{"repo":"pablocael/pynear","free":true,"listed":false,"github":"https://github.com/pablocael/pynear","clone":"git clone https://github.com/pablocael/pynear.git","description":"A python library for efficient KNN search within metric spaces using multiple distance functions.","language":"C++","stars":41,"topics":["knn","machine-learning","metric-spaces","nearest-neighbors","simd","similarity-search","vector-database","vector-search","vp-tree","approximate-search"],"license":"MIT","category":"machine-learning","readme_excerpt":"PyNear PyNear is a metric-space nearest-neighbour library with a C++ core, built for the workloads between the embeddings world and brute force: binary descriptors with recall guarantees (MIH + IVF-Binary + the novel MIH-seeded HNSW — dedup, copy detection, ORB/BRIEF matching, robotics), memory-tight ANN (HNSW with int8 quantisation), and exact search (VP-trees, up to 256-D) where a missed neighbour is a bug, not a recall statistic. One small NumPy-only API, scikit-learn drop-in, pre-built wheels ( pip install pynear ). k-NN with guarantees. Near-duplicate search that provably misses nothing, quantised ANN that beats float indexes at 4× less RAM, and exact search when exactness is mandatory. MIH — binary near-duplicate retrieval with a pigeonhole completeness guarantee (every neighbour within your radius is found), up to 3.5× faster than Faiss's MIH at matched recall · SQ8 HNSW — tracks or beats Faiss's float HNSW up to 0.91 recall at a quarter of the memory · VP-trees — exact k-NN 12× faster than a flat scan for CV matching, dedup compliance, and ANN ground truth · drop-in for scikit-learn · SIMD on x86 and ARM · zero native deps beyond NumPy. --- Table of Contents - Introduction - Why PyNear? - Choosing an index - Installation - Quick start - Low-dimensional exact search (VPTreeL2Index) - High-dimensional binary descriptors (MIHBinaryIndex) - Migrating from scikit-learn - Features - Available indices - Pickle serialisation - Tree inspection - Demos - Benchmarks - Real-World","default_branch":null,"files":null,"tree":[],"storefront":"/r/pablocael","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/pablocael/pynear/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}