Datasets:
Formats:
parquet
Languages:
English
Size:
10M - 100M
Tags:
biology
chemistry
drug-discovery
clinical-trials
protein-protein-interaction
gene-essentiality
License:
File size: 3,908 Bytes
6d1bbc7 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 | """Download AACT pipe-delimited snapshot from CTTI.
Downloads ~2.23 GB ZIP and extracts only the 13 needed tables
into data/ct/aact/ as pipe-delimited .txt files.
AACT (Aggregate Analysis of ClinicalTrials.gov) is maintained by
Duke/CTTI. Data is public domain (US government data).
Source: https://aact.ctti-clinicaltrials.org/pipe_files
Format: ZIP containing pipe-delimited .txt files (one per table)
Usage:
python scripts_ct/download_aact.py [--url URL]
"""
import argparse
import zipfile
from pathlib import Path
from negbiodb.download import (
check_disk_space,
download_file_http,
load_config,
verify_file_exists,
)
def extract_needed_tables(
zip_path: Path,
dest_dir: Path,
table_names: list[str],
) -> dict[str, Path]:
"""Extract only the needed tables from AACT ZIP.
AACT ZIP contains files named like 'studies.txt', 'interventions.txt'.
Returns dict mapping table_name -> extracted file path.
"""
dest_dir.mkdir(parents=True, exist_ok=True)
extracted = {}
with zipfile.ZipFile(zip_path, "r") as zf:
all_names = zf.namelist()
for table in table_names:
fname = f"{table}.txt"
matches = [n for n in all_names if n.endswith(fname)]
if not matches:
print(f" WARNING: {fname} not found in ZIP")
continue
# Use the first match (handles subdirectories in ZIP)
member = matches[0]
dest_file = dest_dir / fname
if dest_file.exists() and dest_file.stat().st_size > 0:
print(f" Already extracted: {fname}")
else:
print(f" Extracting: {member} -> {fname}")
with zf.open(member) as src, open(dest_file, "wb") as dst:
dst.write(src.read())
extracted[table] = dest_file
size_mb = dest_file.stat().st_size / (1024**2)
print(f" {fname}: {size_mb:.1f} MB")
return extracted
def main():
parser = argparse.ArgumentParser(
description="Download AACT pipe-delimited snapshot"
)
parser.add_argument(
"--url",
type=str,
default=None,
help="Direct URL to AACT ZIP (overrides scraping)",
)
args = parser.parse_args()
cfg = load_config()
dl = cfg["ct_domain"]["downloads"]["aact"]
dest_dir = Path(dl["dest_dir"])
required_disk_gb = dl["required_disk_gb"]
tables = dl["tables"]
print("=== AACT Pipe Files Download ===")
print(f"Dest dir: {dest_dir}")
print(f"Tables: {len(tables)}")
check_disk_space(dest_dir, required_disk_gb)
# Determine URL
if args.url:
url = args.url
else:
print(
"\nAACT download URL changes monthly. Provide via --url flag."
"\nGet the latest URL from: "
"https://aact.ctti-clinicaltrials.org/pipe_files"
"\n\nExample:"
"\n python scripts_ct/download_aact.py --url "
'"https://ctti-aact.nyc3.digitaloceanspaces.com/..."'
)
return
# Download ZIP
zip_path = dest_dir / "aact_pipe_files.zip"
download_file_http(url, zip_path, desc="AACT pipe files")
if not verify_file_exists(zip_path, min_bytes=100_000_000):
raise ValueError(f"AACT ZIP too small or missing: {zip_path}")
# Extract needed tables
print(f"\nExtracting {len(tables)} tables from ZIP...")
extracted = extract_needed_tables(zip_path, dest_dir, tables)
print(f"\n=== AACT Download Summary ===")
print(f"ZIP size: {zip_path.stat().st_size / (1024**3):.2f} GB")
print(f"Tables extracted: {len(extracted)} / {len(tables)}")
missing = set(tables) - set(extracted.keys())
if missing:
print(f"MISSING tables: {', '.join(sorted(missing))}")
print("\nAACT download complete.")
if __name__ == "__main__":
main()
|