hypertools is a well‑engineered Python library for high‑dimensional data analysis and visualization, with a strong focus on animated 3D trajectories, multi‑subject alignment (Haxby hyperalignment, SRM, Procrustes), cluster analysis, time‑series forecasting, and missing‑data imputation. The package exposes a scikit‑learn–compatible Pipeline: 'manip → normalize → reduce → align → plot', plus standalone dispatchers ('hyp.plot', 'hyp.align', 'hyp.cluster', 'hyp.predict', 'hyp.impute') that share a consistent model‑spec grammar (string, class, instance, dict) and support `return_model` reuse. Two plotting backends (matplotlib and plotly) produce parity for kaleidoscopic animations (serialitary, chemo, bullet, morph) and static charts. The codebase is fortified by an audit‑driven test suite of >160 test files, many using real instead of mocked data, and delivery‑orchestrated through a coherent CI pipeline. Vendored code (PPCA, brainiak SRM, Noto Sans fonts) and a lazy‑import mechanism that auto‑installs optional extras on demand keep the core lean while enabling rich functionality.