datasketch 1.5.3

Probabilistic data structures for processing and searching very large datasets

datasketch gives you probabilistic data structures that can process and search very large amount of data super fast, with little loss of accuracy.

This package contains the following data sketches:

Data Sketch	Usage
MinHash	estimate Jaccard similarity and cardinality
Weighted MinHash	estimate weighted Jaccard similarity
HyperLogLog	estimate cardinality
HyperLogLog++	estimate cardinality

The following indexes for data sketches are provided to support sub-linear query time:

Index	For Data Sketch	Supported Query Type
MinHash LSH	MinHash, Weighted MinHash	Jaccard Threshold
MinHash LSH Forest	MinHash, Weighted MinHash	Jaccard Top-K
MinHash LSH Ensemble	MinHash	Containment Threshold

datasketch must be used with Python 2.7 or above and NumPy 1.11 or above. Scipy is optional, but with it the LSH initialization can be much faster.

Note that MinHash LSH and MinHash LSH Ensemble also support Redis and Cassandra storage layer (see MinHash LSH at Scale).

Install

To install datasketch using pip:

pip install datasketch

This will also install NumPy as dependency.

To install with Redis dependency:

pip install datasketch[redis]

To install with Cassandra dependency:

pip install datasketch[cassandra]

To install with Scipy for faster MinHashLSH initialization:

pip install datasketch[scipy]