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from __future__ import annotations
import json
from dataclasses import asdict, dataclass
from pathlib import Path
from typing import Iterable, Iterator
from config.paths import (
CUI_TO_VALID_AUI_JSON,
CUI_TO_VALID_AUI_PARQUET,
GRAPH_ID_MAPS_PARQUET,
MRCONSO_CLINICAL_PARQUET,
MRCONSO_CLINICAL_PARQUET_DEFAULT,
)
from src.data.query_entity_linker import QueryEntityLinker
def _resolve_mrconso_parquet(path: Path | None) -> Path:
if path is not None:
candidate = path
elif MRCONSO_CLINICAL_PARQUET.exists():
candidate = MRCONSO_CLINICAL_PARQUET
else:
candidate = MRCONSO_CLINICAL_PARQUET_DEFAULT
if not candidate.exists():
raise FileNotFoundError(
f"Clinical MRCONSO parquet not found: {candidate}. "
"Copy mrconso_clinical.parquet to data/processed/graph/ or set "
"ICD_MRCONSO_CLINICAL_PARQUET."
)
return candidate
@dataclass(frozen=True)
class ValidAuiRecord:
cui: str
aui: str
graph_idx: int
str: str
sab: str
def _cui_to_valid_aui_sql(
*,
id_maps_parquet: Path,
mrconso_parquet: Path,
) -> str:
return f"""
WITH graph_auis AS (
SELECT
cui,
REPLACE(node_id, 'AUI:', '') AS aui,
idx,
degree,
str,
sab
FROM read_parquet('{id_maps_parquet.as_posix()}')
WHERE kind = 'AUI' AND cui IS NOT NULL
),
ranked AS (
SELECT
g.cui,
g.aui,
g.idx,
g.str,
g.sab,
ROW_NUMBER() OVER (
PARTITION BY g.cui
ORDER BY g.degree DESC, g.idx
) AS rn
FROM graph_auis g
INNER JOIN read_parquet('{mrconso_parquet.as_posix()}') m
ON g.aui = m.AUI
)
SELECT cui, aui, idx AS graph_idx, str, sab
FROM ranked
WHERE rn = 1
"""
def build_cui_to_valid_aui_parquet(
output: Path = CUI_TO_VALID_AUI_PARQUET,
*,
id_maps_parquet: Path = GRAPH_ID_MAPS_PARQUET,
mrconso_parquet: Path | None = None,
) -> int:
"""Build the CUI→AUI parquet cache via DuckDB + clinical MRCONSO parquet."""
mrconso = _resolve_mrconso_parquet(mrconso_parquet)
if not id_maps_parquet.exists():
raise FileNotFoundError(f"Graph id maps not found: {id_maps_parquet}")
import duckdb
output.parent.mkdir(parents=True, exist_ok=True)
con = duckdb.connect()
con.execute(
f"""
COPY (
{_cui_to_valid_aui_sql(
id_maps_parquet=id_maps_parquet,
mrconso_parquet=mrconso,
)}
) TO '{output.as_posix()}' (FORMAT PARQUET)
"""
)
con.close()
import polars as pl
return pl.scan_parquet(output).select(pl.len()).collect().item()
def build_cui_to_valid_aui_map(
*,
id_maps_parquet: Path = GRAPH_ID_MAPS_PARQUET,
mrconso_parquet: Path | None = None,
) -> dict[str, ValidAuiRecord]:
"""Map each CUI to its highest-degree AUI present in clinical MRCONSO."""
build_cui_to_valid_aui_parquet(
id_maps_parquet=id_maps_parquet,
mrconso_parquet=mrconso_parquet,
)
lookup = CuiToValidAuiLookup(CUI_TO_VALID_AUI_PARQUET)
try:
import polars as pl
cuis = (
pl.scan_parquet(CUI_TO_VALID_AUI_PARQUET)
.select("cui")
.collect()
.get_column("cui")
.to_list()
)
return lookup.lookup_many(cuis)
finally:
lookup.close()
def save_cui_to_valid_aui_map(
path: Path,
mapping: dict[str, ValidAuiRecord],
) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
payload = {cui: asdict(rec) for cui, rec in mapping.items()}
path.write_text(json.dumps(payload), encoding="utf-8")
def load_cui_to_valid_aui_map(
path: Path = CUI_TO_VALID_AUI_JSON,
) -> dict[str, ValidAuiRecord]:
payload = json.loads(path.read_text(encoding="utf-8"))
return {
cui: ValidAuiRecord(
cui=str(rec["cui"]),
aui=str(rec["aui"]),
graph_idx=int(rec["graph_idx"]),
str=str(rec.get("str", "")),
sab=str(rec.get("sab", "")),
)
for cui, rec in payload.items()
}
class CuiToValidAuiLookup:
"""Polars-backed lookup over ``cui_to_valid_aui.parquet`` (memory-safe)."""
