import os import random import shutil import argparse from pathlib import Path from tqdm import tqdm def SplitDataset(dataset_name: str, dataset_dir: str, val_ratio: float, seed: int = 42): # Validate ratio if not 0 < val_ratio < 1: raise ValueError("Validation split ratio (--split) must be between 0 and 1 (exclusive).") # Set paths dataset_path = Path(dataset_dir) / dataset_name train_path = dataset_path / "Train" val_path = dataset_path / "Val" # Validate dataset directory if not dataset_path.exists(): raise FileNotFoundError(f"Dataset folder '{dataset_path}' not found.") # Create Train/Val subfolders train_path.mkdir(exist_ok=True) val_path.mkdir(exist_ok=True) # Find .parquet files parquet_files = [f for f in dataset_path.glob("*.parquet")] if not parquet_files: raise ValueError(f"No .parquet files found in '{dataset_path}'.") # Shuffle files deterministically random.seed(seed) random.shuffle(parquet_files) # Split into train and val val_count = int(len(parquet_files) * val_ratio) val_files = parquet_files[:val_count] train_files = parquet_files[val_count:] print(f"📦 Found {len(parquet_files)} parquet files in '{dataset_name}'") print(f"🔀 Splitting {val_count} to 'Val' ({val_ratio:.0%}) and {len(train_files)} to 'Train'") # Move files to Val for file in tqdm(val_files, desc="📁 Moving to Val", unit="file"): shutil.move(str(file), str(val_path / file.name)) # Move files to Train for file in tqdm(train_files, desc="📁 Moving to Train", unit="file"): shutil.move(str(file), str(train_path / file.name)) print("✅ Split complete.") if __name__ == "__main__": parser = argparse.ArgumentParser(description="Split a dataset of .parquet files into Train and Val sets.") parser.add_argument( "-n", "--dataset_name", required=True, type=str, help="Name of the dataset folder inside the dataset directory." ) parser.add_argument( "-d", "--dataset_dir", default="./src/Datasets", type=str, help="Path to the parent directory containing dataset folders. Default is './src/Datasets'." ) parser.add_argument( "-s", "--split", default=0.1, type=float, help="Fraction of files to use for validation (between 0 and 1). Default is 0.1 (10%)." ) args = parser.parse_args() SplitDataset(args.dataset_name, args.dataset_dir, args.split)