From d805f64195ad23f5a56b3c4e1822fff6d2960735 Mon Sep 17 00:00:00 2001 From: ThearchyHelios Date: Sun, 4 Oct 2026 01:17:29 +0800 Subject: [PATCH] =?UTF-8?q?=E6=95=B0=E6=8D=AE=E7=9B=AE=E5=BD=95=20F1=20?= =?UTF-8?q?=E4=B8=80=E8=87=B4=E6=80=A7=EF=BC=9A=E6=97=A5=E6=9C=9F=E5=88=97?= =?UTF-8?q?=E7=9A=84=E5=88=A4=E5=AE=9A=E6=8A=BD=E6=88=90=20catalog.is=5Fda?= =?UTF-8?q?te=5Fcolumn=EF=BC=8C=E6=95=B0=E6=8D=AE=E5=89=96=E6=9E=90?= =?UTF-8?q?=EF=BC=88=E5=94=AF=E4=B8=80=E6=97=A5=E6=9C=9F=E5=88=97=E6=8F=90?= =?UTF-8?q?=E8=AE=AE=E4=B8=9A=E5=8A=A1=E6=97=A5=E6=9C=9F=EF=BC=89=E5=92=8C?= =?UTF-8?q?=20SQL=20=E6=A3=80=E6=9F=A5=EF=BC=88=E6=8C=89=E4=B8=9A=E5=8A=A1?= =?UTF-8?q?=E6=97=A5=E6=9C=9F=E4=BB=A5=E5=A4=96=E7=9A=84=E6=97=B6=E9=97=B4?= =?UTF-8?q?=E5=88=97=E7=BB=9F=E8=AE=A1=EF=BC=89=E5=85=B1=E7=94=A8=EF=BC=8C?= =?UTF-8?q?=E5=8F=AA=E6=9C=89=E6=97=B6=E5=88=BB=E7=9A=84=20TIME=E3=80=81?= =?UTF-8?q?=E6=95=B4=E6=95=B0=E5=AD=98=E7=9A=84=E6=97=B6=E9=97=B4=E6=88=B3?= =?UTF-8?q?=E4=B8=A4=E8=BE=B9=E9=83=BD=E4=B8=8D=E7=AE=97=EF=BC=9B=E8=A1=A8?= =?UTF-8?q?=E5=90=8D=E5=8C=B9=E9=85=8D=E7=BB=9F=E4=B8=80=E6=8C=89=20name?= =?UTF-8?q?=5Fkey=EF=BC=88=E5=8F=AA=E6=8A=8A=20ASCII=20=E5=AD=97=E6=AF=8D?= =?UTF-8?q?=E8=BD=AC=E5=B0=8F=E5=86=99=EF=BC=89=EF=BC=8Cresolve=5Ftable=5F?= =?UTF-8?q?name=20=E5=92=8C=20SQL=20=E6=A3=80=E6=9F=A5=E9=87=8C=E8=AE=A4?= =?UTF-8?q?=E8=A1=A8=E5=90=8D=E4=B8=8D=E5=86=8D=E6=8C=89=20Unicode=20?= =?UTF-8?q?=E8=BD=AC=E5=B0=8F=E5=86=99=EF=BC=8C=E5=92=8C=E4=BD=BF=E7=94=A8?= =?UTF-8?q?=E6=AC=A1=E6=95=B0=E3=80=81=E5=BD=B1=E5=93=8D=E9=9D=A2=E5=90=8C?= =?UTF-8?q?=E4=B8=80=E4=B8=AA=E5=8F=A3=E5=BE=84=EF=BC=9B=E5=88=87=E8=AF=8D?= =?UTF-8?q?=E5=90=88=E5=B9=B6=E6=88=90=20catalog.name=5Fwords=EF=BC=8C?= =?UTF-8?q?=E5=89=96=E6=9E=90=E4=B8=8D=E5=86=8D=E5=8F=A6=E5=86=99=E4=B8=80?= =?UTF-8?q?=E4=BB=BD=EF=BC=9B=E6=9B=B4=E6=96=B0=E8=BF=87=E6=97=B6=E7=9A=84?= =?UTF-8?q?=E8=AF=B4=E6=98=8E=EF=BC=88=E9=94=99=E8=AF=AF=E7=BA=A7=E6=A3=80?= =?UTF-8?q?=E6=9F=A5=E5=B7=B2=E7=BB=8F=E4=B8=8A=E7=BA=BF=E3=80=81=E5=89=96?= =?UTF-8?q?=E6=9E=90=E9=A2=84=E7=AE=97=E7=9A=84=E5=8F=AB=E6=B3=95=E8=B7=9F?= =?UTF-8?q?=E8=AE=BE=E7=BD=AE=E7=95=8C=E9=9D=A2=EF=BC=89=EF=BC=9B=E7=A0=81?= =?UTF-8?q?=E5=80=BC=E6=AF=94=E8=BE=83=E4=B8=8D=E5=88=86=E5=A4=A7=E5=B0=8F?= =?UTF-8?q?=E5=86=99=E4=BF=9D=E7=95=99=EF=BC=8C=E6=B3=A8=E9=87=8A=E5=86=99?= =?UTF-8?q?=E6=98=8E=E6=98=AF=E7=85=A7=E9=A1=BE=20MySQL=20=E9=BB=98?= =?UTF-8?q?=E8=AE=A4=E6=8E=92=E5=BA=8F=E8=A7=84=E5=88=99=E3=80=81=E5=AE=81?= =?UTF-8?q?=E5=8F=AF=E6=BC=8F=E6=8A=A5?