Spaces:
No application file
No application file
File size: 2,396 Bytes
96d8696 | 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 | #!/usr/bin/env python
"""Stage 01 — preprocess.
Reads data/raw/{train,test}.csv, cleans text, downloads + resizes images.
Writes data/processed/{train,test}_clean.parquet and data/processed/images/.
Usage:
python scripts/01_preprocess.py --config configs/base.yaml
"""
import argparse
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
from src.data.image_pipeline import process_batch
from src.data.loader import load_test, load_train
from src.data.text_cleaning import clean_dataframe
from src.utils.config import load_config
from src.utils.exceptions import PricePredictorError
from src.utils.logging import get_logger
from src.utils.seed import set_seed
logger = get_logger(__name__)
def run(config_path: str) -> None:
config = load_config(config_path)
set_seed(config["seed"])
data_cfg = config["data"]
processed_dir = Path(data_cfg["processed_dir"])
processed_dir.mkdir(parents=True, exist_ok=True)
for split, loader_fn, csv_key in [("train", load_train, "train_csv"), ("test", load_test, "test_csv")]:
logger.info("=== Preprocessing split: %s ===", split)
df = loader_fn(data_cfg[csv_key])
df = clean_dataframe(df, column="catalog_content")
image_dir = processed_dir / "images" / split
results = process_batch(
urls=df["image_link"].tolist(),
output_dir=str(image_dir),
size=data_cfg["image_size"],
max_workers=data_cfg.get("image_download_workers", 16),
)
df["image_path"] = [r["path"] for r in results]
df["image_is_placeholder"] = [r["placeholder"] for r in results]
out_path = processed_dir / f"{split}_clean.parquet"
df.to_parquet(out_path, index=False)
logger.info("Wrote %s (%d rows)", out_path, len(df))
def main() -> None:
parser = argparse.ArgumentParser(description="Stage 01: preprocess raw data")
parser.add_argument("--config", default="configs/base.yaml")
args = parser.parse_args()
try:
run(args.config)
except PricePredictorError as e:
logger.error("Preprocessing failed: %s", e)
sys.exit(1)
except Exception as e: # unexpected — still fail loudly with context
logger.exception("Unexpected error during preprocessing: %s", e)
sys.exit(1)
if __name__ == "__main__":
main()
|