BLOOM FILTERS BY EXAMPLE

Summary from the TLDR Web Dev newsletter

Bloom filters are probabilistic data structures that efficiently check if an element might be in a set. They use a bit vector and multiple hash functions to set bits when an element is added, allowing for quick membership tests. While Bloom filters can definitively say an element is not in the set, they may produce false positives due to the possibility of different elements setting the same bits.