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- backend/app/data/catalog.py | 80 +++++++++++++++++-------- backend/app/data/catalog_profile.py | 23 ++----- backend/app/data/sqlcheck.py | 30 +++++----- backend/tests/test_catalog_semantics.py | 39 ++++++++++++ 4 files changed, 116 insertions(+), 56 deletions(-) diff --git a/backend/app/data/catalog.py b/backend/app/data/catalog.py index caea0a17..b9176051 100644 --- a/backend/app/data/catalog.py +++ b/backend/app/data/catalog.py @@ -1,4 +1,4 @@ -"""业务数据目录：每张表一份业务说明，给助手建图、db_schema 工具和后续的检查用。 +"""业务数据目录：每张表一份业务说明，给助手建图、db_schema 工具和 SQL 检查（data/sqlcheck.py）用。 **为什么要有它。** 接进来的业务库往往一个注释都没有：几百张表、上千个字段，助手只看得到名字，模型就会 照着名字编字段、猜关联。目录把「一行代表什么、业务主键是哪几列、业务日期按哪列算、金额是什么单位、 @@ -23,12 +23,14 @@ notes 结构（每个「项」都是 {value, source, status}，可选 note、upd 来源（source）：comment 数据库注释、fk 外键约束、name 命名推断、profile 数据剖析（data/catalog_profile.py）、 llm 模型起草、human 人工填写。状态（status）：proposed 推断（命名推断、模型起草、数据库注释）、verified 有确证 （外键约束；数据剖析核实了覆盖率和父键唯一的关系也是，见 profile_relation_holds）、confirmed 人工确认、 -rejected 人工驳回。只有 confirmed 和 verified -将来会触发错误级检查；给模型看时 proposed 的项标「推断，未确认」；rejected 的项留着（防止下次起草又提出 -来），但模型和检查都看不到。 +rejected 人工驳回。SQL 检查只在依据全是 confirmed、verified +时报错误级（data/sqlcheck.py），依据里有 proposed 就降为提示；给模型看时 proposed 的项标「推断，未确认」； +rejected 的项留着（防止下次起草又提出来），但模型和检查都看不到。 -本模块分几块：存取（带乐观锁）、结构校验、合并与审阅、起草、渲染、关系图、使用次数、冻结。存取以外的 -函数尽量是纯函数，接口层、db_schema 工具和后续阶段（1B 助手挑表、2 数据剖析、4 维护闭环）共用。 +本模块分几块：存取（带乐观锁）、结构校验、合并与审阅、对话提案、起草、渲染、关系图、使用次数、冻结。存取 +以外的函数尽量是纯函数，接口层、db_schema 工具、助手挑表（api/copilot_context.py）、数据剖析 +（data/catalog_profile.py）和 SQL 检查（data/sqlcheck.py）共用；几处两边都要用的判断也放在这里只写一份： +表名的匹配（resolve_table_name，按 name_key）、名字切词（name_words）、日期列的判定（is_date_column）。 """ from __future__ import annotations @@ -535,7 +537,7 @@ def _same_core(a: Mapping[str, Any], b: Mapping[str, Any]) -> bool: def visible_notes(notes: Mapping[str, Any] | None) -> dict[str, Any]: - """去掉被驳回的项和关系。给模型看、冻结进证据、将来的检查都只用这一份。""" + """去掉被驳回的项和关系。给模型看、冻结进证据、SQL 检查（data/sqlcheck.py）都只用这一份。""" return _assemble({k: v for k, v in _slots(notes).items() if v.get("status") != "rejected"}) @@ -1128,15 +1130,20 @@ def system_notes_source(source: Any) -> bool: def resolve_table_name(schema_cache: Mapping[str, Any] | None, name: str) -> str | None: - """在表结构里找表，返回 schema_cache["tables"] 的键。全名、只有表名、大小写不一致都认。""" + """在表结构里找表，返回 schema_cache["tables"] 的键。全名、只有表名、大小写不一致都认。 + + 大小写按 name_key 比：只把 ASCII 字母转小写，和 SQLite 比较标识符、使用次数（table_usage）、影响面 + （catalog_impact）的口径一致。以前这里按 Unicode 转小写，表名里有非 ASCII 大写字母时（「CAFÉ_ORDERS」） + 这里认得、那两处认不得，同一张表在目录页和影响面上对不上。 + """ tables = (schema_cache or {}).get("tables") or {} if name in tables: return name short = name.rsplit(".", 1)[-1] if short in tables: return short - lowered = short.lower() - return next((n for n in tables if n.lower() == lowered), None) + key = name_key(short) + return next((n for n in tables if name_key(n) == key), None) #: 数据库注释多长、带不带句读，决定它是「名字」还是「解释」 @@ -1202,11 +1209,37 @@ _CAMEL_ID = re.compile(r"^(?P.