sprout | Go implementation of an in-memory bloom filter

sprout is a Go library. sprout has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

A bloom filter is a probabilistic data structure that is used to determine if an element is present in a set. Bloom filters are fast and space efficient. They allow for false positives, but mitigate the probability with an expected false positive rate. An error rate of 0.001 implies that the probability of a false positive is 1 in 1000. Bloom filters don't store the elements themselves, but instead use a set of hash functions to determine the presence of an element. To fulfil the false positive rate, bloom filters can be initialized with a capacity. The capacity is the number of elements that can be inserted into the bloom filter, and this cannot be changed. Sprout implements a bloom filter in Go. The bits of the filter are stored in a memory-mapped file. Sprout also allows attaching a persistent storage (boltdb and badgerdb) to store the key value pairs. Sprout also implement a scalable bloom filter described in a paper written by P. Almeida, C.Baquero, N. Preguiça, D. Hutchison. A scalable bloom filter allows you to grow the filter beyond the initial filter capacity, while preserving the desired false positive rate.