GlycoShape_1

"""
pull_structures.py
----------------------------
Pulls all glycan structure files from GlycoShape API and uploads
to HuggingFace as a Parquet dataset.
Requirements:
    pip install requests huggingface_hub pyarrow tqdm
Usage:
    python pull_structures.py --repo your-username/GlycoShape
"""

import argparse, io, json, os, time, zipfile, requests
from pathlib import Path
import pyarrow as pa
import pyarrow.parquet as pq
from tqdm import tqdm
from huggingface_hub import HfApi

# ── Config ─────────────────────────────────────────────────────────────────────
BASE_URL   = "https://glycoshape.org/api"
BATCH_SIZE = 50        # write to parquet every N glycans (memory control)
SLEEP_SEC  = 0.3       # polite delay between requests
TIMEOUT    = 30        # seconds per request


# ── Fetch the full list of GlyTouCan IDs ───────────────────────────────
def fetch_available_ids() -> list[str]:
    print("Fetching GlyTouCan ID list from /api/available …")
    r = requests.get(f"{BASE_URL}/available", timeout=TIMEOUT)
    r.raise_for_status()
    ids = r.json()
    print(f"  → {len(ids)} glycans found")
    return ids


# ── Download ZIP and extract PDB files for a glycan ──────────────────
def download_structures(glycan_id: str) -> list[dict]:
    """
    Returns a list of records, one per PDB file inside the ZIP:
    {
        glytoucan_id : str   – GlyTouCan accession (e.g. "G00028MO")
        filename     : str   – original filename inside the ZIP
        file_type    : str   – extension: "pdb", "mol2", etc.
        cluster      : str   – cluster label parsed from filename (if present)
        pdb_content  : str   – full text content of the file
    }
    """
    url = f"{BASE_URL}/download/{glycan_id}"
    try:
        r = requests.get(url, timeout=60)
        r.raise_for_status()
    except requests.HTTPError as e:
        print(f"  HTTP error for {glycan_id}: {e}")
        return []
    except requests.RequestException as e:
        print(f"  Network error for {glycan_id}: {e}")
        return []

    records = []
    try:
        with zipfile.ZipFile(io.BytesIO(r.content)) as zf:
            for name in zf.namelist():
                ext = Path(name).suffix.lstrip(".").lower()
                if ext not in {"pdb", "mol2", "cif", "xyz"}:
                    continue  # skip non-structure files (logs, etc.)

                raw = zf.read(name)
                try:
                    content = raw.decode("utf-8")
                except UnicodeDecodeError:
                    content = raw.decode("latin-1")

                # Parse cluster label from filename, e.g. "cluster_1.pdb" → "1"
                stem = Path(name).stem
                cluster = ""
                for part in stem.replace("-", "_").split("_"):
                    if part.isdigit():
                        cluster = part
                        break

                records.append({
                    "glytoucan_id": glycan_id,
                    "filename":     name,
                    "file_type":    ext,
                    "cluster":      cluster,
                    "pdb_content":  content,
                })
    except zipfile.BadZipFile:
        print(f"  Bad ZIP for {glycan_id}")

    return records


# ── Write a batch of records to a Parquet shard ─────────────────────────
def write_parquet(records: list[dict], out_dir: Path, shard_idx: int) -> Path:
    schema = pa.schema([
        pa.field("glytoucan_id", pa.string()),
        pa.field("filename",     pa.string()),
        pa.field("file_type",    pa.string()),
        pa.field("cluster",      pa.string()),
        pa.field("pdb_content",  pa.large_string()),
    ])
    table    = pa.Table.from_pylist(records, schema=schema)
    out_path = out_dir / f"shard-{shard_idx:05d}.parquet"
    pq.write_table(table, out_path, compression="zstd")
    print(f"  → wrote {out_path.name}  ({len(records)} structure files)")
    return out_path

