molfeat

npx skills add K-Dense-AI/scientific-agent-skills --skill molfeat --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

# Molfeat - Molecular Featurization Hub ## Overview Molfeat is a comprehensive Python library for molecular featurization that unifies 100+ pre-trained embeddings and hand-crafted featurizers. Convert chemical structures (SMILES strings or RDKit molecules) into numerical representations for machine learning tasks including QSAR modeling, virtual screening, similarity searching, and deep learning applications. Features fast parallel processing, scikit-learn compatible transformers, and built-in caching. **Version note:** Examples target **molfeat 0.11.0** (PyPI stable, May 2025). Requires **Python 3.9–3.10** (`requires-python` caps below 3.11). Depends on **datamol ≥0.8.0** and **PyTorch ≥1.13**. Since 0.8.7, prefer datamol `Mol` objects over raw `rdkit.Chem.Mol`. Since 0.10.1, fingerprint calculators use RDKit's `rdFingerprintGenerator` API internally. Since 0.11.0, pretrained models load in memory and base models are set to PyTorch evaluation mode automatically. ## When to Use This Skill This skill should be used when working with: - **Molecular machine learning**: Building QSAR/QSPR models, property prediction - **Virtual screening**: Ranking compound libraries for biological act

uv pip install "molfeat==0.11.0"
With all pip-installable optional dependencies
uv pip install "molfeat[all]==0.11.0"
grep -i "chembert" references/available_featurizers.md
grep -i "pharmacophore" references/available_featurizers.md
uv pip install "molfeat[transformer]==0.11.0"  # For ChemBERTa/ChemGPT
uv pip install "molfeat[dgl]==0.11.0"          # For GIN models
uv pip install "molfeat[graphormer]==0.11.0"   # For Graphormer