{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/3"},{"label":"Bio-Informatics","url":"https://skillfed.io/packages/category/scientific-engineering-bio-informatics"},{"label":"Medical Science Apps.","url":"https://skillfed.io/packages/category/scientific-engineering-medical-science-apps"}],"enrichment":{"capability":"Datamol provides a pythonic layer on top of RDKit for molecular manipulation, offering simplified APIs for converting between molecular formats, standardizing molecules, and performing common cheminformatics operations.","skillfed_tags":["cheminformatics","rdkit-wrapper","molecular-io"],"use_cases":["Convert SMILES strings to molecular objects and compute fingerprints for machine learning pipelines.","Standardize and sanitize molecular structures in bulk from CSV or SDF files stored locally or on cloud storage.","Generate 3D conformers and compute solvent-accessible surface area for molecular dynamics or docking studies.","Batch-process large molecular datasets with automatic parallelization and progress tracking.","Visualize molecular structures and conformers in Jupyter notebooks with built-in 2D and 3D rendering."],"what_it_does":"Datamol is a Python library that wraps RDKit to simplify molecular cheminformatics workflows. It exposes RDKit's core Mol objects through a more intuitive API, handling common tasks like SMILES parsing, molecular fingerprinting, conformer generation, and format conversion with sensible defaults. The library emphasizes ease of use while maintaining direct access to underlying RDKit objects, so you can drop down to RDKit when needed.\n\nIt includes built-in parallelization via joblib, remote file support through fsspec for reading and writing SDF, CSV, and other formats from cloud storage, and visualization tools. The package targets chemists and computational biologists working with small-molecule datasets, offering both batch operations on DataFrames and single-molecule transformations.","worth_installing":"Yes. Datamol is actively maintained, has no known vulnerabilities, and offers genuine convenience for RDKit-based workflows. Install it if you work with molecular structures and want a more ergonomic API than raw RDKit; the Apache-2.0 license poses no barrier. The main gotcha is rdkit's dependency chain\u2014use conda-forge for a smooth install."},"id":"datamol","links":{"html":"https://skillfed.io/packages/datamol","md":"https://skillfed.io/packages/datamol.md","pypi":"https://pypi.org/project/datamol/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2024-06-10","license_spdx":null,"license_treatment":"permissive","name":"datamol","python_support":"supports_current","summary":"A python library to work with molecules. Built on top of RDKit."},"popularity":{"monthly_downloads":103981,"position":12776,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.12.5"}