datamol
Pythonic wrapper around RDKit with a simplified interface and sensible defaults. Preferred for standard drug discovery work — SMILES/SELFIES/InChI conversion, molecule standardization and sanitization, descriptors, ECFP and other fingerprints, Tanimoto distance matrices, Butina clustering and diverse subset picking, Bemis-Murcko scaffolds and scaffold splits, BRICS/RECAP fragmentation, 3D conformer generation, SDF/CSV/Excel and cloud I/O, and parallel processing via n_jobs. Returns native rdkit.Chem.Mol objects, so it composes with RDKit throughout. Also trigger on datamol, import datamol as dm, dm.to_mol, dm.standardize_mol, dm.cluster_mols, or dm.pick_diverse. For advanced control or custom parameters, use the rdkit skill directly.
- Version
- 1.2
- License
- MIT
- Compatibility
- Requires Python 3.8+ and datamol (uv pip install). RDKit is installed automatically as a datamol dependency (since 0.12.2). Optional s3fs/gcsfs for cloud I/O via fsspec.
Pinned to revision f67572246d9b, so it is the text this page describes rather than whatever the author pushed since.
Pre-approved tools experimental
Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.
- Read
- Write
- Edit
- Bash
Files
- skills/datamol/SKILL.md
- skills/datamol/references/conformers_module.md
- skills/datamol/references/core_api.md
- skills/datamol/references/core_workflows.md
- skills/datamol/references/descriptors_viz.md
- skills/datamol/references/fragments_scaffolds.md
- skills/datamol/references/io_module.md
- skills/datamol/references/reactions_data.md
- skills/datamol/references/workflow_patterns.md
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