top_drives/docs/API.md
Jan-Peter von Hunnius 67a79f190a Refactor: extract lib.rs into focused sub-modules, add --output-dir CLI option
- Split monolithic src/lib.rs (~640 lines) into 7 sub-modules:
  types.rs, context.rs, user_data.rs, translate.rs, http.rs,
  csv_util.rs, test_utils.rs
- Add configurable --output-dir CLI option for CSV output files
- Implement atomic file writes (write-to-temp + rename) for all CSVs
- Change compute_car_counts() to return CarCounts directly (not Result)
- Add test-utils feature gate for shared test helpers
- Add HTTP mock tests with mockito (6 tests)
- Add proptest tests for compute_car_counts (3 property tests)
- Update integration tests to use shared test utilities
- Update documentation (API.md, ARCHITECTURE.md, DATA_STRUCTURES.md)
2026-05-08 20:21:46 +02:00

350 lines
12 KiB
Markdown

# API Documentation
## Overview
This document provides comprehensive API documentation for the Top Drives Records Analyzer, including all public functions, data structures, and their usage patterns.
## Module Structure
```
src/
├── lib.rs # Thin re-export module: declares sub-modules, re-exports public types
├── types.rs # Core types: AppError, Car, BestCarRecord, TripletKey
├── context.rs # Analysis state: AnalysisContext, CarCounts, compute_car_counts
├── user_data.rs # User data: MyCarsData, load_my_cars_data
├── translate.rs # Translation: translate_track_name, translate_track_type
├── http.rs # HTTP: get_file (async download with retry)
├── csv_util.rs # CSV utilities: compare_cars, escape_csv_field
├── test_utils.rs # Test helpers: make_record, make_car
├── records.rs # Binary entry point: CLI definition and dispatch
├── commands/
│ ├── mod.rs # Command dispatch, run_analysis(), load_my_cars_or_warn()
│ ├── fetch.rs # Fetch command: download car/track/timing data
│ ├── best.rs # Best command: best.csv + very_best.csv
│ ├── trash.rs # Trash command: trash.csv
│ ├── wishlist.rs # Wishlist command: wishlist.csv, add.csv, remove.csv
│ ├── details.rs # Details command: details.csv
│ ├── track.rs # Track command: stdout query
│ └── all.rs # All command: generates all output files
├── parsing/
│ ├── mod.rs # Core parsing: parse_car_times, update_best_car, parse_all_times
│ └── car_list.rs # Car database loading: get_car_list
└── output/
└── mod.rs # CSV output: write_sorted_csv, write_best_csv, wishlist logic, etc.
```
---
## Shared Library (`src/lib.rs`)
Thin re-export module that declares 6 focused sub-modules and re-exports all public types for backward compatibility. External code can use `top_drives::Car` without knowing the internal module layout.
### Public Types
#### `Car`
**Core car information structure**
```rust
#[derive(Debug, Clone, Deserialize)]
pub struct Car {
pub rid: String, // Repository identifier
pub brand: String, // Manufacturer/brand name
#[serde(rename = "onlyName")]
pub only_name: String, // Model name (without brand)
pub year: u16, // Model year
pub rq: u8, // Rarity level (10-113)
#[serde(default)]
pub prize: bool, // Whether car is prize-only
pub guid: String, // Game-specific card identifier
}
```
**Purpose**: Represents a car entity from the records database.
**Deserialization**: Uses `serde::Deserialize` with `#[serde(rename = "onlyName")]` for the `only_name` field and `#[serde(default)]` for `prize`.
#### `BestCarRecord`
**Best performing car record for a specific track/RQ/condition**
```rust
#[derive(Debug, Clone)]
pub struct BestCarRecord {
pub car_rid: String, // Car identifier
pub brand: String, // Manufacturer
pub only_name: String, // Model name
pub year: u16, // Year
pub rq: u8, // RQ level
pub config: String, // Tune config (111, 233, etc.)
pub time: f64, // Track time in seconds
pub owned: bool, // User ownership status
pub prize: bool, // Prize car status
pub guid: String, // Game identifier
}
```
#### `TripletKey`
**Composite key for unique track conditions**
```rust
pub type TripletKey = (String, u8, String);
// Track ID RQ Level Surface Condition
```
#### `AnalysisContext`
**Mutable analysis state using concurrent DashMap**
```rust
pub struct AnalysisContext {
pub best_cars: Arc<DashMap<TripletKey, Vec<BestCarRecord>>>,
}
```
**Methods**:
- `new()` — Create a new, empty analysis context
**Thread Safety**: Uses `DashMap` for sharded internal locking, allowing concurrent access from multiple parsing tasks without a global lock.
