use crate::model::*; mod query_filter; pub use self::query_filter::QueryFilterSyntaxError; use self::query_filter::*; pub struct Query { filters: Vec, } impl Query { pub fn search(&self, input: &mut Iterator) -> Vec { let mut results: Vec<(i64, &Texture)> = Vec::new(); // We use pseudo decimal fixed point numbers here. // 1.000_000 = 1_000_000; // This is done, since algorithms like quicksort can fail on floats. let required_score = self.required_score() * 1_000_000i64; 'texture_loop: for texture in input { let mut score = 0i64; for (pos, filter) in self.filters.iter().enumerate() { match filter.score(texture) { Score::RequiredMatch(true) => (), Score::RequiredMatch(false) => { // skip this texture continue 'texture_loop; } Score::Match(true) => { score += 1_000_000i64 + ((100_000.0 / f64::sqrt(pos as f64 + 1.0)) as i64); } Score::Match(false) => (), } } if score >= required_score { results.push((score, texture)) } } results.sort_by_key(|(score, _)| score * -1); results .iter() .map(|(_, texture)| Texture::clone(texture)) .collect::>() } fn required_score(&self) -> i64 { let non_special = self.filters.iter().filter(|f| !f.is_special()).count() as i64; // ceil(non_special / 2) (non_special + 1) / 2 } pub fn parse(input: &[String]) -> Result { let mut result = Query { filters: vec![] }; for fltr in input { let qryfltr = fltr.parse::()?; result.filters.push(qryfltr); } Ok(result) } } #[cfg(test)] /// These tests check against the example section in the search design document. mod test { use super::*; use std::str::FromStr; /// just a shorthand fn tex(id: i32, name: &str, tags: &str, added_on: &str, resolution: u64) -> Texture { Texture { id: format!("{}", id), // Id should actaly be a uuid, but for testing this is fine. name: name.to_string(), tags: tags.split(",").map(|s| s.trim().to_string()).collect(), added_on: Date::from_str(added_on).unwrap(), resolution: (resolution, resolution), format: TextureFormat::JPEG, texture_hash: Sha256::from_data(b"Some Hash"), } } // data of example section of search document. fn test_data() -> Vec { vec![ tex( 1, "wood_185841", "Holz, Dunkel, Rot, Edel", "2019-05-15", 4 * 1024, ), tex(2, "wood_84846", "Holz, Hell", "2019-05-13", 2 * 1024), tex(3, "silk_large", "Stoff, Rot, Edel", "2018-01-01", 8 * 1024), tex(4, "cotton_xxx", "Stoff, Rot, Rau", "2018-02-01", 2048), tex(5, "green_frabric", "GrĂ¼n, Stoff", "2018-03-01", 1024), tex(6, "tin54_45", "Metall, Hell", "2018-03-01", 4 * 1024), tex(7, "copper4_1k", "Rot, Metall", "2016-03-01", 1024), tex( 8, "rusty_metall", "Rot, Metall, Rost, Dunkel", "2015-03-01", 8 * 1024, ), ] } fn assert_query(query: &str, expected: Vec) { let q = Query::parse( &query .split_whitespace() .map(|s| s.to_string()) .collect::>(), ) .unwrap(); let data = test_data(); let result = q.search(&mut data.iter()); let only_ids = result .into_iter() .map(|tex| tex.id.parse::().unwrap()) .collect::>(); assert_eq!(only_ids, expected) } #[test] fn test_examples_from_doc_1() { assert_query("Holz Dunkel", vec![1, 2, 8]); } #[test] fn test_examples_from_doc_2() { assert_query("n:wood_", vec![1, 2]); } #[test] fn test_examples_from_doc_3() { assert_query("before:2019-05-31 after:2019-04-30", vec![1, 2]); } #[test] fn test_examples_from_doc_4() { assert_query("Stoff Rot Edel", vec![3, 4, 1]); } #[test] fn test_examples_from_doc_5() { assert_query("Stoff Rot !Edel", vec![4, 3, 5, 7, 8]); } #[test] fn test_examples_from_doc_6() { assert_query("Metall Dunkel res:4k", vec![8, 6, 1]); } }