# ── Main ───────────────────────────────────────────────────────────────────────
def main():
    parser = argparse.ArgumentParser()
    parser.add_argument("--out-dir",      default="../data/structure_parquets/", help="Output dir for parquet shards (default: ../data/structure_parquets/)")
    parser.add_argument("--limit",        type=int, default=None,                help="Only process first N glycans (for testing)")
    parser.add_argument("--retry-failed", action="store_true",                   help="Retry only the IDs listed in failed_ids.json")
    args = parser.parse_args()

    out_dir = Path(args.out_dir)
    out_dir.mkdir(parents=True, exist_ok=True)

    # 1. Get IDs — either from failed_ids.json or the full API list
    if args.retry_failed:
        fail_path = out_dir / "failed_ids.json"
        if not fail_path.exists():
            print(f"No failed_ids.json found in {out_dir}")
            return
        all_ids = json.loads(fail_path.read_text())
        print(f"Retrying {len(all_ids)} previously failed glycans …")
    else:
        all_ids = fetch_available_ids()
        if args.limit:
            all_ids = all_ids[: args.limit]
            print(f"  (limited to first {args.limit} for testing)")

    # 2. Download + write in batches
    # Use a high shard_idx start when retrying so we don't overwrite existing shards
    batch:     list[dict] = []
    shard_idx: int        = len(list(out_dir.glob("shard-*.parquet")))
    failed:    list[str]  = []

    for glycan_id in tqdm(all_ids, desc="Downloading"):
        records = download_structures(glycan_id)
        if records:
            batch.extend(records)
        else:
            failed.append(glycan_id)

        if len(batch) >= BATCH_SIZE * 10:
            write_parquet(batch, out_dir, shard_idx)
            shard_idx += 1
            batch = []

        time.sleep(SLEEP_SEC)

    # flush remainder
    if batch:
        write_parquet(batch, out_dir, shard_idx)

    if failed:
        fail_path = out_dir / "failed_ids.json"
        fail_path.write_text(json.dumps(failed, indent=2))
        print(f"\n⚠ {len(failed)} glycans failed — saved to {fail_path}")
    elif args.retry_failed:
        # clean up failed_ids.json if everything succeeded this time
        (out_dir / "failed_ids.json").unlink(missing_ok=True)
        print("\n✓ All previously failed glycans downloaded successfully")


if __name__ == "__main__":
    main()

	"""
	pull_structures.py
	----------------------------
	Pulls all glycan structure files from GlycoShape API and uploads
	to HuggingFace as a Parquet dataset.

	Requirements:
	pip install requests huggingface_hub pyarrow tqdm

	Usage:
	python pull_structures.py --repo your-username/GlycoShape
	"""

	import argparse, io, json, os, time, zipfile, requests
	from pathlib import Path
	import pyarrow as pa
	import pyarrow.parquet as pq
	from tqdm import tqdm
	from huggingface_hub import HfApi

	# ── Config ─────────────────────────────────────────────────────────────────────
	BASE_URL = "https://glycoshape.org/api"
	BATCH_SIZE = 50 # write to parquet every N glycans (memory control)
	SLEEP_SEC = 0.3 # polite delay between requests
	TIMEOUT = 30 # seconds per request


	# ── Fetch the full list of GlyTouCan IDs ───────────────────────────────
	def fetch_available_ids() -> list[str]:
	print("Fetching GlyTouCan ID list from /api/available …")
	r = requests.get(f"{BASE_URL}/available", timeout=TIMEOUT)
	r.raise_for_status()
	ids = r.json()
	print(f" → {len(ids)} glycans found")
	return ids


	# ── Download ZIP and extract PDB files for a glycan ──────────────────
	def download_structures(glycan_id: str) -> list[dict]:
	"""
	Returns a list of records, one per PDB file inside the ZIP:
	{
	glytoucan_id : str – GlyTouCan accession (e.g. "G00028MO")
	filename : str – original filename inside the ZIP
	file_type : str – extension: "pdb", "mol2", etc.
	cluster : str – cluster label parsed from filename (if present)
	pdb_content : str – full text content of the file
	}
	"""
	url = f"{BASE_URL}/download/{glycan_id}"
	try:
	r = requests.get(url, timeout=60)
	r.raise_for_status()
	except requests.HTTPError as e:
	print(f" HTTP error for {glycan_id}: {e}")
	return []
	except requests.RequestException as e:
	print(f" Network error for {glycan_id}: {e}")
	return []

	records = []
	try:
	with zipfile.ZipFile(io.BytesIO(r.content)) as zf:
	for name in zf.namelist():
	ext = Path(name).suffix.lstrip(".").lower()
	if ext not in {"pdb", "mol2", "cif", "xyz"}:
	continue # skip non-structure files (logs, etc.)

