datamol
Wraps RDKit through the datamol Python library (import datamol as dm) for molecular cheminformatics, returning native rdkit.Chem.Mol objects. Covers SMILES/SELFIES/InChI conversion, sanitization and standardization, descriptors, fingerprints and similarity, Butina clustering and diverse subset picking, Bemis-Murcko scaffolds, BRICS/RECAP fragmentation, 3D conformers, reactions, SDF/CSV/Excel I/O including cloud paths, and parallel batch processing. Use when parsing or standardizing SMILES from external sources, computing descriptors or fingerprints for a compound library, clustering or selecting diverse molecules, making scaffold-based train/test splits, or generating conformers. Use when running a molecule-processing pipeline with n_jobs. For fine-grained control or custom parameters, use RDKit directly instead.
- Version
- 1.2
- License
- Apache-2.0 license
- 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 df088027ff23, 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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