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TANTIVY
Fast full-text search engine library written in Rust
MIT
ABOUT
Building full-text search into applications often means either running a heavyweight external service like Elasticsearch or writing fragile custom search logic. Tantivy provides Lucene-quality full-text search as a library — embeddable directly into Rust or Python applications with no external dependencies. It handles indexing, tokenization, BM25 scoring, filtering, faceting, and fuzzy search with performance competitive to Elasticsearch but without the operational overhead.
INSTALL
pip install tantivyINTEGRATION GUIDE
1. Embedding full-text search into Python applications without running Elasticsearch
2. Building a document retrieval pipeline with BM25 scoring for RAG pre-filtering
3. Indexing large text corpora for offline analytics and keyword-based document discovery
4. Supporting fuzzy search, phrase queries, and faceted search in content management systems
5. Creating a low-latency search backend for documentation sites, knowledge bases, or e-commerce
TAGS
full-text-searchsearch-enginerustindexingnlp