import argparse
import os
import selfies as sf
from tqdm import tqdm

def convert_file(input_file, verbose=False, batch_size=10000):
    base_name = os.path.splitext(input_file)[0]
    selfies_file = f"{base_name}.selfies"
    alphabet_file = f"{base_name}.alph"
    
    alphabet = set()
    total_lines = 0
    processed_lines = 0
    error_count = 0

    # Count total lines if verbose
    if verbose:
        with open(input_file, 'r') as fin:
            total_lines = sum(1 for _ in fin)

    with open(input_file, 'r') as fin, open(selfies_file, 'w') as fout:
        if verbose:
            pbar = tqdm(total=total_lines, desc=f"Converting {input_file}")

        batch = []
        for line in fin:
            # Truncate line at first whitespace
            smiles = line.split()[0]
            batch.append(smiles)
            if len(batch) == batch_size:
                error_count += process_batch(batch, fout, alphabet)
                processed_lines += len(batch)
                if verbose:
                    pbar.update(len(batch))
                batch = []

        # Process remaining lines
        if batch:
            error_count += process_batch(batch, fout, alphabet)
            processed_lines += len(batch)
            if verbose:
                pbar.update(len(batch))

        if verbose:
            pbar.close()

    with open(alphabet_file, 'w') as f:
        for symbol in sorted(alphabet):
            f.write(f"{symbol}\n")
    
    if verbose:
        print(f"Conversion complete. Processed {processed_lines} lines.")
        print(f"Encountered {error_count} errors during conversion.")
        print(f"SELFIES saved to {selfies_file}")
        print(f"Alphabet saved to {alphabet_file}")

def process_batch(batch, fout, alphabet):
    error_count = 0
    for smiles in batch:
        try:
            selfies = sf.encoder(smiles, strict=False)
            if selfies:  # Check if the SELFIES string is not empty
                fout.write(f"{selfies}\n")
                alphabet.update(sf.split_selfies(selfies))
            else:
                error_count += 1
        except sf.EncoderError:
            error_count += 1
    return error_count

def main():
    parser = argparse.ArgumentParser(description="SELFIES Converter")
    parser.add_argument("input_file", help="Input SMILES file (.smi)")
    parser.add_argument("-v", "--verbose", action="store_true", help="Increase output verbosity")
    parser.add_argument("-b", "--batch-size", type=int, default=10000, help="Batch size for processing")
    args = parser.parse_args()

    convert_file(args.input_file, args.verbose, args.batch_size)

if __name__ == "__main__":
    main()