arkforge 0.0.5

Official Python SDK for ArkForge DeFi portfolio management

ArkForge Python SDK

Python client for ArkForge DeFi portfolio management API.

Installation

pip install arkforge

Requirements

• Python 3.8+
• Valid ArkForge API key

Usage

from arkforge import ArkForgeClient
from arkforge.models import OptimizePortfolioRequest

client = ArkForgeClient(api_key="sk-arkforge-...")

result = client.optimize_portfolio(
    OptimizePortfolioRequest(
        assets=["BTC", "ETH", "SOL"],
        risk_profile="moderate"
    )
)

print(result.allocation)

Configuration

client = ArkForgeClient(
    api_key="sk-arkforge-...",
    base_url="https://api.arkforge.io",
    timeout=120,
    retry_attempts=5
)

Environment variables:

• ARKFORGE_API_KEY - API key
• ARKFORGE_BASE_URL - API base URL (default: http://localhost:3001)

API Methods

ArkForgeClient:

• optimize_portfolio(request) - Optimize portfolio allocation (live or backtest mode)
• optimize_portfolio_async(request) - Async version
• get_risk_profiles() - Get available risk profiles
• health() - Check service health

KeyManagementClient:

• create_key(request) - Create API key
• list_keys() - List API keys
• get_key_details(key_id) - Get key details
• revoke_key(key_id, reason) - Revoke API key
• rotate_key(key_id, name) - Rotate API key

Backtesting

The SDK supports backtesting by providing historical price data. The API automatically enters backtest mode when historical_data is provided.

from arkforge import ArkForgeClient, OptimizePortfolioRequest

client = ArkForgeClient(api_key="sk-arkforge-...")

# Prepare historical data (90+ days per asset)
historical_data = [
    {"symbol": "BTC", "timestamp": "2024-01-01T00:00:00Z", "price": 42350.50},
    {"symbol": "BTC", "timestamp": "2024-01-02T00:00:00Z", "price": 43120.75},
    # ... 90+ days of data per asset
]

# Optional: Historical sentiment data
historical_sentiment = [
    {
        "asset": "BTC",
        "timestamp": "2024-01-15T00:00:00Z",
        "score": 0.37,
        "category": "bullish",
        "confidence": 0.82
    }
]

# Same request interface, just add historical data
request = OptimizePortfolioRequest(
    assets=["BTC", "ETH", "SOL"],
    risk_profile="moderate",
    historical_data=historical_data,
    historical_sentiment=historical_sentiment  # Optional
)

result = client.optimize_portfolio(request)

See examples/backtesting_example.py for a complete example.

Development

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Type checking
mypy arkforge

# Linting
ruff check arkforge