- Replace stdout output with structured CSV file generation - Add wishlist, all commands with --min-count and --max-wishlist flags - Introduce CarCounts struct for shared analysis computation - Improve error handling: return Result instead of unwrap/panic - Add prize field to BestCarRecord - Remove TODO.md
381 lines
11 KiB
Markdown
381 lines
11 KiB
Markdown
# Top Drives Records Analyzer
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A comprehensive Rust-based tool for analyzing car performance data in the Top Drives racing game. This tool fetches track times from a community-maintained repository and provides detailed analysis including best cars, trash identification, and wishlist optimization.
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## 🚀 Features
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- **Best Car Analysis**: Find the best performing cars across all tracks and conditions
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- **Wishlist Optimization**: Identify cars to add to or remove from your wishlist
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- **Collection Cleanup**: Identify cars that can be safely removed from your collection
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- **Track-Specific Analysis**: Get detailed performance data for specific tracks and conditions
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- **RQ-Based Filtering**: Filter results by car rarity (RQ) levels
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- **Multiple Surface Types**: Support for Dry, Wet, Dirt, Snow, and other track conditions
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## 📋 Table of Contents
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- [Installation](#installation)
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- [Quick Start](#quick-start)
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- [Usage Guide](#usage-guide)
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- [Commands Reference](#commands-reference)
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- [Daily Workflow](#daily-workflow)
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- [Data Sources](#data-sources)
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- [Configuration](#configuration)
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- [Development](#development)
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- [Contributing](#contributing)
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## 🛠️ Installation
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### Prerequisites
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- [Rust](https://rustup.rs/) (latest stable version)
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- Internet connection for fetching data
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### Setup
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1. **Clone the repository**
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```bash
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git clone <repository-url>
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cd top_drives
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```
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2. **Build the project**
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```bash
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cargo build --release
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```
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3. **Run the analyzer**
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```bash
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cargo run --bin records -- fetch
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```
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## 🚦 Quick Start
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1. **Initial Setup**: Fetch the latest car and track data
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```bash
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cargo run --bin records -- fetch
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```
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2. **Full Analysis**: Generate all output files in a single pass
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```bash
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cargo run --bin records -- all
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```
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3. **Best Cars**: Find the best cars across all tracks
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```bash
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cargo run --bin records -- best
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```
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4. **Collection Cleanup**: Identify cars safe to remove
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```bash
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cargo run --bin records -- trash
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```
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5. **Wishlist Management**: Optimize your wishlist
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```bash
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cargo run --bin records -- wishlist
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```
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## 📖 Usage Guide
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### Basic Commands
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#### Fetch Data
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```bash
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cargo run --bin records -- fetch
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```
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Downloads the latest car database and track information from the community repository.
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#### Best Cars Analysis
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```bash
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cargo run --bin records -- best
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```
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Generates `best.csv` (all cars best on at least one track) and `very_best.csv` (cars best on ≥10 tracks). Both files are sorted by RQ.
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**Output Files:**
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```
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best.csv — All cars best on at least one track
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very_best.csv — Cars best on ≥10 tracks (default)
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```
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Use `--min-count N` to change the threshold for `very_best.csv`:
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```bash
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cargo run --bin records -- best --min-count 5
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```
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#### Trash Analysis
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```bash
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cargo run --bin records -- trash
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```
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Generates `trash.csv` — owned cars that are not best on any track, have RQ < 80, and are not prize cars. Sorted by RQ.
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**Output File:**
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```
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trash.csv — Owned cars safe to remove
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```
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#### Wishlist Management
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```bash
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cargo run --bin records -- wishlist
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```
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Generates `wishlist.csv` (ideal wishlist: very_best unowned cars, capped at 300), `add.csv` (cars that should be on your wishlist but aren't), and `remove.csv` (cars on your wishlist that shouldn't be). All sorted by RQ.
