deepchem

library2.8.0pypypi✓ verified 89d ago

DeepChem is a Python library for deep learning in drug discovery, quantum chemistry, and the life sciences. It provides molecular featurization, model building, and dataset handling, supporting both TensorFlow and PyTorch backends. Current stable version is 2.8.0, with approximately bi-annual releases.

ai-ml data

pip install deepchem

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · DEEPCHEM

deepchem

ai-mlpythonv2.8.0

harness data pending

Install & Compatibility

Where this runs

No compatibility data collected yet for this library.

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

deepchem

✓ import deepchem as dc

✗ from deepchem import *

Wildcard import is discouraged; use 'import deepchem as dc' for namespace clarity.

Featurizer classes

✓ from deepchem.feat import MolGraphConvFeaturizer

✗ from deepchem.featurizers import *

Module is 'feat' not 'featurizers' in recent versions.

Minimal example: load Delaney solubility dataset, train a GraphConv model, and evaluate with Pearson R².

import deepchem as dc # Load a dataset from MoleculeNet tasks, datasets, transformers = dc.molnet.load_delaney(featurizer='GraphConv') train_dataset, valid_dataset, test_dataset = datasets # Define a graph convolutional model model = dc.models.GraphConvModel(n_tasks=len(tasks), mode='regression', dropout=0.2) # Fit the model on training data model.fit(train_dataset, nb_epoch=10) # Evaluate on test set metric = dc.metrics.Metric(dc.metrics.pearson_r2_score) scores = model.evaluate(test_dataset, [metric]) print(scores)

Debug

Known issues

breakingDeepChem 2.4.0 dropped TensorGraph and moved to Keras-based models. Models built with older versions will not work without migration.

fix

All models now use Keras layers. TensorGraph classes have been removed.

affects: >=2.4.0

breakingDeepChem 2.8.0 requires Python <3.12. Installation on Python 3.12 will fail.

fix

Use Python 3.7–3.11. Downgrade Python or use a virtual environment with supported version.

affects: 2.8.0

gotchaDefault backend between TensorFlow and PyTorch is not always clear. Some models (e.g., GraphConvModel) are TensorFlow only, while others (e.g., GCNModel) exist in both. Check documentation for backend compatibility.

fix

Use the specific model import (e.g., 'from deepchem.models import GCNModel') and ensure required backend is installed. For PyTorch models, install PyTorch separately.

affects: all

deprecatedThe legacy featurizer classes like 'CircularFingerprint' are deprecated in favor of graph-based featurizers (e.g., 'MolGraphConvFeaturizer').

fix

Use 'from deepchem.feat import MolGraphConvFeaturizer' instead.

affects: >=2.6.0

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'deepchem.feat.graph_features'

The 'graph_features' submodule was removed in DeepChem 2.7.0, with graph featurizers moved to 'deepchem.feat.graph_data' or directly to 'deepchem.feat'.

fix

Update import to 'from deepchem.feat import MolGraphConvFeaturizer' or use 'from deepchem.feat.graph_data import GraphData'.

AttributeError: 'GraphData' object has no attribute 'num_node_features'

In newer versions of DeepChem, the attribute was renamed or restructured. Old code expecting a direct attribute fails.

fix

Access features via 'graph_data.node_features.shape[1]' instead of 'graph_data.num_node_features'.

ImportError: cannot import name 'load_delaney' from 'deepchem.molnet'

The 'load_delaney' function was removed or moved. MoleculeNet loaders are now organized differently in DeepChem 2.8.0.

fix

Use 'from deepchem.molnet import load_delaney' (still exists) or check if the dataset is available via 'dc.molnet.load_delaney()'. If not found, use the new API: 'from deepchem.molnet import load_delaney' (same). Actually, this error often occurs due to mismatched versions; for 2.8.0, it should be present. If not, try using 'deepchem.molnet.load_delaney'.

ValueError: Graph convolution requires RDKit to be installed.

RDKit is a required dependency for molecular featurization, but not automatically installed with pip. Missing RDKit causes this error.

fix

Install RDKit via conda: 'conda install -c conda-forge rdkit' (recommended) or pip: 'pip install rdkit-pypi' (may have issues).

Upgrade

Version history

2.8.0latest on PyPI · released Apr 2, 2024

Audit

Dependencies

tensorflowrequiredPrimary deep learning framework dependency for many models and layers.

pytorchoptionalAlternative backend for models ported to PyTorch (e.g., GCN, AttentiveFP).

rdkitrequiredRequired for molecular featurization and cheminformatics.

Agent activity

18 hits · last 30 days

node

Amazon

OpenAI (training)

Resources

githubhttps://github.com/deepchem/deepchem ↗

packagehttps://pypi.org/project/deepchem/ ↗

homepagehttps://deepchem.io ↗

docshttps://deepchem.readthedocs.io/en/latest/ ↗