Metadata-Version: 2.1
Name: datamol
Version: 0.3.6
Summary: A python library to work with molecules. Built on top of RDKit.
Home-page: https://github.com/datamol-org/datamol
Author: Valence Discovery
Author-email: hadrien@valencediscovery.com
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/datamol-org/datamol/issues
Project-URL: Documentation, https://doc.datamol.io
Project-URL: Source Code, https://github.com/datamol-org/datamol
Description: <div align="center">
            <img src="docs/images/logo-title.png" height="80px">
            <h3>Molecular Manipulation Made Easy</h3>
        </div>
        
        ---
        
        [![Binder](http://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/datamol-org/datamol/master?urlpath=lab/tree/docs/tutorials/The_Basics.ipynb)
        [![PyPI](https://img.shields.io/pypi/v/datamol)](https://pypi.org/project/datamol/)
        [![Conda](https://img.shields.io/conda/v/conda-forge/datamol?label=conda&color=success)](https://anaconda.org/conda-forge/datamol)
        [![PyPI - Downloads](https://img.shields.io/pypi/dm/datamol)](https://pypi.org/project/datamol/)
        [![Conda](https://img.shields.io/conda/dn/conda-forge/datamol)](https://anaconda.org/conda-forge/datamol)
        [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/datamol)](https://pypi.org/project/datamol/)
        [![license](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/datamol-org/datamol/blob/master/LICENSE)
        [![GitHub Repo stars](https://img.shields.io/github/stars/datamol-org/datamol)](https://github.com/datamol-org/datamol/stargazers)
        [![GitHub Repo stars](https://img.shields.io/github/forks/datamol-org/datamol)](https://github.com/datamol-org/datamol/network/members)
        
        Datamol is a python library to work with molecules. It's a layer built on top of [RDKit](https://www.rdkit.org/) and aims to be as light as possible.
        
        - 🐍 Simple pythonic API
        - ⚗️ RDKit first: all you manipulate are `rdkit.Chem.Mol` objects.
        - ✅ Manipulating molecules often rely on many options; Datamol provides good defaults by design.
        - 🧠 Performance matters: built-in efficient parallelization when possible with optional progress bar.
        - 🕹️ Modern IO: out-of-the-box support for remote paths using `fsspec` to read and write multiple formats (sdf, xlsx, csv, etc).
        
        ## Try Online
        
        Visit [![Binder](http://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/datamol-org/datamol/master?urlpath=lab/tree/docs/tutorials/The_Basics.ipynb) and try Datamol online.
        
        ## Documentation
        
        Visit https://doc.datamol.io.
        
        ## Installation
        
        Use conda:
        
        ```bash
        mamba install -c conda-forge datamol
        ```
        
        ## Quick API Tour
        
        ```python
        import datamol as dm
        
        # Common functions
        mol = dm.to_mol("O=C(C)Oc1ccccc1C(=O)O", sanitize=True)
        fp = dm.to_fp(mol)
        selfies = dm.to_selfies(mol)
        inchi = dm.to_inchi(mol)
        
        # Standardize and sanitize
        mol = dm.to_mol("O=C(C)Oc1ccccc1C(=O)O")
        mol = dm.fix_mol(mol)
        mol = dm.sanitize_mol(mol)
        mol = dm.standardize_mol(mol)
        
        # Dataframe manipulation
        df = dm.data.freesolv()
        mols = dm.from_df(df)
        
        # 2D viz
        legends = [dm.to_smiles(mol) for mol in mols[:10]]
        dm.viz.to_image(mols[:10], legends=legends)
        
        # Generate conformers
        smiles = "O=C(C)Oc1ccccc1C(=O)O"
        mol = dm.to_mol(smiles)
        mol_with_conformers = dm.conformers.generate(mol)
        
        # 3D viz (using nglview)
        dm.viz.conformers(mol, n_confs=10)
        
        # Compute SASA from conformers
        sasa = dm.conformers.sasa(mol_with_conformers)
        
        # Easy IO
        mols = dm.read_sdf("s3://my-awesome-data-lake/smiles.sdf", as_df=False)
        dm.to_sdf(mols, "gs://data-bucket/smiles.sdf")
        ```
        
        ## Compatibilities
        
        Version compatibilities are an essential topic for production-software stacks. We are cautious about documenting compatibility between `datamol`, `python` and `rdkit`.
        
        | `datamol` | `python`      | `rdkit`               |
        | --------- | ------------- | --------------------- |
        | `0.3`     | `>=3.7,<=3.9` | `>=2020.09,<=2021.03` |
        
        ## CI Status
        
        |                                         | `master`                                                                                                                                                                           |
        | --------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
        | Lib build & Testing                     | [![GitHub Workflow Status](https://img.shields.io/github/workflow/status/datamol-org/datamol/test)](https://github.com/datamol-org/datamol/actions/workflows/test.yml)             |
        | Code Sanity (linting and type analysis) | [![GitHub Workflow Status](https://img.shields.io/github/workflow/status/datamol-org/datamol/code-check)](https://github.com/datamol-org/datamol/actions/workflows/code-check.yml) |
        | Documentation Build                     | [![GitHub Workflow Status](https://img.shields.io/github/workflow/status/datamol-org/datamol/doc)](https://github.com/datamol-org/datamol/actions/workflows/doc.yml)               |
        
        ## Changelogs
        
        See the latest changelogs at [CHANGELOG.rst](./CHANGELOG.rst).
        
        ## License
        
        Under the Apache-2.0 license. See [LICENSE](LICENSE).
        
        ## Authors
        
        See [AUTHORS.rst](./AUTHORS.rst).
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.7
Description-Content-Type: text/markdown
