$ show openmm/spice-dataset
This repository provides the SPICE dataset, a collection of molecular structures and properties for machine learning and molecular simulation. It includes precomputed HDF5 files for amino acid ligands, the DES370K set of small organic molecules, dipeptides, ions, PubChem compounds, solvated amino acids, water clusters, and more. The accompanying Python scripts generate these datasets from raw SDF and PDB files, performing tasks such as molecular filtering, energy computation, and solvation. The repository is primarily a data resource rather than a software application, with scripts that are tightly coupled to the specific dataset generation pipeline. It lacks dependency pinning and formal testing, but the data files are directly usable for training and benchmarking molecular models.
The LLM identified 3 files worth highlighting for reuse:
A generic downloader script that likely handles fetching raw molecular data from external sources. It is parameterized via config.yaml and could be adapted to download other datasets with minimal changes, demonstrating a reusable ETL pattern.
Processes SDF files to extract molecular structures and properties. This script encapsulates common SDF parsing and filtering logic that can be reused for any SDF-based dataset, making it a valuable reusable data asset.
A job submission script that likely interfaces with a cluster scheduler (e.g., SLURM) to run computational chemistry tasks. It abstracts submission logic and can be repurposed for other batch processing workflows, demonstrating a reusable automation pattern.