Fast vector similarity using Rust and Python

In plain words

Fast Vector Similarity is a library that computes similarity and statistical dependency measures between high-dimensional vectors using Rust and Python. It offers alternatives to cosine similarity, including measures like Hoeffding's D, which can detect more subtle relationships in data such as sentence embeddings from language models. The tool leverages Rust's performance to make computationally intensive similarity calculations faster in Python than traditional NumPy implementations.

written from the facts on this page · September 2026

From the sources

High-performance vector similarity library in Rust with Python bindings: Spearman, Kendall, distance correlation, Jensen-Shannon, Hoeffding's D, and bootstrapped confidence intervals - Dicklesworthstone/fast_vector_similarity

In the maker’s words, at launch

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