#### `CarCounts`
**Aggregated per-car win counts**
```rust
pub struct CarCounts {
pub by_rid: HashMap<String, (BestCarRecord, usize)>,
pub guid_to_rid: HashMap<String, String>,
pub car_map: HashMap<String, Car>,
pub car_list: Vec<Car>,
}
```
#### `MyCarsData`
**Parsed user data from `my_cars.json`**
```rust
#[derive(Debug, Default)]
pub struct MyCarsData {
pub owned: HashSet<String>, // Owned car GUIDs
pub wishlist: HashSet<String>, // Wishlist car GUIDs
}
```
#### `AppError`
**Unified error type**
```rust
#[derive(Debug, thiserror::Error)]
pub enum AppError {
#[error("I/O error: {0}")]
Io(#[from] std::io::Error),
#[error("Network error: {0}")]
Network(String),
#[error("Parse error in {file}: {reason}")]
Parse { file: String, reason: String },
#[error("Missing data file: {0}")]
MissingFile(String),
#[error("Internal error: {0}")]
Internal(String),
}
```
### Public Functions
#### `translate_track_name(track_code: &str) -> String`
**Translates internal track identifiers to human-readable names**
- **Input**: Track code (e.g., `"laguna"`)
- **Output**: Track name (e.g., `"Laguna Seca"`)
- **Fallback**: Returns original code if no mapping found
- **Data source**: `track_names.json` (compiled into binary via `include_str!`)
#### `translate_track_type(track_code: &str) -> &'static str`
**Translates condition codes to surface names**
- **Input**: Condition code (e.g., `"00"`)
- **Output**: Surface name (e.g., `"Dry"`)
- **Fallback**: Returns the raw code string for unrecognized codes
#### `get_file(file_url: &str, local_file_path: &str) -> Result<(), AppError>`
**Downloads a file from a URL and saves it locally**
- Writes to a `.tmp` file first, then renames on success (atomic write)
- Retries up to 3 times on server errors (5xx) and empty responses
- Returns `AppError::Network` on HTTP failures
- Returns `AppError::Io` on file write failures
#### `load_my_cars_data(path: &str) -> Result<MyCarsData, AppError>`
**Loads and parses user car collection data**
- **Input**: Path to `my_cars.json`
- **Returns**: `MyCarsData` with owned and wishlist GUIDs
- **Errors**: `AppError::MissingFile` if file not found, `AppError::Parse` if JSON invalid
#### `compare_cars(a: &Car, b: &Car) -> std::cmp::Ordering`
**Sorting comparator for cars**
- Sorts by: RQ → Brand → Model name
#### `compute_car_counts(ctx: &AnalysisContext, car_list: Vec<Car>) -> CarCounts`
**Aggregates per-car win counts from analysis context**
- Iterates all entries in the `DashMap`
- Returns `CarCounts` with by_rid, guid_to_rid, car_map, and car_list
#### `escape_csv_field(field: &str) -> String`
**Escapes a field for safe CSV inclusion**
- Wraps in quotes if field contains comma, quote, newline, or carriage return
- Doubles internal quotes per CSV spec
---
## Records Binary (`src/records.rs`)
CLI entry point. Defines command-line arguments and dispatches to command handlers.
### CLI Global Options
| Option | Default | Description |
|--------|---------|-------------|
| `--my-cars` | `my_cars.json` | Path to user's car collection export |
| `--cars-db` | `cars_repo.json` | Path to car database file |
| `--times-dir` | `times` | Directory containing per-car timing JSON files |
| `--tracks-db` | `tracks_repo.json` | Path to tracks database file |
### CLI Commands
| Command | Description | Flags |
|---------|-------------|-------|
| `fetch` | Download latest car, track, and timing data | None |
| `best` | Generate `best.csv` and `very_best.csv` | `--min-count N` (default: 10) |
| `trash` | Generate `trash.csv` | None |
| `wishlist` | Generate `wishlist.csv`, `add.csv`, `remove.csv` | `--min-count N`, `--max-wishlist M` |
| `all` | Generate all output files in a single pass | `--min-count N`, `--max-wishlist M` |
| `details` | Generate `details.csv` with all timing data | None |
| `track` | Show best car for specific track/condition/RQ | `<track> <condition> <rq>` |
---
## Parsing Module (`src/parsing/`)
### Constants (`src/parsing/mod.rs`)
| Constant | Value | Description |
|----------|-------|-------------|
| `MAX_RQ` | 113 | Maximum RQ level for range analysis |
| `MIN_VALID_TIME` | 1.2 | Minimum valid track time (seconds) |
