A Practical Python API for Querying AFLOWLIB

Conrad W. Rosenbrock Department of Physics and Astronomy, Brigham Young University, Provo, Utah 84602, USA. (Dated: October 3, 2017) Abstract Large databases such as aflowlib.org provide valuable data sources for discovering material trends through machine learning. Although a REST API and query language are available, there is a learning curve associated with the AFLUX language that acts as a barrier for new users. Additionally, the data is stored using non-standard serialization formats. Here we present a highlevel API that allows immediate access to the aflowlib data using standard python operators and language features. It provides an easy way to integrate aflowlib data with other python materials packages such as ase and quippy, and provides automatic deserialization into numpy arrays and python objects. This package is available via pip install aflow.