Ports the leaf data-layer modules and validates them: - mschema/ (models, eligibility, merge, render), db/ (connection, sampling, introspect, fetch_ca), rest/client.py -- renamed psdwp3->nsp, verbatim. - L0 (testcontainers, real Postgres): db connection read-only enforcement (psd_ro cannot CREATE/INSERT), introspect against a known schema (tables, columns, types, comments, FKs, enum, composite PK), sampling most-frequent values + truncation reporting. 15 tests, ~4s. - L1 (fake data): rest/client RPC contract (mocked transport -- X-API-Key header, payloads, base_url slash handling, HTTP/network error surfacing), mschema/render 3 formats (markdown, mschema-text, schema-dict) + eligibility rules (wide_text excluded, short_text/numeric/enum/temporal/ boolean eligible, annotation override wins). 25 tests. pyproject registers l0/l2 markers + addopts '-m not l2' (L2 opt-in). Deferred to their dependency-porting tasks: test_rrf.py (search needs vectorstore, B3) and the 11 CLI contract tests (need _guards/session, wired when each command lands). 'Not assumed reliable' now has real teeth for the data layer; CLI/search contracts follow.
91 lines
2.1 KiB
Python
91 lines
2.1 KiB
Python
from datetime import datetime
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from pathlib import Path
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from typing import Self
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import yaml
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from pydantic import BaseModel, Field
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class _YamlModel(BaseModel):
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def to_yaml(self, path: Path) -> None:
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path.parent.mkdir(parents=True, exist_ok=True)
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data = self.model_dump(by_alias=True, mode="json", exclude_defaults=False)
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path.write_text(
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yaml.safe_dump(data, sort_keys=False, allow_unicode=True, width=120)
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)
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@classmethod
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def from_yaml(cls, path: Path) -> Self:
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raw = yaml.safe_load(path.read_text())
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return cls.model_validate(raw)
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class ColumnPhysical(BaseModel):
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type: str
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nullable: bool = True
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pk: bool = False
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default: str | None = None
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comment: str = ""
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examples: list[str] = []
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is_enum: bool = False
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eligible: bool = True
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eligibility_reason: str = ""
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class ForeignKey(BaseModel):
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columns: list[str]
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ref_table: str
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ref_columns: list[str]
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name: str = ""
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class Index(BaseModel):
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name: str
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columns: list[str]
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unique: bool = False
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primary: bool = False
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type: str = "btree"
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class TablePhysical(BaseModel):
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comment: str = ""
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row_count: int = 0 # stima da pg_class.reltuples
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columns: dict[str, ColumnPhysical] = {}
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foreign_keys: list[ForeignKey] = []
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indexes: list[Index] = []
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class PhysicalSchema(_YamlModel):
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database: str
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db_schema: str = Field(alias="schema")
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introspected_at: datetime
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tables: dict[str, TablePhysical] = {}
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model_config = {"populate_by_name": True}
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class ColumnAnnotation(BaseModel):
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description: str = ""
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synonyms: list[str] = []
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concepts: list[str] = []
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evidence: list[str] = []
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notes: str = ""
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eligible: bool | None = None
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class TableAnnotation(BaseModel):
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description: str = ""
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concepts: list[str] = []
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notes: str = ""
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columns: dict[str, ColumnAnnotation] = {}
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class Annotations(_YamlModel):
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tables: dict[str, TableAnnotation] = {}
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@classmethod
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def from_yaml(cls, path: Path) -> "Annotations":
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if not path.exists():
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return cls()
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return super().from_yaml(path)
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