def __init__(self, parquet_path: Path = CUI_TO_VALID_AUI_PARQUET) -> None:
if not parquet_path.exists():
raise FileNotFoundError(f"CUI→AUI parquet not found: {parquet_path}")
import polars as pl
self._parquet_path = parquet_path
self._scan = pl.scan_parquet(parquet_path)
def count(self) -> int:
import polars as pl
return self._scan.select(pl.len()).collect().item()
def lookup_many(self, cuis: Iterable[str]) -> dict[str, ValidAuiRecord]:
unique = list(dict.fromkeys(str(c) for c in cuis if c))
if not unique:
return {}
import polars as pl
df = self._scan.filter(pl.col("cui").is_in(unique)).collect()
out: dict[str, ValidAuiRecord] = {}
for row in df.iter_rows(named=True):
cui = str(row["cui"])
out[cui] = ValidAuiRecord(
cui=cui,
aui=str(row["aui"]),
graph_idx=int(row["graph_idx"]),
str=str(row["str"]) if row["str"] is not None else "",
sab=str(row["sab"]) if row["sab"] is not None else "",
)
return out
def close(self) -> None:
return None
def ensure_cui_to_valid_aui_lookup(
*,
parquet_path: Path = CUI_TO_VALID_AUI_PARQUET,
rebuild: bool = False,
id_maps_parquet: Path = GRAPH_ID_MAPS_PARQUET,
mrconso_parquet: Path | None = None,
) -> CuiToValidAuiLookup:
if not parquet_path.exists() or rebuild:
build_cui_to_valid_aui_parquet(
parquet_path,
id_maps_parquet=id_maps_parquet,
mrconso_parquet=mrconso_parquet,
)
return CuiToValidAuiLookup(parquet_path)
def ensure_cui_to_valid_aui_map(
*,
path: Path = CUI_TO_VALID_AUI_JSON,
rebuild: bool = False,
id_maps_parquet: Path = GRAPH_ID_MAPS_PARQUET,
mrconso_parquet: Path | None = None,
) -> dict[str, ValidAuiRecord]:
lookup = ensure_cui_to_valid_aui_lookup(
rebuild=rebuild,
id_maps_parquet=id_maps_parquet,
mrconso_parquet=mrconso_parquet,
)
try:
import polars as pl
cuis = (
pl.scan_parquet(CUI_TO_VALID_AUI_PARQUET)
.select("cui")
.collect()
.get_column("cui")
.to_list()
)
return lookup.lookup_many(cuis)
finally:
lookup.close()
def detect_entities_for_text(
text: str,
*,
linker: QueryEntityLinker,
lookup: CuiToValidAuiLookup,
) -> list[dict[str, object]]:
"""Return kept CUI/AUI entities for one query text."""
linked = linker.link_cuis(text)
records = lookup.lookup_many(cui for cui, _ in linked)
entities: list[dict[str, object]] = []
for cui, confidence in linked:
record = records.get(cui)
if record is None:
continue
entities.append(
{
"cui": record.cui,
"aui": record.aui,
"confidence": round(float(confidence), 4),
"graph_idx": record.graph_idx,
"str": record.str,
"sab": record.sab,
}
)
return entities
def export_entity_detections(
rows: list[dict[str, object]],
*,
linker: QueryEntityLinker,
lookup: CuiToValidAuiLookup,
text_key: str = "query_text",
include_code: bool = True,
) -> list[dict[str, object]]:
"""Build export records aligned to input JSONL rows."""
return list(
iter_entity_detection_entries(
rows,
linker=linker,
lookup=lookup,
text_key=text_key,
include_code=include_code,
)
)
def iter_entity_detection_entries(
rows: list[dict[str, object]],
*,
linker: QueryEntityLinker,
lookup: CuiToValidAuiLookup,
text_key: str = "query_text",
include_code: bool = True,
) -> Iterator[dict[str, object]]:
for row in rows:
text = str(row.get(text_key, "")).strip()
entry: dict[str, object] = {"query_text": text}
if include_code and "code" in row:
entry["code"] = row["code"]
entry["entities"] = detect_entities_for_text(
text,
linker=linker,
lookup=lookup,
)
yield entry
def write_entity_detections_json(
entries: Iterable[dict[str, object]],
output: Path,
*,
pretty: bool = False,
) -> tuple[int, int, int]:
"""Stream entries to JSON without holding the full payload in memory."""
output.parent.mkdir(parents=True, exist_ok=True)
n_entries = 0
with_entities = 0
total_entities = 0
with open(output, "w", encoding="utf-8") as f:
f.write('{\n "entries": [\n')
first = True
for entry in entries:
if not first:
f.write(",\n")
else:
first = False
f.write(" ")
if pretty:
rendered = json.dumps(entry, ensure_ascii=False, indent=2)
f.write(rendered.replace("\n", "\n "))
else:
f.write(json.dumps(entry, ensure_ascii=False))
n_entries += 1
n_ent = len(entry.get("entities", []))
if n_ent:
with_entities += 1
total_entities += n_ent
f.write("\n ]\n}\n")
return n_entries, with_entities, total_entities
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