shogiarena 0.1.1

Asynchronous tournament and SPSA tuning platform for USI shogi engines

ShogiArena

📖 Full Documentation | 日本語ドキュメント

ShogiArena is a comprehensive platform for shogi engine development and evaluation. It provides:

• Python Wrapper for USI Engines: Easy-to-use synchronous and asynchronous interfaces (SyncUsiEngine, AsyncUsiEngine) for integrating any USI-compatible shogi engine into your Python projects
• Advanced Tournament Environment: Flexible tournament execution with customizable rules, time controls, adjudication, and parallel game execution (Round-robin, SPRT, SPSA)
• Real-time Dashboard: Web-based interface for monitoring live games, analyzing statistics, and visualizing rating evolution
• Engine Parameter Tuning: Automated optimization using SPSA with gradient-based search and statistical validation via SPRT

Demo

https://github.com/user-attachments/assets/1cdebe23-b1a9-4d8e-91c0-f56ca970b569

Live tournament monitoring with real-time updates and interactive dashboard

Installation

pip install shogiarena

For development installation, see DEVELOPMENT.md.

Configuration (Optional)

While not required, running shogiarena init is recommended for:

shogiarena init

What it configures:

• Output directories: Centralized location for tournament results and databases
• Engine cache: Shared storage for engine binaries across projects
• Repository integration: Access to engine repositories (e.g., YaneuraOu) via artifact references
• Placeholder support: Use {output_dir} and {engine_dir} in configs

What you can do without it:

• ✅ Use Python API (SyncUsiEngine, AsyncUsiEngine) with direct paths
• ✅ Run tournaments with absolute paths in configs
• ✅ Everything works with default paths (./shogiarena_output, temp directories)

What requires configuration:

• ❌ Artifact references (e.g., artifact: yaneuraou@main:YaneuraOu-by-gcc)
• ❌ Placeholder variables in configs (e.g., path: "{engine_dir}/myengine")
• ❌ Private GitHub repository access (requires github_token in settings)

See detailed setup guide for more options.

Quick Examples

Example 1: Use Engine in Python

The simplest way to integrate a USI engine into your Python code:

from shogiarena.arena.engines.sync_usi_engine import SyncUsiEngine
from shogiarena.arena.engines.usi_think import UsiThinkRequest

# Use any USI engine
with SyncUsiEngine.from_config_path("engine.yaml") as engine:
    request = UsiThinkRequest(time_ms=5000)
    result = engine.think(sfen="startpos", request=request)
    print(f"Bestmove: {result.bestmove}, Score: {result.score_cp}cp")

Or with a direct path:

from shogiarena.arena.engines.sync_usi_engine import SyncUsiEngine

with SyncUsiEngine.from_path("/path/to/engine") as engine:
    result = engine.think(sfen="startpos", request=UsiThinkRequest(nodes=1000000))
    print(result.bestmove)

Example 2: Run Tournament via CLI

Use the provided example configuration:

# Tournament (Round-robin)
shogiarena run tournament examples/configs/run/tournament/example.yaml

# SPRT (Statistical testing)
shogiarena run sprt examples/configs/run/sprt/example.yaml

# SPSA (Parameter tuning)
shogiarena run spsa examples/configs/run/spsa/example.yaml

The dashboard will automatically open at http://localhost:8080 to monitor progress.

Note: Example configs may use placeholders like {output_dir} and {engine_dir}. You can either run shogiarena init (alias for shogiarena config init) to set them up, or replace placeholders with absolute paths. See Example Configurations for details.

Core Features

Tournament Modes

Round-Robin Tournament

shogiarena run tournament examples/configs/run/tournament/example.yaml

Run comprehensive engine comparisons with customizable time controls, opening positions, and adjudication rules.

SPRT (Sequential Probability Ratio Test)

shogiarena run sprt examples/configs/run/sprt/example.yaml

Efficiently test if one engine version is statistically stronger than another with early stopping.

SPSA (Simultaneous Perturbation Stochastic Approximation)

shogiarena run spsa examples/configs/run/spsa/example.yaml

Optimize engine parameters using gradient-based stochastic search with parallel game execution.

See Tournament Guide and SPSA Guide for detailed configuration options.

Dashboard Features

• Live Updates: Real-time game progress and statistics
• Interactive Visualizations: Rating evolution, win-rate matrices, parameter convergence
• Game Browser: Replay and analyze individual games
• SPSA Tracking: Monitor parameter values and gradient estimates

Python Library

Beyond simple engine interaction, the library provides advanced features:

Asynchronous Engine Control

import asyncio
from shogiarena.arena.engines.engine_factory import EngineFactory
from shogiarena.arena.engines.usi_think import UsiThinkRequest

async def compare_engines():
    # Create multiple engines in parallel
    engine1 = await EngineFactory.create_engine("engine1.yaml")
    engine2 = await EngineFactory.create_engine("engine2.yaml")
    await asyncio.gather(engine1.start(), engine2.start())
    
    # Analyze same position concurrently
    results = await asyncio.gather(
        engine1.think(sfen="startpos", request=UsiThinkRequest(time_ms=5000)),
        engine2.think(sfen="startpos", request=UsiThinkRequest(time_ms=5000)),
    )

Programmatic Tournament Execution

from shogiarena.arena.configs.tournament import ArenaConfig
from shogiarena.arena.runners.tournament_runner import TournamentRunner

# Run tournaments programmatically with full control
config = ArenaConfig.from_yaml("tournament.yaml")
runner = TournamentRunner(config)
runner.run_sync()  # or: await runner.run() for async

Custom Analysis Tools

from shogiarena.arena.engines.sync_usi_engine import SyncUsiEngine
from shogiarena.arena.engines.usi_think import UsiThinkRequest

# Build custom analysis workflows
with SyncUsiEngine.from_path("/path/to/engine") as engine:
    for position in my_position_list:
        result = engine.think(sfen=position, request=UsiThinkRequest(nodes=1000000))
        analyze_and_store(result)

See Python Library Guide for detailed API documentation.

Documentation

• Getting Started - Installation and first steps
• User Guide - Tournament setup, SPSA tuning, Python API
• Technical Documentation - Architecture, USI protocol, services
• API Reference - Core classes and modules
• Development Guide - Contributing, building, testing

Example Configurations

The examples/configs/ directory provides ready-to-use configuration templates:

Tournament Configurations:

• examples/configs/run/tournament/example.yaml - Comprehensive tournament setup with detailed comments
• examples/configs/run/sprt/example.yaml - SPRT testing configuration
• examples/configs/run/spsa/example.yaml - SPSA parameter tuning setup

Engine Configurations:

• examples/configs/resources/engines/ - Engine configuration templates with various options

Instance Configurations:

• examples/configs/resources/instances/local_example.yaml - Local execution
• examples/configs/resources/instances/ssh_example.yaml - Remote SSH execution
• examples/configs/resources/instances/ssh_pool_example.yaml - SSH instance pool

Note: Example configurations may use placeholders like {output_dir} and {engine_dir}. Run shogiarena init (alias for shogiarena config init) to configure these paths, or replace them with absolute paths.

License

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