  Black-box optimization (BBO) has a broad range of applications, including
automatic machine learning, experimental design, and database knob tuning.
However, users still face challenges when applying BBO methods to their
problems at hand with existing software packages in terms of applicability,
performance, and efficiency. This paper presents OpenBox, an open-source BBO
toolkit with improved usability. It implements user-friendly interfaces and
visualization for users to define and manage their tasks. The modular design
behind OpenBox facilitates its flexible deployment in existing systems.
Experimental results demonstrate the effectiveness and efficiency of OpenBox
over existing systems. The source code of OpenBox is available at
https://github.com/PKU-DAIR/open-box.
