We introduce topox, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: hypergraphs, simplicial, cellular, path and combinatorial complexes. topox consists of three packages: toponetx facilitates constructing and computing on these domains, including working with nodes, edges and higher-order cells; topoembedx provides methods to embed topological domains into vector spaces, akin to popular graph-based embedding algorithms such as node2vec; topomodelx is built on top of PyTorch and offers a comprehensive toolbox of higher-order message passing functions for neural networks on topological domains. The extensively documented and unit-tested source code of topox is available under MIT license at https://github.com/pyt-team.

翻译：我们介绍了topox，一个Python软件套件，为计算和机器学习提供可靠且用户友好的基础组件，适用于扩展图结构的拓扑领域：超图、单纯复形、胞腔复形、路径复形和组合复形。topox包含三个软件包：toponetx支持构建和计算这些拓扑领域，包括处理节点、边和高阶胞腔；topoembedx提供将拓扑领域嵌入到向量空间的方法，类似于基于图的经典嵌入算法（如node2vec）；topomodelx基于PyTorch构建，为拓扑领域的神经网络提供高阶消息传递函数的综合工具箱。topox的源代码经过详尽文档记录和单元测试，以MIT许可证发布于https://github.com/pyt-team。