Individual skill
datamol
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
skills/datamol/SKILL.md
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- Last checked
- Nov 10, 2026
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- Repository last updated
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- License
- MIT
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- ai-scientist Repository topic
- bioinformatics Repository topic
- chemoinformatics Repository topic
- claude Repository topic
- claude-skills Repository topic
- claudecode Repository topic
- clinical-research Repository topic
- computational-biology Repository topic
- data-analysis Repository topic
- drug-discovery Repository topic
- engineering Derived category
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# Datamol Cheminformatics Skill
## Overview
Datamol is a Python library that provides a lightweight, Pythonic abstraction layer over RDKit for molecular cheminformatics. Simplify complex molecular operations with sensible defaults, efficient parallelization, and modern I/O capabilities. All molecular objects are native `rdkit.Chem.Mol` instances, ensuring full compatibility with the RDKit ecosystem.
**Verified target:** datamol **0.13.0**, released September 9, 2026. Local checks used
Python 3.13 and RDKit 2026.03.6. Python 3.11+ and RDKit 2024.09+ are required.
The 0.13 distribution includes SELFIES, visualization, cloud, Excel and Parquet
runtime dependencies. Current API examples and verification limits are recorded in
[references/review.md](references/review.md). Pin the environment: RDKit upgrades can
change canonical representations and retained conformers. Compare chemical invariants,
not a fixed conformer count or an exact version-dependent canonical string.