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**Output Files:**
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```
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wishlist.csv — Ideal wishlist (very_best unowned, capped)
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add.csv — Cars to add to wishlist
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remove.csv — Cars to remove from wishlist
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```
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Use `--min-count N` to change the threshold for very_best cars (default 10):
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```bash
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cargo run --bin records -- wishlist --min-count 5
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```
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Use `--max-wishlist M` to change the wishlist cap (default 300):
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```bash
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cargo run --bin records -- wishlist --max-wishlist 500
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```
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#### Full Analysis
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```bash
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cargo run --bin records -- all
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```
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Generates all 6 CSV files in a single parse pass. Equivalent to running `best`, `trash`, and `wishlist` together, but more efficient.
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**Output Files:**
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```
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best.csv — All cars best on at least one track
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very_best.csv — Cars best on ≥10 tracks
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trash.csv — Owned cars safe to remove
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wishlist.csv — Ideal wishlist (very_best unowned, capped)
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add.csv — Cars to add to wishlist
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remove.csv — Cars to remove from wishlist
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```
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Supports both `--min-count N` (default 10) and `--max-wishlist M` (default 300):
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```bash
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cargo run --bin records -- all --min-count 5 --max-wishlist 500
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```
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#### Detailed Performance Data
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```bash
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cargo run --bin records -- details
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```
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Generates `details.csv` with comprehensive timing data for all tracks and conditions.
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**Sample Output:**
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```
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RQ,TrackID,Condition,CarRQ,Brand,Model,Year,Config,Time
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85,laguna,Dry,85,McLaren,F1,1993,233,112.45
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82,monaco,Dry,82,Ferrari,250 GTO,1962,111,45.23
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```
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#### Track-Specific Analysis
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```bash
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cargo run --bin records -- track "Laguna Seca" "Dry" "85"
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```
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Prints the best car for a specific track, condition, and RQ combination to stdout.
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### Advanced Usage
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#### Multiple RQ Analysis
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The tool supports analyzing performance across different RQ ranges. Use the `best` and `wishlist` commands to see how cars perform at various rarity levels.
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#### Track Conditions
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The analyzer supports multiple track conditions:
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- **Dry**: Standard asphalt conditions
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- **Wet**: Rain-affected tracks
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- **Dirt**: Off-road conditions
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- **Snow**: Winter conditions
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- **Gravel**: Loose surface conditions
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## 🗃️ Commands Reference
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| Command | Description | Arguments |
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|---------|-------------|-----------|
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| `fetch` | Download latest car and track data | None |
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| `best` | Generate `best.csv` and `very_best.csv` | `[--min-count N]` |
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| `trash` | Generate `trash.csv` (owned cars safe to remove) | None |
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| `wishlist` | Generate `wishlist.csv`, `add.csv`, `remove.csv` | `[--min-count N] [--max-wishlist M]` |
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| `all` | Generate all 6 CSV files in a single pass | `[--min-count N] [--max-wishlist M]` |
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| `details` | Print detailed timing data for all tracks (stdout) | None |
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| `track` | Print best car for specific track (stdout) | `<track_name> <condition> <rq>` |
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### Flags
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| Flag | Default | Description |
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|------|---------|-------------|
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| `--min-count N` | `10` | Minimum number of tracks a car must be best on to qualify as "very best" |
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| `--max-wishlist M` | `300` | Maximum number of cars on the ideal wishlist |
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## 📅 Daily Workflow
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The typical daily workflow uses the `all` command, which runs all analysis in a single efficient parse pass:
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```bash
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cargo run --bin records -- fetch
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cargo run --bin records -- all
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```
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Or combine them:
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```bash
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cargo run --bin records -- fetch && cargo run --bin records -- all
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```
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This generates the following output files (all sorted by car RQ):
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| File | Format | Description |
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|------|--------|-------------|
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| `best.csv` | `RQ,Brand,Model,Year,Count` | All cars best on at least one track |
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| `very_best.csv` | `RQ,Brand,Model,Year,Count` | Cars best on ≥ min_count tracks |
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| `trash.csv` | `RQ,Brand,Model,Year` | Owned cars not best on any track (RQ<80, not prize) |
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| `wishlist.csv` | `RQ,Brand,Model,Year,Count` | Ideal wishlist (very_best unowned, capped) |
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| `add.csv` | `RQ,Brand,Model,Year,Count` | Cars to add to wishlist |
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| `remove.csv` | `RQ,Brand,Model,Year,Count` | Cars to remove from wishlist |
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### Workflow Steps
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1. **Fetch** fresh data from the community repository
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2. **Analyze** your collection with `all` to generate all CSV files
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3. **Review** `best.csv` to see how your cars rank
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4. **Check** `add.csv` for cars worth adding to your wishlist