| `TIME_TOLERANCE` | 0.005 | Tolerance for tie detection (seconds) |
| `TEST_BOWL_FACTOR` | 2000.0 | Multiplier for Test Bowl time inversion |
| `CONCURRENCY_LIMIT` | 20 | Maximum concurrent tasks |
| `CAR_TIMING_API_BASE` | API URL | Base URL for per-car timing data |
### Key Functions
#### `parse_car_times(car, my_cars, best_cars, times_dir) -> Result<(), AppError>`
**Processes timing data for a single car** (`src/parsing/mod.rs`)
- **Synchronous** — designed to be called from `tokio::task::spawn_blocking`
- Reads car JSON file from the times directory
- Processes each configuration and track
- Applies quality filters (downvotes, minimum time)
- Handles Test Bowl time inversion
- Uses `rsplit_once("_a")` for correct track name splitting
#### `update_best_car(best_cars, track_id, car_rq, surface, new_record)`
**Updates best car records with a new performance entry** (`src/parsing/mod.rs`)
- Iterates RQ range from car's RQ to `MAX_RQ`
- Replaces existing record if new time is faster
- Adds to tie list if within `TIME_TOLERANCE`
- Prevents duplicate `car_rid` entries in tie lists
- Optimized: avoids cloning on the last iteration via `is_last` guard
#### `parse_all_times(my_cars, ctx, cars_db_path, times_dir) -> Result<Vec<Car>, AppError>`
**Orchestrates concurrent parsing of all car timing files** (`src/parsing/mod.rs`)
- Loads car list from database
- Uses `Semaphore(CONCURRENCY_LIMIT)` for bounded concurrency
- Acquires semaphore in async context, then runs sync parsing via `spawn_blocking`
- Returns the full car list for downstream use
#### `fetch_times(cars_db_path, times_dir) -> Result<(), AppError>`
**Fetches timing data files for all cars** (`src/parsing/mod.rs`)
- Uses bounded concurrency via semaphore
- Returns first error encountered, or `Ok(())` if all succeed
#### `get_car_list(cars_db_path: &str) -> Result<Vec<Car>, AppError>`
**Loads the car database** (`src/parsing/car_list.rs`)
- Uses serde deserialization for type-safe parsing
- Returns `AppError::MissingFile` or `AppError::Parse` on failure
---
## Commands Module (`src/commands/`)
### `run_analysis(owned, cars_db_path, times_dir) -> Result<(AnalysisContext, CarCounts), AppError>`
**Common analysis setup** (`src/commands/mod.rs`)
Loads car database, parses all timing files concurrently, and computes car counts.
### `load_my_cars_or_warn(path: &str) -> Result<MyCarsData, AppError>`
**Loads user data with graceful degradation** (`src/commands/mod.rs`)
- Returns empty `MyCarsData::default()` with a warning if file is missing
- Propagates parse errors and other failures
---
## Output Module (`src/output/`)
### CSV Output Functions
#### `write_sorted_csv(path, header, entries, cmp, format_row) -> Result<(), AppError>`
**Generic sorted CSV writer**
- Sorts by index (avoids cloning entries)
- Writes header row
- Formats each row via closure
#### `write_best_csv(counts)`, `write_very_best_csv(counts, min_count)`
**Generate best car CSV files**
- Format: `RQ,Brand,Model,Year,Count`
- Fields are CSV-escaped
#### `write_trash_csv(counts, owned)`
**Generate trash car CSV file**
- Filters: not best on any track, RQ < 80, not prize car
- Format: `RQ,Brand,Model,Year`
#### `write_wishlist_files(counts, owned, wishlist, min_count, max_wishlist)`
**Generate wishlist, add, and remove CSV files**
- Computes ideal wishlist once
- Derives all three files from it
- Format: `RQ,Brand,Model,Year,Count`
#### `write_details_csv(ctx)`
**Generate comprehensive timing data CSV**
- Format: `RQ,TrackID,Condition,CarRQ,Brand,Model,Year,Config,Time`
- Sorted by RQ then track ID
#### `print_best_car(ctx, track, condition, rq) -> Result<(), AppError>`
**Print best car for a specific track/condition/RQ to stdout**
#### `compute_ideal_wishlist(counts, owned, min_count, max_wishlist) -> Vec<(BestCarRecord, usize)>`
**Computes the ideal wishlist**
- Filters to cars with count >= `min_count`
- Excludes owned cars
- Sorts by RQ
- Caps at `max_wishlist`
### Sorting Helpers
#### `compare_records(a: &BestCarRecord, b: &BestCarRecord) -> std::cmp::Ordering`
**Comparison for BestCarRecord sorting**
- Sorts by: RQ → Brand → Model name