feat(toolkit): ship macro_lactone_toolkit package
Unify macrolactone detection, numbering, fragmentation, and splicing under the installable macro_lactone_toolkit package. - replace legacy src.* modules with the new package layout - add analyze/number/fragment CLI entrypoints and pixi tasks - migrate tests, README, and scripts to the new package API
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@@ -1,165 +1,10 @@
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"""
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Batch processing script for analyzing all macrolactones in the dataset.
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"""
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from __future__ import annotations
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import sys
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sys.path.append('..')
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import pandas as pd
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from pathlib import Path
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from tqdm import tqdm
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import json
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from rdkit import Chem
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from src.fragment_cleaver import process_molecule
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from src.fragment_dataclass import MoleculeFragments
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def batch_process_molecules(csv_path: str, output_base_dir: str,
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max_molecules: int = None):
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"""
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Process all molecules in the CSV file.
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Args:
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csv_path: Path to the CSV file containing SMILES
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output_base_dir: Base directory for output
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max_molecules: Maximum number of molecules to process (None for all)
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"""
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# Read CSV
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df = pd.read_csv(csv_path)
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print(f"Loaded {len(df)} molecules from {csv_path}")
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if max_molecules:
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df = df.head(max_molecules)
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print(f"Processing first {max_molecules} molecules")
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# Create output directory
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output_dir = Path(output_base_dir)
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output_dir.mkdir(parents=True, exist_ok=True)
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# Statistics
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successful = 0
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failed = 0
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failed_molecules = []
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all_fragments = []
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# Process each molecule
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for idx, row in tqdm(df.iterrows(), total=len(df), desc="Processing molecules"):
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smiles = row['smiles']
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molecule_id = row.get('IDs', f'molecule_{idx}')
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try:
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# Process molecule
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mol_fragments = process_molecule(smiles, idx)
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if mol_fragments is None or len(mol_fragments.fragments) == 0:
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failed += 1
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failed_molecules.append({
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'index': idx,
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'id': molecule_id,
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'reason': 'No fragments extracted'
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})
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continue
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# Create output directory for this molecule
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mol_output_dir = output_dir / mol_fragments.parent_id
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mol_output_dir.mkdir(parents=True, exist_ok=True)
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# Save complete molecule fragments
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mol_fragments_path = mol_output_dir / f"{mol_fragments.parent_id}_all_fragments.json"
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mol_fragments.to_json_file(str(mol_fragments_path))
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# Save individual fragments
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for frag in mol_fragments.fragments:
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frag_path = mol_output_dir / f"{frag.fragment_id}.json"
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frag.to_json_file(str(frag_path))
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# Collect for overall statistics
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all_fragments.append({
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'parent_id': frag.parent_id,
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'fragment_id': frag.fragment_id,
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'cleavage_position': frag.cleavage_position,
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'fragment_smiles': frag.fragment_smiles,
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'atom_count': frag.atom_count,
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'molecular_weight': frag.molecular_weight,
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'parent_smiles': frag.parent_smiles
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})
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successful += 1
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except Exception as e:
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failed += 1
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failed_molecules.append({
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'index': idx,
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'id': molecule_id,
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'error': str(e)
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})
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print(f"\nError processing molecule {idx} ({molecule_id}): {e}")
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# Save overall statistics
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stats = {
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'total_molecules': len(df),
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'successful': successful,
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'failed': failed,
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'total_fragments': len(all_fragments),
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'failed_molecules': failed_molecules
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}
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stats_path = output_dir / 'processing_stats.json'
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with open(stats_path, 'w') as f:
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json.dump(stats, f, indent=2)
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# Save all fragments as CSV for easy analysis
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if all_fragments:
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fragments_df = pd.DataFrame(all_fragments)
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fragments_csv_path = output_dir / 'all_fragments.csv'
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fragments_df.to_csv(fragments_csv_path, index=False)
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print(f"\n✓ Saved all fragments to: {fragments_csv_path}")
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# Print summary
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print(f"\n{'='*60}")
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print(f"PROCESSING COMPLETE")
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print(f"{'='*60}")
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print(f"Total molecules: {len(df)}")
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print(f"Successfully processed: {successful}")
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print(f"Failed: {failed}")
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print(f"Total fragments extracted: {len(all_fragments)}")
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print(f"{'='*60}")
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print(f"\nResults saved to: {output_dir}")
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print(f"Statistics saved to: {stats_path}")
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return fragments_df if all_fragments else None
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from macro_lactone_toolkit.cli import main
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if __name__ == "__main__":
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import argparse
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parser = argparse.ArgumentParser(
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description="Batch process macrolactones to extract side chain fragments"
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)
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parser.add_argument(
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'--input',
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type=str,
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default='../ring16/temp.csv',
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help='Input CSV file path'
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)
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parser.add_argument(
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'--output',
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type=str,
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default='../output/fragments',
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help='Output directory path'
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)
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parser.add_argument(
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'--max',
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type=int,
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default=None,
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help='Maximum number of molecules to process (default: all)'
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)
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args = parser.parse_args()
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batch_process_molecules(
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csv_path=args.input,
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output_base_dir=args.output,
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max_molecules=args.max
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)
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sys.argv = ["macro-lactone-toolkit", "fragment", *sys.argv[1:]]
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main()
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