Fast fuzzy text search
Project description
Narrow Down
Fast fuzzy text search
- GitHub repo: https://github.com/chr1st1ank/narrow-down.git
- Documentation: https://chr1st1ank.github.io/narrow-down
- Free software: Apache Software License 2.0
- Status: Prototype. Solid and fast production quality, but still subject to API changes until version 1.0 is reached.
Features
- Document indexing and search based on the Minhash LSH algorithm
- High performance thanks to a native extension module in Rust
- Easy-to-use API with automated parameter tuning
- Works with many storage backends. Currently implemented:
- In-Memory
- SQLite
- Custom backend by implementing a lean interface
- Native asyncio interface
Quickstart
TODO
Similar projects
- pylsh offers a good implementation of the classic Minhash LSH scheme in Python and Cython. If you only need this and you don't need a database backend it can be a good choice.
- Datasketch implements an interesting collection of different data sketching algorithms for similarity matching, cardinality estimation and k-nearest-neighbour search. The implementation is not highly optimized but very well usable, the documentation rich and multiple database backends can be used for some of the sketches
- Milvus offers a full database stack for vector search, a different approach for fast searching. It can also be applied to text search when an emedding like Word2Vec or Bert is used to vectorize the text.
Credits
This package was created with Cookiecutter and the fedejaure/cookiecutter-modern-pypackage project template.
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