K Means Python Packages

k-means-constrained

K-Means clustering - constrained with minimum and maximum cluster size. Documentation: https://joshlk.github.io/k-means-constrained

pyckmeans

Consensus and WECR K-Means clustering.

polyvoice

Speaker diarization for Rust — who spoke when. ONNX-powered: Silero VAD, WeSpeaker embeddings, Pyannote segmentation, K-means/AHC clustering, overlap detection. Python bindings & CLI included.

ckmeans

A Python package for fast 1D clustering using a Rust binary. Prefer ckmeans to Jenks.

diffsptk

A differentiable version of SPTK

superkmeans

A Super fast K-Means library for High-Dimensional vectors on CPUs (x86, ARM) and GPUs

ml-python

The easiest way to do machine learning

spherecluster

Clustering routines for the unit sphere

dovalens

CLI for dataset profiling, statistics, clustering/anomaly detection, and drift (KS); generates a single HTML report from a CSV.

synloc

A Python package to create synthetic data from locally estimated distributions

mp-kmeans

CUDA-accelerated mixed-precision k-means clustering for large-scale data.

composite-silhouette

A clustering evaluation framework that combines micro- and macro-averaged silhouette scores into a composite metric using statistical weighting.

compsil

CompSil: Composite Silhouette for Cluster-Count Selection

ballot

High-performance Python package for balanced k-means clustering using optimal transport and entropic regularization