Datasets:
File size: 4,112 Bytes
5798cd6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 | #!/usr/bin/env python3
"""Summarize MedWeave image coverage and export external-image mappings."""
from __future__ import annotations
import argparse
import csv
import glob
import json
from collections import Counter, defaultdict
from pathlib import Path
from typing import Any
def read_jsonl(path: Path):
with path.open(encoding="utf-8") as handle:
for line in handle:
if line.strip():
yield json.loads(line)
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--repo-root", type=Path, default=Path("."))
parser.add_argument("--csv", type=Path, default=None)
parser.add_argument(
"--all",
action="store_true",
help="Include redistributed assets in the CSV (default: external only)",
)
args = parser.parse_args()
root = args.repo_root.resolve()
manifest_path = root / "image_manifests" / "all.jsonl"
assets = {row["sha256"]: row for row in read_jsonl(manifest_path)}
question_counts: Counter[str] = Counter()
example_ids: dict[str, list[str]] = defaultdict(list)
domain_rows: Counter[str] = Counter()
data_paths = sorted(Path(path) for path in glob.glob(str(root / "data" / "*" / "test-*.jsonl")))
if not data_paths:
raise FileNotFoundError(f"No QA shards found below {root / 'data'}")
for path in data_paths:
domain = path.parent.name
for row in read_jsonl(path):
digest = row.get("image_sha256")
if not digest:
continue
question_counts[digest] += 1
domain_rows[domain] += 1
if len(example_ids[digest]) < 3:
example_ids[digest].append(str(row["id"]))
source_asset_counts: Counter[str] = Counter()
source_question_counts: Counter[str] = Counter()
available_assets = 0
external_assets = 0
output_rows: list[dict[str, Any]] = []
for digest, row in sorted(assets.items()):
available = bool(row.get("available_on_hub"))
if available:
available_assets += 1
else:
external_assets += 1
sources = [str(value) for value in row.get("source_datasets", [])]
if not available:
for source in sources:
source_asset_counts[source] += 1
source_question_counts[source] += question_counts[digest]
if args.all or not available:
output_rows.append(
{
"specialty": row.get("specialty", ""),
"source_datasets": ";".join(sources),
"expected_path": row["expected_path"],
"sha256": digest,
"source_references": ";".join(row.get("source_references", [])),
"available_on_hub": available,
"distribution_status": row.get("distribution_status", ""),
"affected_questions": question_counts[digest],
"example_question_ids": ";".join(example_ids[digest]),
}
)
summary = {
"qa_rows_with_images_by_domain": dict(sorted(domain_rows.items())),
"assets_total": len(assets),
"assets_available_on_hub": available_assets,
"assets_external": external_assets,
"external_by_source": {
source: {
"assets": source_asset_counts[source],
"affected_questions": source_question_counts[source],
}
for source in sorted(source_asset_counts)
},
}
print(json.dumps(summary, indent=2, sort_keys=True))
if args.csv:
args.csv.parent.mkdir(parents=True, exist_ok=True)
fieldnames = list(output_rows[0]) if output_rows else []
with args.csv.open("w", encoding="utf-8", newline="") as handle:
writer = csv.DictWriter(handle, fieldnames=fieldnames)
writer.writeheader()
writer.writerows(output_rows)
print(json.dumps({"csv": str(args.csv), "rows": len(output_rows)}, sort_keys=True))
if __name__ == "__main__":
main()
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