from tools import setup_logging

# Use default configuration
logger = setup_logging()
logger.info("Trading started")

# Customize configuration
logger = setup_logging(
    console_level=logging.INFO,
    file_level=logging.DEBUG,
    log_dir="logs",
    log_file="my_strategy.log",
    error_log_file="my_strategy_errors.log"
)

from tools.indicators import SMA, RSI, IndicatorExecutor
import pandas as pd

# Create sample data
df = pd.DataFrame({'close': [100, 102, 101, 103, 105, 104, 106, 108, 107, 109]})

# Compute indicators
executor = IndicatorExecutor()
result = executor.compute_multiple([SMA(period=5), RSI(period=5)], df)
print(result)

from tools.factors.portfolio.backtest import PortfolioBacktest
from tools.factors.portfolio.cost_models import (
    TransactionCostModel,
    TieredSpread,
    KyleLambdaImpact,
)

# Compose realistic cost model
cost_model = TransactionCostModel(
    spread=TieredSpread(
        small_order_bps=0.5,   # <1% daily volume
        medium_order_bps=2.5,  # 1-10% daily volume
        large_order_bps=9.0,   # >10% daily volume
    ),
    market_impact=KyleLambdaImpact(
        lambda_params={'BTCUSDT': 0.00032, 'ETHUSDT': 0.00045},
    ),
)

# Run backtest with realistic costs
backtest = PortfolioBacktest(
    rebalancing_freq='1D',
    cost_model=cost_model,
    initial_capital=100_000,
)
results = backtest.run(prices, weights, volumes)
print(f"Cost drag: {results['summary']['transaction_costs_pct']:.2f}%")

from tools.execution import BinanceExchange, ExecutionEngine, SafetyGuard
from tools.portfolio import PortfolioManager
from tools.core.models import MarketOrder, OrderSide

# Connect to Binance testnet
exchange = BinanceExchange(
    api_key="your_testnet_key",
    api_secret="your_testnet_secret",
    testnet=True
)

engine = ExecutionEngine(exchange)

# Check account balances
balances = exchange.get_account_balance()

# Submit typed orders
order1 = MarketOrder(symbol="BTCUSDT", side=OrderSide.BUY, quantity=0.001)
order2 = MarketOrder(symbol="ETHUSDT", side=OrderSide.BUY, quantity=0.01)

result1 = engine.submit_order(order1)
result2 = engine.submit_order(order2)

# Check results
if result1.is_filled:
    print(f"✓ BTC order filled at ${result1.average_price:.2f}")

# Track portfolio locally
portfolio = PortfolioManager(
    initial_balance=10000,
    symbols=["BTCUSDT", "ETHUSDT"]
)

# Add safety controls
guard = SafetyGuard(
    initial_balance=10000,
    max_drawdown=0.20,  # Stop if down 20% from initial capital
    max_trades_per_hour=20,
    drawdown_from_peak=False,  # Calculate from initial, not peak (default)
    restore_state=True  # Restore circuit breaker state from DB (default)
)

# Check if trading is allowed
can_trade, reason = guard.can_trade("BTCUSDT")
if not can_trade:
    print(f"Trading blocked: {reason}")

# Reset circuit breaker if needed
guard.reset(reason="Issue resolved")

from tools.execution import FactorStrategy

# Spot trading (no leverage, no shorting)
strategy = FactorStrategy(
    symbols=["BTCUSDT", "ETHUSDT", "BNBUSDT"],
    rsi_period=14,
    max_leverage=1.0,    # Constrain sum(|weights|) <= 1.0
    allow_short=False,   # Filter out short positions
)

# Futures/margin trading (with leverage and shorting)
strategy_futures = FactorStrategy(
    symbols=["BTCUSDT", "ETHUSDT", "BNBUSDT"],
    rsi_period=14,
    max_leverage=2.0,    # Allow 2x leverage
    allow_short=True,    # Allow short positions
)