feat: add normalized config tracking and improve command
- Add normalize_to_final_build() to map tune configs to final builds (323/233/332) - Add normalized_config field to BestCarRecord - Change CarCounts.by_rid key from String to (String, String) for per-config tracking - Change CarCounts.guid_to_rid to HashMap<String, HashSet<(String, String)>> - Extract owned tune configs from my_cars.json (engineMajor/weightMajor/chassisMajor) - Add improve command: owned cars not yet at final build, sorted by track count - Strip version prefixes (v2c_/v1c_) from config keys at parse time - Update dedup check in update_best_car to consider normalized_config - Add atomic_write helper for safe CSV output - Delete completed plans/code-review-v2.md - Apply rustfmt formatting across codebase
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25 changed files with 735 additions and 759 deletions
110
src/context.rs
110
src/context.rs
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@ -3,7 +3,7 @@
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//! Contains the mutable analysis state (`AnalysisContext`) and the
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//! aggregated per-car win counts (`CarCounts`) computed from it.
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use std::collections::HashMap;
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use std::collections::{HashMap, HashSet};
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use std::sync::Arc;
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use dashmap::DashMap;
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@ -33,24 +33,29 @@ impl Default for AnalysisContext {
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impl AnalysisContext {
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/// Create a new, empty analysis context.
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pub fn new() -> Self {
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AnalysisContext {
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best_cars: Arc::new(DashMap::new()),
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}
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AnalysisContext { best_cars: Arc::new(DashMap::new()) }
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}
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}
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/// Aggregated per-car win counts across all track/RQ/condition combinations.
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/// Computed once from `AnalysisContext` and shared across all output functions.
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///
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/// The composite key `(car_rid, normalized_config)` ensures that the same car
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/// with different final builds (e.g., "323" vs "332") is tracked separately.
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pub struct CarCounts {
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/// Map from car_rid → (BestCarRecord, count of tracks where this car is best)
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pub by_rid: HashMap<String, (BestCarRecord, usize)>,
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/// Map from guid → car_rid (for O(1) ownership/wishlist lookups)
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pub guid_to_rid: HashMap<String, String>,
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/// Map from (car_rid, normalized_config) → (BestCarRecord, count of tracks where this car+config is best)
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pub by_rid: HashMap<(String, String), (BestCarRecord, usize)>,
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/// Map from guid → set of (car_rid, normalized_config) for O(1) ownership/wishlist lookups.
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/// A guid may map to multiple entries if the same car is best with different configs.
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pub guid_to_rid: HashMap<String, HashSet<(String, String)>>,
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/// Map from guid → Car (for O(1) lookups of car metadata by GUID).
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/// Built once in `compute_car_counts()` and reused by trash/wishlist output.
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pub car_map: HashMap<String, Car>,
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/// Full car list from the database (kept for any callers that need iteration).
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pub car_list: Vec<Car>,
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/// Actual tune config for each owned car (guid → config string from playerDeck).
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/// Used by the improve command to determine which cars are not yet at a final build.
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pub owned_configs: HashMap<String, String>,
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}
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/// Computes per-car win counts from the analysis context.
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@ -58,39 +63,46 @@ pub struct CarCounts {
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/// Returns a `CarCounts` struct that can be shared across all output functions.
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/// This function cannot fail — it only performs `DashMap` iteration and
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/// `HashMap` inserts.
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pub fn compute_car_counts(ctx: &AnalysisContext, car_list: Vec<Car>) -> CarCounts {
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let mut by_rid: HashMap<String, (BestCarRecord, usize)> = HashMap::new();
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let mut guid_to_rid: HashMap<String, String> = HashMap::new();
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///
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/// Groups by `(car_rid, normalized_config)` so that the same car with different
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/// final builds is counted as separate entries.
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pub fn compute_car_counts(
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ctx: &AnalysisContext,
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car_list: Vec<Car>,
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owned_configs: HashMap<String, String>,
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) -> CarCounts {
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let mut by_rid: HashMap<(String, String), (BestCarRecord, usize)> = HashMap::new();
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let mut guid_to_rid: HashMap<String, HashSet<(String, String)>> = HashMap::new();
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for entry in ctx.best_cars.iter() {
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for best_car in entry.value() {
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let rid_entry = by_rid
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.entry(best_car.car_rid.clone())
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.or_insert_with(|| (best_car.clone(), 0usize));
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let key = (best_car.car_rid.clone(), best_car.normalized_config.clone());
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let rid_entry = by_rid.entry(key.clone()).or_insert_with(|| (best_car.clone(), 0usize));
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rid_entry.1 += 1;
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// Keep the record with the best (lowest) time for this car.
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// Keep the record with the best (lowest) time for this car+config.
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if best_car.time < rid_entry.0.time {
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rid_entry.0 = best_car.clone();
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}
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// HashMap iteration order is non-deterministic, but car_rid and guid
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// have a 1:1 relationship in the data model, so any mapping is correct.