*[a-z0-9])(?:Id|ID)$") _WORDS = re.compile(r"[A-Z]+(?=[A-Z][a-z])|[A-Z]?[a-z]+|[A-Z]+|\d+") -def _words(name: str) -> list[str]: - """名字切成小写的词：下划线和驼峰都是分隔（memberTag、member_tag、MEMBER_TAG 都是 member + tag）。""" +def name_words(name: str) -> list[str]: + """名字切成小写的词：下划线和驼峰都是分隔（memberTag、member_tag、MEMBER_TAG 都是 member + tag）。 + + 命名推断、数据剖析认码值列和日期列都用这一个切法（以前剖析另写了一份一样的）。 + """ return [w.lower() for part in name.split("_") for w in _WORDS.findall(part)] +#: 名字像日期、时间的列，切词后的最后一个词：visit_time、ordered_at、joined_on、createdAt、biz_dt、load_ts…… +_DATE_TAILS = frozenset({"at", "on", "date", "time", "day", "dt", "ts", "timestamp", "datetime"}) +#: 单独做列名也算日期的词。at、on 单独做列名不是日期 +_DATE_WORDS = frozenset({"date", "time", "day", "dt", "ts", "timestamp", "datetime"}) +_TEXT_TYPES = ("CHAR", "TEXT", "STRING", "CLOB") + + +def is_date_column(name: str, type_name: str | None) -> bool: + """日期类列：类型是日期、时间戳（DATE、DATETIME、TIMESTAMP……）；或者类型是文字（或者不知道类型）、名字像日期 + （SQLite 的日期常存成文字）。只有时刻的 TIME、整数存的时间戳不算：取值不是日期。 + + 数据剖析（表里只有一个日期类列时提议它作业务日期）和 SQL 检查（按业务日期以外的时间列统计）共用这一个判断。 + 以前两边各写一套：剖析认的「唯一日期列」，SQL 检查可能认为还有别的时间列，反过来也一样，两边对不上。 + """ + t = (type_name or "").upper() + if "DATE" in t or "TIMESTAMP" in t: + return True + if t and not any(k in t for k in _TEXT_TYPES): + return False + words = name_words(name) + return bool(words) and words[-1] in _DATE_TAILS and (len(words) > 1 or words[0] in _DATE_WORDS) + + def _singulars(word: str) -> set[str]: """一个词可能的单数形式（含它自己）。两边都取这个集合、有交集就算同一个词：categories 和 category、 courses 和 course、status 和 statuses 都对得上，不靠一套「复数变单数」的规则硬猜。""" @@ -1224,7 +1257,7 @@ def _name_index(tables: Mapping[str, Any]) -> dict[tuple[str, str], set[str]]: """{(前面几个词拼起来, 最后一个词的单数形式): 表名}。""" index: dict[tuple[str, str], set[str]] = {} for name in tables: - words = _words(name) + words = name_words(name) if not words: continue prefix = "".join(words[:-1]) @@ -1277,7 +1310,7 @@ def infer_name_relations(schema_cache: Mapping[str, Any] | None, table: str, *, stem = _id_stem(name) if stem is None or name.lower() in constrained: continue - words = _words(stem) + words = name_words(stem) if not words or len("".join(words)) < 2: continue prefix = "".join(words[:-1]) @@ -1287,7 +1320,7 @@ def infer_name_relations(schema_cache: Mapping[str, Any] | None, table: str, *, if not candidates: # 直接对不上：库里的表常带业务前缀（store_tags），列名却只写词根（tagId）。 # 只认和引用它的表共用前缀的那张，从最长的共用前缀试起；仍然不止一张就不推 - own = _words(table) + own = name_words(table) for k in range(len(own) - 1, 0, -1): for form in _singulars(words[-1]): candidates |= index.get(("".join(own[:k]) + prefix, form), set()) @@ -2148,14 +2181,13 @@ __all__ = [ "CatalogEntry", "CatalogInvalid", "CatalogModelUnavailable", "CatalogPathError", "DRAFT_DEFAULT_TABLES", "DraftReport", "INFERRED_MARK", "ITEM_SOURCES", "ITEM_STATUSES", "JoinEdge", "KIND_LABEL", "MEASURE_LABEL", "MergeStats", "NEW_RELATION_PATH", "PATCH_MAX_CHANGES", "PROFILE_NOTE_PREFIX", "PROFILE_VERIFY_COVERAGE", - "PatchChange", "PatchPlan", - "QUERY_SNAPSHOT_KIND", "REVIEW_ACTIONS", "TABLE_FIELDS", "TABLE_FIELD_LABEL", "TABLE_KINDS", "TableDraft", - "TableDraftResult", "UI_KIND_LABEL", "UI_MEASURE_LABEL", "apply_human_edit", "apply_patch", "codes_complete", - "describe_slot", - "draft_catalog", "draft_structure", "draft_with_model", "fk_relations", "frozen_catalog", "infer_name_relations", - "initial_status", "join_paths", "make_item", "merge_notes", "now_iso", "parse_path", "plan_patch", - "profile_relation_holds", "query_snapshot_meta", "read_catalog", "read_entry", "relation_graph", "relation_id", - "render_table_index", "render_table_notes", "resolve_draft_model", "resolve_table_name", "review_entry", - "review_item", "same_notes", "save_human_edit", "save_patch", "status_counts", "structure_relation_ids", + "PatchChange", "PatchPlan", "QUERY_SNAPSHOT_KIND", "REVIEW_ACTIONS", "TABLE_FIELDS", "TABLE_FIELD_LABEL", + "TABLE_KINDS", "TableDraft", "TableDraftResult", "UI_KIND_LABEL", "UI_MEASURE_LABEL", "apply_human_edit", + "apply_patch", "codes_complete", "describe_slot", "draft_catalog", "draft_structure", "draft_with_model", + "fk_relations", "frozen_catalog", "infer_name_relations", "initial_status", "is_date_column", "join_paths", + "make_item", "merge_notes", "name_words", "now_iso", "parse_path", "plan_patch", "profile_relation_holds", + "query_snapshot_meta", "read_catalog", "read_entry", "relation_graph", "relation_id", "render_table_index", + "render_table_notes", "resolve_draft_model", "resolve_table_name", "review_entry", "review_item", "same_notes", + "same_profile_note", "save_human_edit", "save_patch", "status_counts", "structure_relation_ids", "system_notes_source", "table_usage", "unreviewed_status", "validate_notes", "visible_notes", "write_entry", ] diff --git a/backend/app/data/catalog_profile.py b/backend/app/data/catalog_profile.py index d76e3ea1..710b657f 100644 --- a/backend/app/data/catalog_profile.py +++ b/backend/app/data/catalog_profile.py @@ -67,7 +67,8 @@ class ProfileSettings: return asdict(self) -#: 数值项：(中文叫法, 下限, 上限, 是否必须是整数)。叫法和将来设置界面上的标签一致，报错里只写它 +#: 数值项：(中文叫法, 下限, 上限, 是否必须是整数)。叫法和数据源设置里剖析预算的标签一致（frontend/src/lib/terms.ts）， +#: 报错里只写它 _NUMBER_FIELDS: dict[str, tuple[str, float, float, bool]] = { "max_queries": ("查询次数上限", 1, 500, True), "query_timeout_s": ("单条查询时限（秒）", 1, 60, False), @@ -770,16 +771,8 @@ _CODE_WORDS = frozenset({"status", "state", "type", "kind", "category", "channel #: 以这些词结尾的列不是码值：标识、名称、说明、时间、金额、数量（channel_id、level_name、status_time……） _NOT_CODE_TAILS = frozenset({"id", "no", "num", "number", "name", "desc", "description", "text", "remark", "note", "at", "date", "time", "on", "amount", "price", "count", "qty", "rate", "url"}) -#: 文字类型的列名以这些词结尾时，按日期类列看待（SQLite 里日期都存成文字：visit_time、ordered_at、joined_on） -_DATE_TAILS = frozenset({"at", "date", "time", "on", "dt", "day"}) #: 像日期的取值：2026-07-01、2026/07/01，后面可以跟时间 _DATE_TEXT = re.compile(r"^\d{4}[-/]\d{2}[-/]\d{2}") -_WORDS = re.compile(r"[A-Z]+(?