	raw = zf.read(name)
	try:
	content = raw.decode("utf-8")
	except UnicodeDecodeError:
	content = raw.decode("latin-1")

	# Parse cluster label from filename, e.g. "cluster_1.pdb" → "1"
	stem = Path(name).stem
	cluster = ""
	for part in stem.replace("-", "_").split("_"):
	if part.isdigit():
	cluster = part
	break

	records.append({
	"glytoucan_id": glycan_id,
	"filename": name,
	"file_type": ext,
	"cluster": cluster,
	"pdb_content": content,
	})
	except zipfile.BadZipFile:
	print(f" Bad ZIP for {glycan_id}")

	return records


	# ── Write a batch of records to a Parquet shard ─────────────────────────
	def write_parquet(records: list[dict], out_dir: Path, shard_idx: int) -> Path:
	schema = pa.schema([
	pa.field("glytoucan_id", pa.string()),
	pa.field("filename", pa.string()),
	pa.field("file_type", pa.string()),
	pa.field("cluster", pa.string()),
	pa.field("pdb_content", pa.large_string()),
	])
	table = pa.Table.from_pylist(records, schema=schema)
	out_path = out_dir / f"shard-{shard_idx:05d}.parquet"
	pq.write_table(table, out_path, compression="zstd")
	print(f" → wrote {out_path.name} ({len(records)} structure files)")
	return out_path

	# ── Main ───────────────────────────────────────────────────────────────────────
	def main():
	parser = argparse.ArgumentParser()
	parser.add_argument("--out-dir", default="../data/structure_parquets/", help="Output dir for parquet shards (default: ../data/structure_parquets/)")
	parser.add_argument("--limit", type=int, default=None, help="Only process first N glycans (for testing)")
	parser.add_argument("--retry-failed", action="store_true", help="Retry only the IDs listed in failed_ids.json")
	args = parser.parse_args()

	out_dir = Path(args.out_dir)
	out_dir.mkdir(parents=True, exist_ok=True)

	# 1. Get IDs — either from failed_ids.json or the full API list
	if args.retry_failed:
	fail_path = out_dir / "failed_ids.json"
	if not fail_path.exists():
	print(f"No failed_ids.json found in {out_dir}")
	return
	all_ids = json.loads(fail_path.read_text())
	print(f"Retrying {len(all_ids)} previously failed glycans …")
	else:
	all_ids = fetch_available_ids()
	if args.limit:
	all_ids = all_ids[: args.limit]
	print(f" (limited to first {args.limit} for testing)")

	# 2. Download + write in batches
	# Use a high shard_idx start when retrying so we don't overwrite existing shards
	batch: list[dict] = []
	shard_idx: int = len(list(out_dir.glob("shard-*.parquet")))
	failed: list[str] = []

	for glycan_id in tqdm(all_ids, desc="Downloading"):
	records = download_structures(glycan_id)
	if records:
	batch.extend(records)
	else:
	failed.append(glycan_id)

	if len(batch) >= BATCH_SIZE * 10:
	write_parquet(batch, out_dir, shard_idx)
	shard_idx += 1
	batch = []

	time.sleep(SLEEP_SEC)

	# flush remainder
	if batch:
	write_parquet(batch, out_dir, shard_idx)

	if failed:
	fail_path = out_dir / "failed_ids.json"
	fail_path.write_text(json.dumps(failed, indent=2))
	print(f"\n⚠ {len(failed)} glycans failed — saved to {fail_path}")
	elif args.retry_failed:
	# clean up failed_ids.json if everything succeeded this time
	(out_dir / "failed_ids.json").unlink(missing_ok=True)
	print("\n✓ All previously failed glycans downloaded successfully")


	if __name__ == "__main__":
	main()