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guid_to_rid.entry(best_car.guid.clone())
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.or_insert_with(|| best_car.car_rid.clone());
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// Track all (rid, config) pairs for each guid.
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guid_to_rid.entry(best_car.guid.clone()).or_default().insert(key);
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}
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}
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// Build guid → Car lookup once, reused by trash/wishlist output functions.
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let car_map: HashMap<String, Car> = car_list.iter()
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.map(|c| (c.guid.clone(), c.clone()))
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.collect();
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let car_map: HashMap<String, Car> =
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car_list.iter().map(|c| (c.guid.clone(), c.clone())).collect();
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CarCounts { by_rid, guid_to_rid, car_map, car_list }
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CarCounts { by_rid, guid_to_rid, car_map, car_list, owned_configs }
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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fn empty_owned_configs() -> HashMap<String, String> {
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HashMap::new()
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}
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#[test]
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fn test_compute_car_counts_basic() {
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let ctx = AnalysisContext::new();
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@ -101,6 +113,7 @@ mod tests {
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year: 2020,
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rq: 85,
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config: "111".to_string(),
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normalized_config: "332".to_string(),
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time: 100.0,
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owned: true,
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prize: false,
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@ -108,14 +121,10 @@ mod tests {
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};
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// Manually insert into best_cars
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ctx.best_cars.insert(
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("Laguna Seca".to_string(), 85, "Dry".to_string()),
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vec![record.clone()],
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);
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ctx.best_cars.insert(
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("Monaco Streets".to_string(), 85, "Dry".to_string()),
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vec![record.clone()],
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);
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ctx.best_cars
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.insert(("Laguna Seca".to_string(), 85, "Dry".to_string()), vec![record.clone()]);
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ctx.best_cars
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.insert(("Monaco Streets".to_string(), 85, "Dry".to_string()), vec![record.clone()]);
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let car_list = vec![Car {
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rid: "Test_Car".to_string(),
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@ -127,16 +136,19 @@ mod tests {
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guid: "guid_test".to_string(),
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}];
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let counts = compute_car_counts(&ctx, car_list);
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let my_data = empty_owned_configs();
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let counts = compute_car_counts(&ctx, car_list, my_data);
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// Should have exactly 1 entry in by_rid
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assert_eq!(counts.by_rid.len(), 1);
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let (rec, count) = counts.by_rid.get("Test_Car").unwrap();
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let (rec, count) = counts.by_rid.get(&("Test_Car".to_string(), "332".to_string())).unwrap();
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assert_eq!(count, &2); // best on 2 tracks
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assert_eq!(rec.car_rid, "Test_Car");
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// guid_to_rid should map guid → rid
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assert_eq!(counts.guid_to_rid.get("guid_test"), Some(&"Test_Car".to_string()));
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// guid_to_rid should map guid → set of (rid, config)
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let guid_entries = counts.guid_to_rid.get("guid_test").unwrap();
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assert_eq!(guid_entries.len(), 1);
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assert!(guid_entries.contains(&("Test_Car".to_string(), "332".to_string())));
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// car_map should have the car
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assert!(counts.car_map.contains_key("guid_test"));
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@ -154,6 +166,7 @@ mod tests {
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year: 2020,
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rq: 85,
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config: "111".to_string(),
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normalized_config: "332".to_string(),
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time: 90.0,
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owned: false,
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prize: false,
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@ -166,24 +179,27 @@ mod tests {
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year: 2020,
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rq: 85,
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config: "233".to_string(),
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normalized_config: "233".to_string(),
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time: 110.0,
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owned: false,
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prize: false,
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guid: "guid_a".to_string(),
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};
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ctx.best_cars.insert(
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("Track1".to_string(), 85, "Dry".to_string()),
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vec![record_fast],
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);
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ctx.best_cars.insert(
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("Track2".to_string(), 85, "Dry".to_string()),
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vec![record_slow],
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);
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ctx.best_cars.insert(("Track1".to_string(), 85, "Dry".to_string()), vec![record_fast]);
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ctx.best_cars.insert(("Track2".to_string(), 85, "Dry".to_string()), vec![record_slow]);
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let counts = compute_car_counts(&ctx, vec![]);
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let (rec, count) = counts.by_rid.get("Car_A").unwrap();
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assert_eq!(*count, 2);
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assert_eq!(rec.time, 90.0); // Should keep the faster time
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let my_data = empty_owned_configs();
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let counts = compute_car_counts(&ctx, vec![], my_data);
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// Different normalized configs → separate entries
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assert_eq!(counts.by_rid.len(), 2);
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let (rec_fast, count_fast) =
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counts.by_rid.get(&("Car_A".to_string(), "332".to_string())).unwrap();
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assert_eq!(*count_fast, 1);
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assert_eq!(rec_fast.time, 90.0);
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let (rec_slow, count_slow) =
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counts.by_rid.get(&("Car_A".to_string(), "233".to_string())).unwrap();
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assert_eq!(*count_slow, 1);
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assert_eq!(rec_slow.time, 110.0);
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}
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}
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