accel 0.3.0

ACCeL is a Python package for managing and filtering conformers in computational chemistry.

ACCeL is a Python package designed to streamline the processing of conformational ensembles in computational chemistry.

It provides a simple and flexible framework for managing large sets of molecular structures, especially conformers and their variants. ACCeL supports automated workflows such as:

• Reading and organizing output files from quantum chemistry calculations

• Extracting atomic coordinates, energies, and thermodynamic corrections

• Filtering structures based on energy thresholds or RMSD values

• Generating input files using user-defined templates

• Labeling and organizing conformers for downstream processing

• Exporting data to CSV or coordinate formats

The core object, Box, enables method-chained operations to efficiently process molecular datasets. ACCeL is particularly useful for researchers working with large conformer sets and quantum chemical outputs.

Features

• Automated file handling and structure filtering

• Energy-based and structural deduplication

• Labeling and grouping by file name

• Boltzmann population and free energy calculations

• Input/output support for XYZ and MOL formats

• Extensible plugin system

Project Information

• Repository: https://github.com/kfchem/accel

• License: MIT

• Python version: 3.9+