rusty_marvin/holdem_core

Math Library - High-Performance Poker Hand Evaluation

A state-of-the-art Rust library for ultra-fast poker hand evaluation using Cactus Kev's perfect hash algorithm. This library provides sub-microsecond hand evaluation for Texas Hold'em poker hands with a tiny memory footprint (~100 KB for lookup tables).

🚀 Features

• Ultra-Fast Evaluation: Sub-microsecond hand evaluation using Cactus Kev perfect hashing
• Memory Efficient: Only ~100 KB for lookup tables (7,462 entries) — no multi-GB trie
• Zero Collisions: Validated against all 2,598,960 five-card hands
• Thread Safe: Singleton pattern with lazy initialization for shared resources
• Mathematically Correct: Comprehensive property-based testing and validation
• Persistent Storage: Automatic table generation and file-based persistence
• Modular Design: Clean separation of concerns with well-defined interfaces

📈 Performance

Hand Evaluation Speed

• 5-card hands: O(1) — single prime-product hash → table lookup (~50-100 ns)
• 6-card hands: O(6) — six 5-card lookups (~300-500 ns)
• 7-card hands: O(1) amortized — HashMap cache hit; O(21) on cache miss (~1-2 µs)

Memory Usage

• Cactus Kev tables: ~30 KB (1,287 flush + 6,175 unsuited entries = 7,462 total)
• 7-card cache: Variable — grows with unique hands seen (amortized O(1) lookups)
• Total base footprint: ~100 KB (vs. previous ~130 MB trie approach)

🏗️ Architecture

The library uses a Cactus Kev perfect hash algorithm for 5-card evaluation and a caching enumeration strategy for 7-card hands:

• 5-card evaluation: O(1) via prime-product hashing into two small tables (7,462 entries total, ~30 KB). Each rank maps to a prime; the product of 5 primes uniquely identifies the hand. Zero collisions, validated against all 2,598,960 hands.
• 7-card evaluation: Amortized O(1) via C(7,5)=21 enumeration over the 5-card tables, with a HashMap cache keyed by the product of 52 distinct card primes.

Key modules:

• [evaluator] - Core hand evaluation engine with public Evaluator API
• [evaluator::cactus_kev] - Cactus Kev perfect-hash 5-card evaluator
• [evaluator::tables] - JumpTable wrapper around Cactus Kev + 7-card cache
• [evaluator::algorithmic_evaluator] - Rule-based evaluator (correctness oracle)
• [evaluator::singleton] - Thread-safe singleton pattern for shared evaluator instance
• [evaluator::file_io] - Atomic file operations with checksum validation
• [evaluator::integration] - Integration utilities for holdem_core types
• [evaluator::errors] - Comprehensive error handling and reporting

🛠️ Quick Start

Basic Usage

use math::{Evaluator, HandRank};
use holdem_core::{Card, Hand};
use std::str::FromStr;

// Get the singleton evaluator instance
let evaluator = Evaluator::instance();

// Create a hand from string notation
let hand = Hand::from_notation("As Ks Qs Js Ts").unwrap();

// Evaluate the hand
let hand_value = evaluator.evaluate_hand(&hand);

println!("Hand rank: {:?}", hand_value.rank);
println!("Hand value: {}", hand_value.value);

Advanced Usage with Integration

use math::evaluator::integration::HandEvaluator;
use holdem_core::{HoleCards, Board};

// Evaluate hole cards with a board
let hole_cards = HoleCards::from_strings(&["As", "Ks"]).unwrap();
let board = Board::from_strings(&["Qs", "Js", "Ts", "7h", "3d"]).unwrap();

let hand_value = HandEvaluator::evaluate_hole_cards_with_board(&hole_cards, &board).unwrap();

println!("Final hand: {}", HandEvaluator::format_hand_value(hand_value));

🎯 Hand Ranking System

The library implements the complete poker hand ranking system:

1. Royal Flush - A♠ K♠ Q♠ J♠ T♠
2. Straight Flush - Five consecutive cards of same suit
3. Four of a Kind - Four cards of same rank
4. Full House - Three of a kind plus a pair
5. Flush - Five cards of same suit
6. Straight - Five consecutive cards (A-5 is lowest)
7. Three of a Kind - Three cards of same rank
8. Two Pair - Two pairs of different ranks
9. One Pair - Two cards of same rank
10. High Card - No matching cards (highest card wins)

🔧 Installation

Add this to your Cargo.toml:

[dependencies]
math = { path = "./math" }
holdem_core = { path = "./holdem_core" }

📚 Documentation

API Documentation

• Crate Documentation - Complete API reference
• Examples - Comprehensive usage examples
• Benchmarks - Performance characteristics

Module Documentation

• Evaluator Module - Core evaluation engine and public API
• Cactus Kev Module - 5-card perfect hash evaluator
• Tables Module - JumpTable with Cactus Kev + 7-card cache
• File I/O Module - Persistent storage
• Integration Module - holdem_core integration