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5. **Clean up** `remove.csv` entries from your wishlist
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6. **Sell** cars listed in `trash.csv` that are no longer useful
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## 📊 Data Sources
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### Car Data
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- **Source**: Community-maintained GitHub repository
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- **Format**: JSON files with performance data per car
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- **Update Frequency**: Regular updates from community contributors
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### Track Data
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- **Source**: Same community repository
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- **Coverage**: All tracks and conditions in Top Drives
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- **Format**: Structured track definitions with conditions
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### Track Names
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- **Source**: `track_names.json` (included in repository)
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- **Format**: JSON mapping track codes to human-readable names
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- **Loaded**: At compile time via `include_str!`
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### User Collection
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- **File**: `my_cars.json`
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- **Format**: Top Drives game export format
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- **Usage**: Identifies owned cars for analysis
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## ⚙️ Configuration
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### Files Structure
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```
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top_drives/
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├── src/
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│ ├── records.rs # Main analyzer binary
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│ └── lib.rs # Shared library (track name translations)
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├── times/ # Car performance data (1000+ files)
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├── cars_repo.json # Car database
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├── tracks_repo.json # Track definitions
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├── track_names.json # Track code → name mappings
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├── my_cars.json # Your car collection
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└── Cargo.toml # Rust project configuration
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```
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### Dependencies
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- **reqwest**: HTTP client for data fetching
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- **serde_json**: JSON parsing and serialization
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- **tokio**: Asynchronous runtime
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- **futures**: Async utility combinators
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- **once_cell**: Lazy static initialization
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## 🔧 Development
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### Project Structure
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The project consists of a single binary with a shared library:
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1. **records**: Primary analysis tool using JSON data (`src/records.rs`)
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2. **lib**: Shared library with track name translations (`src/lib.rs`)
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### Key Constants
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- `MAX_RQ: u8 = 113` — Maximum RQ level used in analysis (defined in `records.rs`)
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### Key Data Structures
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#### Car Information
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```rust
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struct Car {
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rid: String, // Unique car identifier
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brand: String, // Manufacturer name
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only_name: String, // Model name
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year: u16, // Model year
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rq: u8, // Rarity level (10-113)
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prize: bool, // Whether car is prize-only
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guid: String, // Game-specific identifier
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}
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```
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#### Performance Records
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```rust
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struct BestCarRecord {
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car_rid: String, // Car identifier
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brand: String, // Manufacturer
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only_name: String, // Model name
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year: u16, // Year
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rq: u8, // Rarity level
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config: String, // Tune configuration
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time: f64, // Track time
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owned: bool, // Whether you own this car
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guid: String, // Game identifier
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}
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```
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### Building
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```bash
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# Debug build
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cargo build
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# Release build
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cargo build --release
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# Run the analyzer
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cargo run --bin records
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```
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## 🤝 Contributing
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1. Fork the repository
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2. Create a feature branch
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3. Make your changes
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4. Add tests if applicable
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5. Submit a pull request
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### Adding New Tracks
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Track definitions are stored in `tracks_repo.json`. Each track includes:
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- Unique identifier
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- Display name
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- Supported conditions
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- Track type classification
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Track name mappings are stored in `track_names.json` and loaded at compile time.
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### Adding Car Data
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New car performance data should be submitted to the upstream repository following their contribution guidelines.
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## 📄 License
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This project is open source. Please check the upstream data repositories for their respective licenses.
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## 🆘 Support
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For issues and questions:
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1. Check existing documentation
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2. Review open issues
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3. Create new issue with detailed description
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## 🔄 Updates
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The tool fetches fresh data each time you run the `fetch` command. Keep your local data updated for best results.
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---
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*Built with ❤️ for the Top Drives community*
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