  We introduce a Python open-source library for $\mathcal{X}$-armed bandit and
online blackbox optimization named PyXAB. PyXAB contains the implementations
for more than 10 $\mathcal{X}$-armed bandit algorithms, such as HOO, StoSOO,
HCT, and the most recent works GPO and VHCT. PyXAB also provides the most
commonly-used synthetic objectives to evaluate the performance of different
algorithms and the various choices of the hierarchical partitions on the
parameter space. The online documentation for PyXAB includes clear instructions
for installation, straight-forward examples, detailed feature descriptions, and
a complete reference of the API. PyXAB is released under the MIT license in
order to encourage both academic and industrial usage. The library can be
directly installed from PyPI with its source code available at
https://github.com/WilliamLwj/PyXAB
