A Bloom filter is a data structure designed to tell you, rapidly and memory-efficiently, whether an element is present in a set. The price paid for this efficiency is that a Bloom filter is a probabilistic data structure: it tells us that the element either definitely is not in the set or may be in the set.
go get -u github.com/darklord19/bloomfilter
import "github.com/darkLord19/bloomfilter"// NewBloomFilter accepts three arguments. First is number of elements you want to track,
// second is acceptable false positive probability, and third is hash you want to use(it must implement hash64 interface)
bf := bloomfilter.NewBloomFilter(10000, 0.10, fnv.New64())
bf.Add([]byte("A"))
bf.Add([]byte("B"))
res, err := bf.DoesNotExist([]byte("C"))
elems := bf.GetElementsEstimate()