qmflows 0.11.2

Motivation

Research on modern computational quantum chemistry relies on a set of computational tools to carry out calculations. The complexity of the calculations usually requires intercommunication between the aforementioned tools, such communication is usually done through shell scripts that try to automate input/output actions like: launching the computations in a cluster, reading the resulting output and feeding the relevant numerical result to another program. Such scripts are difficult to maintain and extend, requiring a significant programming expertise to work with them. Being then desirable a set of automatic and extensible tools that allows to perform complex simulations in heterogeneous hardware platforms.

This library tackles the construction and efficient execution of computational chemistry workflows. This allows computational chemists to use the emerging massively parallel compute environments in an easy manner and focus on interpretation of scientific data rather than on tedious job submission procedures and manual data processing.

Description

This library consists of a set of modules written in Python3 to automate the following tasks:

1. Input generation.

2. Handle tasks dependencies (Noodles).

3. Advanced molecular manipulation capabilities with (rdkit).

4. Jobs failure detection and recovery.

5. Numerical data storage (h5py).

Installation

• Download miniconda for python3: miniconda (also you can install the complete anaconda version).

• Install according to: installConda.

• Create a new virtual environment using the following commands:

  • conda create -n qmflows

• Activate the new virtual environment

  • source activate qmflows

To exit the virtual environment type source deactivate.