 Python 对象。
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常见情况：
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- Relation/Attachment 可能返回字符串形式的 "[]" / "[{...}]"
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- 空值经常是 "[]"（字符串）
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"""
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if value is None:
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return None
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if isinstance(value, str):
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s = value.strip()
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if s == "[]":
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return []
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if (s.startswith("[") and s.endswith("]")) or (s.startswith("{") and s.endswith("}")):
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return _json_loads_safe(s)
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return value
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return value
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def extract_relation_rowids(value: Any) -> list[str]:
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"""从 Relation 字段的 value 中提取 rowid 列表。
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兼容形态：
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- list[dict]（常见：[{rowid,name,link}, ...]）
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- str（可能是 JSON 字符串数组，如 "[{...}]" 或 "[]"；也可能是逗号分割 rowId）
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- dict（单条）
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"""
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value = normalize_mdy_value(value)
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if value is None:
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return []
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if isinstance(value, list):
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out: list[str] = []
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for item in value:
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if isinstance(item, dict):
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rid = item.get("rowid") or item.get("rowId")
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if rid:
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out.append(str(rid))
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elif isinstance(item, str) and item.strip():
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out.append(item.strip())
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return out
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if isinstance(value, dict):
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rid = value.get("rowid") or value.get("rowId")
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return [str(rid)] if rid else []
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if isinstance(value, str):
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s = value.strip()
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if not s or s == "[]":
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return []
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# 兜底：逗号分割
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return [x for x in (p.strip() for p in s.split(",")) if x]
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return []
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def extract_plate_order_related_rowids(plate_order_row: dict[str, Any]) -> dict[str, list[str]]:
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"""从开版主表行记录中提取各关联表的 rowid 列表。
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返回：
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- {related_key: [rowid, ...], ...}
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"""
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result: dict[str, list[str]] = {}
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for control_id, related_key in plate_order_relation_control_map.items():
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rowids = extract_relation_rowids(plate_order_row.get(control_id))
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if rowids:
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result[related_key] = rowids
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return result
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def flatten_row_by_field_definitions(
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row: dict[str, Any],
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field_definitions: dict[str, dict[str, Any]],
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*,
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drop_types: set[str] | None = None,
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drop_names: set[str] | None = None,
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include_system_keys: bool = True,
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) -> dict[str, Any]:
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"""按字段定义把一条明道云 row 转成“可读 dict”。
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- key 使用字段中文名（若缺失则回退 controlId）
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- value 做一定的 JSON 字符串规范化
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- 默认包含系统字段：rowid/ctime/utime（若存在）
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"""
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drop_types = drop_types or set()
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drop_names = drop_names or set()
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out: dict[str, Any] = {}
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if include_system_keys:
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for k in ("rowid", "ctime", "utime"):
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if k in row:
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out[k] = row.get(k)
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for field_id, meta in field_definitions.items():
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name = meta.get("name") or field_id
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ftype = meta.get("type")
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if ftype in drop_types:
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continue
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if name in drop_names:
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continue
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out[name] = normalize_mdy_value(row.get(field_id))
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return out
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def flatten_plate_order_related_row(related_key: str, related_row: dict[str, Any]) -> dict[str, Any]:
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"""将开版关联表的一条 row 扁平化为 dict（用于入库 staging.related）。
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- 自动删除回溯 Relation 字段（开版管理/开发管理等）
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- 保留 rowid/ctime/utime（若存在）
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- 额外写入 source 信息，便于排查
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"""
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meta = plate_order_related_field_definitions.get(related_key) or {}
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wsid = meta.get("worksheet_id")
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cn_name = meta.get("name")
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fields = meta.get("fields") or {}
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flat = flatten_row_by_field_definitions(
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related_row,
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fields,
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drop_types={"Relation"},
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drop_names={"开版管理", "开发管理"},
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include_system_keys=True,
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)
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# 扁平化结构：[{key: val}, ...] 里的每个元素是一条记录
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flat["source"] = related_key
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if cn_name:
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flat["source_name"] = cn_name
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if wsid:
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flat["worksheet_id"] = wsid
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return flat
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