83 lines
2.6 KiB
Python
83 lines
2.6 KiB
Python
"""Factor Market Example.
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Demonstrates purchasing and using trading factors.
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"""
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from openclaw.factor import FactorStore
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from openclaw.core.economy import TradingEconomicTracker
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from openclaw.factor.types import FactorContext
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from datetime import datetime
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def main():
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"""Run the factor market example."""
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print("=" * 60)
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print("OpenClaw Trading - Factor Market Example")
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print("=" * 60)
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# 1. Initialize
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print("\n1. Initializing factor store...")
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tracker = TradingEconomicTracker(agent_id="factor_trader")
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store = FactorStore(agent_id="factor_trader", tracker=tracker)
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print(f" Agent ID: factor_trader")
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print(f" Initial Balance: ${tracker.balance:,.2f}")
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# 2. List available factors
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print("\n2. Available Factors:")
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factors = store.list_available()
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basic_factors = [f for f in factors if f['price'] == 0]
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advanced_factors = [f for f in factors if f['price'] > 0]
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print("\n Basic (Free):")
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for f in basic_factors[:3]:
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print(f" - {f['name']} ({f['id']})")
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print("\n Advanced (Paid):")
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for f in advanced_factors[:3]:
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print(f" - {f['name']} ({f['id']}): ${f['price']}")
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# 3. Use a basic factor
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print("\n3. Using basic factor (MA Crossover)...")
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factor = store.get_factor("buy_ma_crossover")
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if factor:
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print(f" Factor: {factor.metadata.name}")
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print(f" Type: {factor.metadata.factor_type.value}")
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print(f" Unlocked: {factor.is_unlocked}")
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# Create evaluation context
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context = FactorContext(
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symbol="AAPL",
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equity=10000.0,
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)
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result = factor.evaluate(context)
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print(f" Signal: {result.signal.value if hasattr(result, 'signal') else result}")
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# 4. Try to purchase advanced factor
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print("\n4. Purchasing advanced factor (ML Prediction)...")
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result = store.purchase("buy_ml_prediction")
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print(f" Success: {result.success}")
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print(f" Message: {result.message}")
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print(f" Remaining Balance: ${tracker.balance:,.2f}")
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# 5. Check inventory
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print("\n5. Factor Inventory:")
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print(f" Total Factors: {len(store.inventory)}")
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print(f" Unlocked: {sum(1 for f in store.inventory.values() if f.unlocked)}")
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# 6. Get purchase history
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print("\n6. Purchase History:")
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history = store.get_purchase_history()
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print(f" Total Purchases: {len(history)}")
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total_spent = sum(p.price for p in history)
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print(f" Total Spent: ${total_spent:,.2f}")
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print("\n" + "=" * 60)
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print("Factor market example complete!")
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print("=" * 60)
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if __name__ == "__main__":
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main()
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