set-trie

Fast subset and superset queries based on tries. If you have lookup-based queries, K -> V, but instead of looking for an exact match with K, you want all K's which are a subset or superset of your query, then look no further.

```rust use set_trie::SetTrie;

fn main() { let mut employees = SetTrie::new(); employees.insert(&["accounting", "banking"], "Daniels"); employees.insert(&["accounting", "banking", "crime"], "Stevens");

assert_eq!(employees.subsets(&[&"accounting", &"banking", &"crime"]).collect::<Vec<_>>(), vec![&"Daniels", &"Stevens"]);
assert_eq!(employees.subsets(&[&"accounting", &"banking"]).collect::<Vec<_>>(), vec![&"Daniels"]);
assert_eq!(employees.supersets(&[&"accounting"]).collect::<Vec<_>>(), vec![&"Daniels", &"Stevens"]);

} ```

Restrictions

Although currently not implemented in the type system, due to a lack of a trait bound over sorted iterators, set tries require all queries to be sorted. Failing to sort the query or key will result in nonsensical results:

```rust use set_trie::SetTrie;

fn main() { let mut trie = SetTrie::new(); trie.insert(&[2, 3], "Foo"); trie.insert(&[1, 2], "Bar");

// although we'd expect this to contain &"Bar".
assert_eq!(trie.subsets(&[&2, &1]).collect::<Vec<_>>(), Vec::<&&str>::new());

} ```

Features

• Subsets and supersets are lazily evaluated, through an iterative DFS algorithm.
• Convenient entry API.

TODO

• [ ] Implement benchmarks (low priority, PR welcome)
• [ ] Memorize seen keys to save 1 binary search (requires benchmarks to compare performance)