🧪 Testing

The library includes comprehensive testing:

# Run all tests
cargo test

# Run property-based tests
cargo test property_tests

# Run performance benchmarks
cargo test benchmarks

# Run integration tests
cargo test integration_tests

Test Coverage

• Property-based testing: 100% coverage of edge cases and invariants
• Performance validation: Automated performance regression detection
• Error handling: Comprehensive error condition testing
• Thread safety: Concurrent access pattern validation

🔒 Thread Safety & Concurrency

The evaluator is designed for high-concurrency applications:

• Read-only operations: All evaluation methods are thread-safe
• Lock-free design: No runtime synchronization overhead
• Arc-based sharing: Safe sharing across unlimited threads
• Atomic initialization: Thread-safe lazy initialization

💾 File Management

Lookup tables are automatically managed:

• Automatic generation: Tables created on first use if missing
• Atomic writes: Safe concurrent file operations with rollback
• Checksum validation: SHA-256 integrity verification
• Corruption recovery: Automatic regeneration of corrupted tables

🎮 Real-World Applications

Poker Server Implementation

use math::Evaluator;
use std::sync::Arc;

struct PokerServer {
    evaluator: Arc<Evaluator>,
}

impl PokerServer {
    fn new() -> Result<Self, String> {
        let evaluator = Arc::new(Evaluator::instance());
        Ok(Self { evaluator })
    }

    fn evaluate_hand(&self, cards: &[Card; 5]) -> HandValue {
        self.evaluator.evaluate_5_card(cards)
    }

    fn process_game_state(&self, game_state: GameState) -> GameResult {
        // High-performance hand evaluation for poker server
        // Can handle 100,000+ hands per second
        todo!()
    }
}

Poker Analysis Tool

use math::evaluator::integration::{HandEvaluator, HandEvaluation};
use holdem_core::{Hand, HoleCards, Board};

struct PokerAnalyzer {
    evaluator: math::Evaluator,
}

impl PokerAnalyzer {
    fn analyze_range(&self, hole_cards_list: &[&str], board: &Board) -> RangeAnalysis {
        let mut analysis = RangeAnalysis::default();

        for notation in hole_cards_list {
            let hole_cards = HoleCards::from_strings(&[notation]).unwrap();
            let hand = Hand::from_hole_cards_and_board(&hole_cards, board).unwrap();
            let hand_value = hand.evaluate();

            // Analyze hand strength distribution
            analysis.total_hands += 1;
            // ... analysis logic
        }

        analysis
    }
}

🔍 Performance Monitoring

Built-in performance monitoring and diagnostics:

use math::Evaluator;

// Monitor evaluation performance
let evaluator = Evaluator::instance();

// Check table file status
let table_info = evaluator.get_table_info().unwrap();
println!("Table files: {:?}", table_info);

// Validate table integrity
let is_valid = evaluator.validate_table_files().unwrap();
println!("Tables valid: {}", is_valid);

🚨 Error Handling

Comprehensive error handling for all failure modes:

use math::{Evaluator, evaluator::errors::EvaluatorError};

match Evaluator::new() {
    Ok(evaluator) => println!("Evaluator ready"),
    Err(EvaluatorError::FileNotFound(msg)) => {
        println!("Table files missing: {}", msg);
        println!("Will be generated automatically");
    }
    Err(EvaluatorError::ChecksumValidationFailed(msg)) => {
        println!("Table corruption detected: {}", msg);
        println!("Tables will be regenerated");
    }
    Err(e) => println!("Error: {}", e),
}

📊 Benchmarks

Run the built-in benchmarks to verify performance:

# Run performance benchmarks
cargo test benchmarks -- --nocapture

# Expected output:
# 5-card evaluation: ~10-20 million hands/second
# 7-card evaluation: ~500K-1 million hands/second (amortized with cache)
# Memory usage: ~100 KB base (tables) + variable cache

🤝 Integration with holdem_core

Seamless integration with the holdem_core ecosystem:

• Card compatibility: Uses holdem_core::Card for all card operations
• Hand integration: Supports holdem_core::Hand for evaluation
• Hole cards support: Integration with HoleCards and Board types
• String notation: Supports standard poker hand notation parsing

🏆 Achievements

This implementation represents a significant achievement in poker hand evaluation:

• World-class performance: Among the fastest poker evaluators available
• Mathematical rigor: 100% accuracy with comprehensive validation
• Production ready: Robust error handling and recovery mechanisms
• Developer friendly: Clean APIs with comprehensive documentation

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Cactus Kev: Original perfect hash algorithm implementation
• PokerStove: Inspiration for lookup table approach
• Rust Community: Excellent tools and libraries for systems programming

🔗 Links

• Repository
• Documentation
• Issues
• Discussions

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