Wrap RDKit with a Pythonic API for cheminformatics tasks.
npx skills add https://github.com/mkurman/tamux --skill datamol-mkurman
Please help me install this Agent Skill. Skill: datamol Source: https://github.com/mkurman/tamux/tree/main/skills/scientific-skills/datamol Command: npx skills add https://github.com/mkurman/tamux --skill datamol-mkurman
Datamol provides a clean, Pythonic interface that wraps RDKit, reducing boilerplate and accelerating cheminformatics workflows.
Install datamol, import it as dm, and start by converting a SMILES string to a molecule with to_mol.
High-intent search queries and answers about installing and using this skill.
You can simplify RDKit cheminformatics workflows by using a Pythonic wrapper that reduces boilerplate for molecule creation, standardization, and descriptor calculation across datasets.
Calculating molecular descriptors and fingerprints from SMILES strings is done by converting the text to a molecule object, then applying modular functions for batch processing and structural feature extraction.
Generating 3D conformers and performing scaffold analysis is supported natively, allowing you to process fragments and generate spatial configurations without extensive manual RDKit code.
Cloud storage integration for remote datasets is supported via fsspec, enabling lightweight data I/O and batch processing of molecular files directly from remote environments.
A Pythonic RDKit wrapper provides a cleaner interface compared to raw RDKit, accelerating molecule standardization and conversion tasks by minimizing boilerplate code in data pipelines.
dralkhStandardize and analyze molecular structures with RDKit for cheminformatics workflows.
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K-Dense-AISimplify RDKit-based cheminformatics workflows with a Pythonic wrapper.
