Requirements

Hard requirements

DeepChem officially supports Python 3.8 through 3.10 and requires these packages on any condition.

Soft requirements

DeepChem has a number of “soft” requirements.

Package name

Version

Location where this package is used (dc: deepchem)

BioPython

latest

dc.utlis.genomics_utils

Deep Graph Library

0.5.x

dc.feat.graph_data, dc.models.torch_models

DGL-LifeSci

0.2.x

dc.models.torch_models

HuggingFace Transformers

Not Testing

dc.feat.smiles_tokenizer

HuggingFace Tokenizers

latest

dc.feat.HuggingFaceVocabularyBuilder

LightGBM

latest

dc.models.gbdt_models

matminer

latest

dc.feat.materials_featurizers

MDTraj

latest

dc.utils.pdbqt_utils

Mol2vec

latest

dc.utils.molecule_featurizers

Mordred

latest

dc.utils.molecule_featurizers

NetworkX

latest

dc.utils.rdkit_utils

OpenAI Gym

Not Testing

dc.rl

OpenMM

latest

dc.utils.rdkit_utils

PDBFixer

latest

dc.utils.rdkit_utils

Pillow

latest

dc.data.data_loader, dc.trans.transformers

PubChemPy

latest

dc.feat.molecule_featurizers

pyGPGO

latest

dc.hyper.gaussian_process

Pymatgen

latest

dc.feat.materials_featurizers

PyTorch

2.1.0

dc.models.torch_models

PyTorch Geometric

2.1.x (with PyTorch 2.1.0)

dc.feat.graph_data dc.models.torch_models

RDKit

latest

Many modules (we recommend you to install)

simdna

latest

dc.metrics.genomic_metrics, dc.molnet.dnasim

Tensorflow Probability

0.11.x

dc.rl

Weights & Biases

Not Testing

dc.models.keras_model, dc.models.callbacks

XGBoost

latest

dc.models.gbdt_models

Tensorflow Addons

latest

dc.models.optimizers

pySCF

latest

dc.models.torch_models.ferminet

TensorFlow

latest

dc.models deepchem>=2.4.0 depends on TensorFlow v2(2.3.x) deepchem<2.4.0 depends on TensorFlow v1(>=1.14)

pysam

latest

dc.feat.bio_seq_featurizer dc.models.data_loader