marcopan
f104c015a1
New evidence/formula_store.py: ConceptFormula (concept, columns, sql, status, sources) as a frontmatter-YAML + SQL-body unit, stored one-file-per-formula under <formulas>/<slug>-<n>.sql.md. save_formula is append-only (competing drafts and reviewed versions coexist); retrieve_formula(concept) returns all of them so the gate can surface candidates and let the reviewer choose. concept_formula_approved / concept_formula_rejected added to DecisionType (records the reviewer's choice; approved formulas travel with schema-linking). L1: test_formula (7 tests) -- retrieval by concept, save/reload roundtrip (SQL body preserved, frontmatter well-formed), multiple formulas per concept, empty on no-match / missing dir, decision-type existence, default draft status. Deferred: --kind formula on nsp search (needs search_cmd porting) wires retrieve_formula into the CLI; lands with the search command.
101 lines
3.7 KiB
Python
101 lines
3.7 KiB
Python
"""SQL concept->formula evidence store (spec D14b, §4.7).
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A concept (e.g. 'fascia pediatrica', 'ablazione') maps to a reusable SQL formula
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(a CASE WHEN ...) that derives it from physical columns. These are reviewable
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units: the gate surfaces a candidate formula, the reviewer approves or rejects it
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(decision types concept_formula_approved / concept_formula_rejected), and approved
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formulas travel with the schema-linking artifact.
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Storage: one file per formula, frontmatter YAML + SQL body (same shape as
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EvidenceDoc.parse). Directory layout: <root>/formulas/<slug>-<n>.sql.md.
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Retrieve is by concept (may return several, e.g. competing drafts vs reviewed).
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"""
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from __future__ import annotations
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import re
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from pathlib import Path
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from typing import Literal
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import yaml
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from pydantic import BaseModel
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FORMULAS_SUBDIR = "formulas"
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_SUFFIX_RE = re.compile(r"^(.*?)-(\d+)\.sql\.md$")
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class ConceptFormula(BaseModel):
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concept: str
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columns: list[str] = []
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sql: str
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status: Literal["draft", "reviewed"] = "draft"
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sources: list[str] = []
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@property
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def _slug(self) -> str:
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"""ASCII slug for the filename (matches textutil.slugify shape)."""
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import unicodedata
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text = unicodedata.normalize("NFKD", self.concept).encode("ascii", "ignore").decode()
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return re.sub(r"[^a-z0-9_]+", "-", text.lower()).strip("-") or "formula"
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def dump(self) -> str:
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meta = self.model_dump(exclude={"sql"}, mode="json")
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fm = yaml.safe_dump(meta, sort_keys=False, allow_unicode=True)
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return f"---\n{fm}---\n{self.sql}\n"
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@classmethod
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def parse(cls, text: str) -> "ConceptFormula":
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if not text.startswith("---\n"):
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raise ValueError("frontmatter mancante (atteso '---\\n' iniziale)")
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try:
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_, fm, body = text.split("---\n", 2)
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except ValueError as e:
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raise ValueError("frontmatter malformato") from e
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meta = yaml.safe_load(fm)
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if not isinstance(meta, dict):
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raise ValueError("frontmatter non valido")
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return cls.model_validate({**meta, "sql": body.strip("\n")})
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def _next_path(root: Path, slug: str) -> Path:
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"""First free <slug>-<n>.sql.md path under root (n starts at 1)."""
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root.mkdir(parents=True, exist_ok=True)
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existing = sorted(root.glob(f"{slug}-*.sql.md"))
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n = 0
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for p in existing:
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m = _SUFFIX_RE.match(p.name)
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if m:
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n = max(n, int(m.group(2)))
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return root / f"{slug}-{n + 1}.sql.md"
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def save_formula(root: Path | str, formula: ConceptFormula) -> Path:
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"""Persist a single concept->formula unit under <root>/formulas/. Returns the
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written path. Append-only: each save writes a new file (so competing drafts and
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reviewed versions coexist until a curator prunes)."""
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root = Path(root)
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formulas_dir = root / FORMULAS_SUBDIR
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path = _next_path(formulas_dir, formula._slug)
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path.parent.mkdir(parents=True, exist_ok=True)
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path.write_text(formula.dump())
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return path
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def retrieve_formula(root: Path | str, concept: str) -> list[ConceptFormula]:
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"""All formulas for `concept` under <root>/formulas/. Empty list if none (or if
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the dir is absent). Multiple results mean competing drafts/versions for the same
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concept -- the caller (gate) lets the reviewer pick."""
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root = Path(root)
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formulas_dir = root / FORMULAS_SUBDIR
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if not formulas_dir.is_dir():
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return []
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out: list[ConceptFormula] = []
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for f in sorted(formulas_dir.glob("*.sql.md")):
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try:
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formula = ConceptFormula.parse(f.read_text())
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except ValueError:
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continue # malformed file: skip, don't crash retrieval
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if formula.concept == concept:
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out.append(formula)
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return out
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