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<div align="center"> <img src="docs/images/logo-title.svg" width="100%"> </div> <p align="center"> <b>datamol - molecular processing made easy</b> <br /> </p> <p align="center"> <a href="https://docs.datamol.io/stable/" target="_blank"> Docs </a> | <a href="https://datamol.io/" target="_blank"> Homepage </a> </p>

Datamol is a python library to work with molecules. It's a layer built on top of RDKit and aims to be as light as possible.

🐍 Simple pythonic API
⚗️ RDKit first: all you manipulate are rdkit.Chem.Mol objects.
✅ Manipulating molecules often relies on many options; Datamol provides good defaults by design.
🧠 Performance matters: built-in efficient parallelization when possible with an 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 and try Datamol online.

Documentation

Visit https://docs.datamol.io.

Installation

Use conda:

mamba install -c conda-forge datamol

Quick API Tour

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")

How to cite

Please cite Datamol if you use it in your research: .

Compatibilities

Version compatibilities are an essential topic for production-software stacks. We are cautious about documenting compatibility between datamol, python and rdkit.

See below the associated versions of Python and RDKit, for which a minor version of Datamol has been tested during its whole lifecycle. It does not mean other combinations does not work but that those are not tested.

`datamol`	`python`	`rdkit`
`0.12.x`	`[3.10, 3.11]`	`[2023.03, 2023.09]`
`0.11.x`	`[3.9, 3.10, 3.11]`	`[2022.09, 2023.03]`
`0.10.x`	`[3.9, 3.10, 3.11]`	`[2022.03, 2022.09]`
`0.9.x`	`[3.9, 3.10, 3.11]`	`[2022.03, 2022.09]`
`0.8.x`	`[3.8, 3.9, 3.10]`	`[2021.09, 2022.03, 2022.09]`
`0.7.x`	`[3.8, 3.9]`	`[2021.09, 2022.03]`
`0.6.x`	`[3.8, 3.9]`	`[2021.09]`
`0.5.x`	`[3.8, 3.9]`	`[2021.03, 2021.09]`
`0.4.x`	`[3.8, 3.9]`	`[2020.09, 2021.03]`
`0.3.x`	`[3.8, 3.9]`	`[2020.09, 2021.03]`

CI Status

The CI runs tests and performs code quality checks for the following combinations:

The three major platforms: Windows, OSX and Linux.
The two latest Python versions.
The two latest RDKit versions.

	`main`
Lib build & Testing
Code Sanity (linting and type analysis)
Documentation Build

License

Under the Apache-2.0 license. See LICENSE.