Struct BloomFilter 

pub struct BloomFilter { /* private fields */ }

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

Bloom filters can have false positives but never false negatives. If contains() returns false, the item is definitely not in the set. If contains() returns true, the item is probably in the set.

Memory Usage

For a given number of items n and false positive rate p:

• Optimal bits: m = -n * ln(p) / (ln(2)^2) ≈ n * 9.6 for 1% FPR
• Optimal hashes: k = (m/n) * ln(2) ≈ 7 for 1% FPR

Example

use rustywallet_bloom::BloomFilter;

let mut filter = BloomFilter::new(100_000, 0.01);
filter.insert("address1");
assert!(filter.contains("address1"));

Implementations

impl BloomFilter

pub fn new(expected_items: usize, false_positive_rate: f64) -> Self

Creates a new Bloom filter optimized for the expected number of items and desired false positive rate.

Arguments

• expected_items - Expected number of items to insert
• false_positive_rate - Desired false positive rate (e.g., 0.01 for 1%)

Example

use rustywallet_bloom::BloomFilter;

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

pub fn with_params(num_bits: usize, num_hashes: usize) -> Self

Creates a Bloom filter with explicit parameters.

Use this if you need precise control over the filter size.

Arguments

• num_bits - Total number of bits in the filter
• num_hashes - Number of hash functions to use

pub fn insert<T: AsRef<[u8]>>(&mut self, item: T)

Inserts an item into the filter.

After insertion, contains() will always return true for this item.

pub fn contains<T: AsRef<[u8]>>(&self, item: T) -> bool

Checks if an item might be in the filter.

Returns false if the item is definitely not in the set. Returns true if the item is probably in the set (may be false positive).

pub fn len(&self) -> usize

Returns the number of items inserted.

pub fn is_empty(&self) -> bool

Returns true if no items have been inserted.

pub fn memory_usage(&self) -> usize

Returns the memory usage in bytes.

pub fn num_bits(&self) -> usize

Returns the number of bits in the filter.

pub fn num_hashes(&self) -> usize

Returns the number of hash functions used.

pub fn estimated_fpr(&self) -> f64

Returns the estimated false positive rate based on current fill.

pub fn clear(&mut self)

Clears all items from the filter.

Trait Implementations

impl Debug for BloomFilter

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.