Crate rustywallet_bloom 

rustywallet-bloom

Fast and memory-efficient Bloom Filter implementation optimized for large datasets like cryptocurrency address lookups.

Features

• Memory efficient: ~1.2 bytes per item at 1% false positive rate
• Fast: Uses FNV-1a hash with double hashing technique
• No dependencies: Pure Rust implementation
• Streaming insert: Load millions of items efficiently

Example

use rustywallet_bloom::BloomFilter;

// Create filter for 1 million items with 1% false positive rate
let mut bloom = BloomFilter::new(1_000_000, 0.01);

bloom.insert("1A1zP1eP5QGefi2DMPTfTL5SLmv7DivfNa");
bloom.insert("bc1qw508d6qejxtdg4y5r3zarvary0c5xw7kv8f3t4");

assert!(bloom.contains("1A1zP1eP5QGefi2DMPTfTL5SLmv7DivfNa"));
assert!(!bloom.contains("not_in_filter")); // probably false

Modules

prelude

Prelude module for convenient imports

Structs

BloomFilter

A space-efficient probabilistic data structure for set membership testing.