=[A-Z][a-z])|[A-Z]?[a-z]+|[A-Z]+|\d+") - - -def _words(name: str) -> list[str]: - """列名切成小写的词：下划线和驼峰都是分隔（和目录的命名推断同一个切法）。""" - return [w.lower() for part in name.split("_") for w in _WORDS.findall(part)] def _code_type_ok(type_name: str | None) -> bool: @@ -799,7 +792,7 @@ def _code_type_ok(type_name: str | None) -> bool: def _looks_like_code(name: str) -> bool: - words = _words(name) + words = catalog.name_words(name) return bool(words) and words[-1] not in _NOT_CODE_TAILS and any(w in _CODE_WORDS for w in words) @@ -881,14 +874,8 @@ async def _check_codes(cx: _Context, table: str, column: str, out: _TableOutcome def _is_date_column(col: dict[str, Any]) -> bool: - """日期类列：类型是日期、时间戳；或者类型是文字、列名像日期（SQLite 的日期都存成文字）。""" - t = str(col.get("type") or "").upper() - if "DATE" in t or "TIMESTAMP" in t: - return True - if t and not any(k in t for k in ("CHAR", "TEXT", "STRING")): - return False - words = _words(str(col.get("name") or "")) - return bool(words) and words[-1] in _DATE_TAILS and (len(words) > 1 or words[0] in ("date", "time", "day")) + """日期类列（catalog.is_date_column：和 SQL 检查认时间列是同一个判断）。""" + return catalog.is_date_column(str(col.get("name") or ""), col.get("type")) async def _check_dates(cx: _Context, table: str, columns: list[str], total: int, out: _TableOutcome, diff --git a/backend/app/data/sqlcheck.py b/backend/app/data/sqlcheck.py index 6f234d1a..ea19d692 100644 --- a/backend/app/data/sqlcheck.py +++ b/backend/app/data/sqlcheck.py @@ -41,6 +41,7 @@ from dataclasses import dataclass, field from typing import Any from app.data import catalog +from app.data.names import name_key logger = logging.getLogger(__name__) @@ -69,11 +70,6 @@ _EXCERPT_MAX = 160 _SENTINEL = "__agentlab_tpl__" _TEMPLATE = re.compile(r"\{\{.*?\}\}", re.S) -#: 名字看得出是时间的列：xxx_at、xxx_time、xxx_date、xxx_on、createdAt…（SQLite 的日期常存成文本，只看类型认不全） -_TEMPORAL_NAME = re.compile(r"(?:^|_)(?:at|time|date|day|dt|ts|on|timestamp|datetime)$|[a-z0-9](?:At|Time|Date|On)$", - re.IGNORECASE) -_TEMPORAL_TYPE = re.compile(r"DATE|TIME", re.IGNORECASE) - def dialect_of(kind: str | None) -> str | None: """数据源类型对应的 sqlglot 方言；不支持的类型返回 None（不查）。""" @@ -133,7 +129,8 @@ class SqlChecker: self.source_name = source_name self._raw = {str(k): v for k, v in (notes or {}).items() if isinstance(v, Mapping) and v} self._visible = {k: