awesome-python-chemistry

Convert AMBER forcefields from ANTECHAMBER to GROMACS format.

Makes alchemical free energy calculations easier by leveraging the full power and flexibility of the PyData stack.

atomate2 is a library of computational materials science workflows.

Is a set of tools and modules for setting up, manipulating, running, visualizing and analyzing atomistic simulations.

A library containing basis sets for use in quantum chemistry calculations. In addition, this library has functionality for manipulation of basis set data.

Cactvs is a universal, scriptable cheminformatics toolkit, with a large collection of modules for property computation, chemistry data file I/O and other tasks.

A tool for retrosynthetic planning.

Ensemble of automated QM workflows that can be run through jupyter notebooks, command lines and yaml files.

A GUI app based on wxPython for calculating the correct amount of reactants (batch) for a particular composition given by the molar ratio of its components.

The Computational Crystallography Toolbox.

ChemFormula provides a class for working with chemical formulas. It allows parsing chemical formulas, calculating formula weights, and generating formatted output strings (e.g. in HTML, LaTeX, or Unicode).

A robust and easy-to-use package that solves a variety of chemistry problems.

Is an open-source package designed to easily bring machine-learning to atomistic calculations.

Enables machine learning on three-dimensional molecular structure.

Crystal graph convolutional neural networks for predicting material properties.

A deep learning framework (based on Chainer) with applications in Biology and Chemistry.

A machine learning and informatics program suite for the analysis, mining, and modeling of chemical and materials data.

Message Passing Neural Networks for Molecule Property Prediction .

A Jupyter book demonstrating working with biochemical data using the scikit-bio library for tasks such as sequence alignment and calculating Hamming distances.

This collection of Jupyter notebooks demonstrates solutions to a range of thermodynamic problems including solving chemical equilibria, comparing real versus ideal gas behavior, and calculating the temperature and composition of a combustion reaction.

Scientific Computing for Chemists with Python is a Jupyter book teaching basic python in chemistry skills, including relevant libraries, and applies them to solving chemical problems.

The graphical user-interface allows users to visualize, manipulate, and render molecular systems and atoms objects.

An interactive structure/property explorer for materials and molecules.

An interactive molecular viewer designed for the IPython notebook.

An embeddable webGL molecule viewer and file format converter.

A molecule manipulation library.

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An API for the Cambridge Structural Database System.

Automate downloading and querying the latest (or a given) version of

High-throughput PubChem client for batch queries with caching, validation, rate-limit-aware retries, and a simple CLI.

ChemSpider wrapper, that allows chemical searches, chemical file downloads, depiction and retrieval of chemical properties.

An interface for the Chemical Identifier Resolver (CIR) by the CADD Group at the NCI/NIH.

Automate downloading, opening, and parsing

A beatuful, interactive visualization of nuclides with access to a varirty of nuclear properties and allows saving high quality images for publications, presentations and outreach.