src/02_process_batch.py

import pandas as pd
import argparse
import os

def safe_float(value):
    try:
        # Handle malformed scientific notation like 2.1997*^-6
        clean_value = value.replace("*^-", "e-").replace("*^", "e")
        return float(clean_value)
    except Exception as e:
        raise ValueError(f"Failed to parse float from '{value}': {e}")

def process_xyz(filepath):
    data = {}
    with open(filepath, 'r') as f:
        lines = f.readlines()

    data["n_atoms"] = int(lines[0].strip())
    values = lines[1].split()
    data["ID"] = values[1]

    #data["SMILES_GDB17"], data["SMILES_B3LYP"] = lines[-2].strip().split()
    data["SMILES_GDB17"] = lines[-2].strip().split()[0]


    data["Rotational_Constant_A"] = safe_float(values[2])
    data["Rotational_Constant_B"] = safe_float(values[3])
    data["Rotational_Constant_C"] = safe_float(values[4])
    data["Dipole_Moment"] = safe_float(values[5])
    data["Isotropic_polarizability"] = safe_float(values[6])
    data["Energy_of_HOMO"] = safe_float(values[7])
    data["Energy_of_LUMO"] = safe_float(values[8])
    data["LUMO_HOMO_GAP"] = safe_float(values[9])
    data["Electronic_spatial_extent"] = safe_float(values[10])
    data["Zero_point_vibrational_energy"] = safe_float(values[11])
    data["Internal_energy_at_0_K"] = safe_float(values[12])
    data["Internal_energy_at_298.15_K"] = safe_float(values[13])
    data["Enthalpy_at_298.15_K"] = safe_float(values[14])
    data["Free_energy_at_298.15_K"] = safe_float(values[15])
    data["Heat_capacity_at_298.15_K"] = safe_float(values[16])

    for i in range(data["n_atoms"]):
        atom = lines[2 + i].split()
        data[f"element_{i}"] = atom[0]
        data[f"x_{i}"] = safe_float(atom[1])
        data[f"y_{i}"] = safe_float(atom[2])
        data[f"z_{i}"] = safe_float(atom[3])
        data[f"charge_{i}"] = safe_float(atom[4])


    return data


def main():
    parser = argparse.ArgumentParser()
    parser.add_argument("--file_list", required=True, help="Path to .txt file listing input .xyz files")
    parser.add_argument("--output_file", required=True, help="Path to output .parquet file (checkpointed)")
    parser.add_argument("--checkpoint_every", type=int, default=100, help="Save after every N molecules")
    args = parser.parse_args()
    print("Processing",args.file_list)
    with open(args.file_list, 'r') as f:
        files = [line.strip() for line in f if line.strip()]

    records = {}
    for i, path in enumerate(files):
        try:
            data = process_xyz(path)
            n_atoms=data["n_atoms"]
            records[n_atoms]=data
        except Exception as e:
            print(f" Failed on {path}: {e}")

        if (i + 1) % args.checkpoint_every == 0:
            df = pd.DataFrame(records)
            df.to_parquet(args.output_file, index=False)
            print(f"Checkpointed {len(df)} molecules at {i+1}/{len(files)}")

    # Final save
    if records:
        df = pd.DataFrame(records)
        df.to_parquet(args.output_file, index=False)
        print(f" Final write: {len(df)} molecules → {args.output_file}")
    else:
        print(" No valid data to save.")


if __name__ == "__main__":
    main()