Expand description
Production-grade data structures and algorithms — zero external dependencies.
A collection of space-efficient probabilistic data structures and graph algorithms for general-purpose use.
§Modules
bloom- Bloom filter for approximate set membershipcount_min- Count-Min sketch for frequency estimationgraph- Graph algorithms (BFS, Dijkstra, A*)heap- Bounded heap for K-nearest neighbor trackingtrie- Trie prefix tree and Rabin-Karp string matching
§Usage
use resq_dsa::bloom::BloomFilter;
use resq_dsa::count_min::CountMinSketch;
use resq_dsa::graph::Graph;
// Bloom filter for deduplication
let mut bf = BloomFilter::new(1000, 0.01);
bf.add("drone-001");
assert!(bf.has("drone-001"));
// Count-Min for frequency tracking
let mut cms = CountMinSketch::new(0.01, 0.01);
cms.increment("sensor-reading", 5);
// Graph for pathfinding
let mut g = Graph::<&str>::new();
g.add_edge("base", "waypoint-1", 100);
g.add_edge("waypoint-1", "target", 50);
let (path, cost) = g.dijkstra(&"base", &"target").unwrap();
assert_eq!(path, vec!["base", "waypoint-1", "target"]);