catalog.visible_notes(v) for k, v in self._raw.items()} - self._visible_lower = {k.lower(): v for k, v in self._visible.items()} + # 表名按 name_key 比（只把 ASCII 字母转小写），和 catalog.resolve_table_name、使用次数、影响面同一个口径 + self._visible_lower = {name_key(k): v for k, v in self._visible.items()} self._edges: dict[str, list[catalog.JoinEdge]] | None = None @property @@ -161,7 +158,7 @@ class SqlChecker: return (key, meta) if key and isinstance(meta, Mapping) else None def notes_of(self, table: str) -> dict[str, Any]: - return self._visible.get(table) or self._visible_lower.get(table.lower()) or {} + return self._visible.get(table) or self._visible_lower.get(name_key(table)) or {} def edges_between(self, a: str, b: str) -> list[catalog.JoinEdge]: """从 a 连到 b 的边（每条关系正反各一条）。关系图第一次用到时才建，之后复用。 @@ -169,7 +166,7 @@ class SqlChecker: 和助手挑表看到的是同一张图（catalog.relation_graph）：目录里的关系，加上没起草过的表按外键、命名现推的； 被驳回的关系不进图，也不会被现推回来。 """ - return [e for e in self.edges_from(a) if e.to_table.lower() == b.lower()] + return [e for e in self.edges_from(a) if name_key(e.to_table) == name_key(b)] def edges_from(self, a: str) -> list[catalog.JoinEdge]: """从 a 出发的全部边。关系图第一次用到时才建，之后复用。""" @@ -177,9 +174,9 @@ class SqlChecker: graph = catalog.relation_graph(self._raw, schema_cache=self.schema_cache) index: dict[str, list[catalog.JoinEdge]] = {} for table, edges in graph.items(): - index.setdefault(table.lower(), []).extend(edges) + index.setdefault(name_key(table), []).extend(edges) self._edges = index - return list(self._edges.get(a.lower(), [])) + return list(self._edges.get(name_key(a), [])) # ---- 检查 @@ -302,10 +299,11 @@ class _Table: return self.columns[column.lower()], str(item.get("status")) def temporal(self, column: str) -> bool: + """这一列是不是时间列（catalog.is_date_column：和数据剖析认日期列是同一个判断，剖析提议业务日期时认的 + 「唯一日期列」和这里认的时间列对得上）。""" meta = next((c for c in self.meta.get("columns") or [] if isinstance(c, Mapping) and str(c.get("name")).lower() == column.lower()), None) - kind = str((meta or {}).get("type") or "") - return bool(_TEMPORAL_TYPE.search(kind) or _TEMPORAL_NAME.search(column)) + return catalog.is_date_column(column, (meta or {}).get("type")) #: 一列解析到的位置：(表, 列的真名) @@ -548,7 +546,7 @@ class _ScopeCheck: if x in skip or y in skip: continue a, b = self.tables[x], self.tables[y] - if a.name.lower() == b.name.lower(): + if name_key(a.name) == name_key(b.name): continue # 自己连自己：目录不记这种关系 pairs = group["pairs"] candidates = self.checker.edges_between(a.name, b.name) @@ -990,7 +988,11 @@ def _number(text: str) -> float | None: def _known_code(literal: tuple[str, bool], codes: Mapping[str, Any]) -> bool: - """值在不在码值表里：原样相等、不分大小写相等、或者两边都是数且数值相等（1 和 '1'、1.0 都算 1）。""" + """值在不在码值表里：原样相等、不分大小写相等、或者两边都是数且数值相等（1 和 '1'、1.0 都算 1）。 + + 不分大小写是有意的：MySQL 默认的排序规则比较字符串本来就不分大小写，status = 'paid' 照样筛得出 'PAID'； + PostgreSQL、SQLite 区分大小写，这样比会漏报一些，但宁可漏报，不能把在 MySQL 上完全正确的写法报成错。 + """ text = literal[0] keys = [str(k) for k in codes] if text in keys or text.strip().lower() in {k.strip().lower() for k in keys}: diff --git a/backend/tests/test_catalog_semantics.py b/backend/tests/test_catalog_semantics.py index 3f307334..a3dd338e 100644 --- a/backend/tests/test_catalog_semantics.py +++ b/backend/tests/test_catalog_semantics.py @@ -441,3 +441,42 @@ async def test_model_draft_drops_formula_items(): assert set(notes["columns"]["total_amount"]) == {"label", "unit"} +# ========================================================================== +# 一致性 +# ========================================================================== + + +@pytest.mark.parametrize("name, type_, expected", [ + ("visit_time", "TEXT", True), ("ordered_at", "TEXT", True), ("joined_on", "VARCHAR(20)", True), + ("createdAt", "", True), ("biz_date", "DATE", True), ("paid", "DATETIME", True), ("loaded", "TIMESTAMP", True), + ("dt", "TEXT", True), ("date", "TEXT", True), + ("created_at", "INTEGER", False), # 整数存的时间戳：取值不是日期，剖析和检查都不当日期列 + ("open_time", "TIME", False), # 只有时刻、没有日期 + ("on_hand", "INTEGER", False), ("status", "TEXT", False), ("at", "TEXT", False), ("ticket_no", "TEXT", False), +]) +def test_date_column_rule_is_shared(name, type_, expected): + assert catalog.is_date_column(name, type_) is expected + # 剖析认的日期列（业务日期提议）和 SQL 检查认的时间列（按别的时间列统计）是同一套 + assert catalog_profile._is_date_column({"name": name, "type": type_}) is expected + table = sqlcheck._Table(alias="t", name="t", meta={"columns": [{"name": name, "type": type_}]}, notes={}, + order=0) + assert table.temporal(name) is expected + + +def test_table_names_match_by_name_key_everywhere(): + """表名只把 ASCII 字母转小写（name_key，和 SQLite 比较标识符一致）：非 ASCII 的大小写不同就是两张表。""" + cache = {"tables": {"CAFÉ_ORDERS": {"columns": []}, "Visits": {"columns": []}}} + assert catalog.resolve_table_name(cache, "visits") == "Visits" + assert catalog.resolve_table_name(cache, "main.VISITS") == "Visits" + assert catalog.resolve_table_name(cache, "cafÉ_orders") == "CAFÉ_ORDERS" + assert catalog.resolve_table_name(cache, "café_orders") is None + checker = sqlcheck.SqlChecker(kind="sqlite", schema_cache=cache, notes={"CAFÉ_ORDERS": { + "label": catalog.make_item("咖啡订单", "human")}}) + assert checker.notes_of("cafÉ_orders")["label"]["value"] == "咖啡订单" + assert checker.notes_of("café_orders") == {} + + +def test_word_splitting_has_one_implementation(): + assert catalog.name_words("memberTagId") == ["member", "tag", "id"] + assert catalog.name_words("MEMBER_TAG") == ["member", "tag"] + assert not hasattr(catalog_profile, "_words") and not hasattr(catalog_profile, "_WORDS")