chore: Simplify pre-commit to mandatory hooks only

- Remove optional code quality hooks (black, isort, ruff, mypy, toml-sort)
  * These blocked commits when tools not installed
  * Users can run them manually when needed
- Keep only MANDATORY hooks:
  * Integration Tests (60 tests, ~7.5s)
  * Bandit Security Scan
- Both MUST pass before every commit

test/integration/conftest.py

@@ -0,0 +1,199 @@
+"""
+Shared fixtures for Predix integration tests.
+Provides common test data, mock objects, and utilities.
+"""
+import pytest
+import tempfile
+import os
+import sys
+import numpy as np
+import pandas as pd
+from pathlib import Path
+from datetime import datetime, timedelta
+from unittest.mock import MagicMock, patch
+
+# Project root
+PROJECT_ROOT = Path(__file__).parent.parent.parent
+sys.path.insert(0, str(PROJECT_ROOT))
+
+
+# =============================================================================
+# MOCK DATA FIXTURES
+# =============================================================================
+
+
+@pytest.fixture
+def mock_factor_data():
+    """Generate mock factor time series data."""
+    np.random.seed(42)
+    dates = pd.date_range("2024-01-01", periods=252, freq="B")
+    factor_values = pd.Series(np.random.randn(252), index=dates, name="test_factor")
+    forward_returns = pd.Series(np.random.randn(252) * 0.01, index=dates, name="returns")
+    return factor_values, forward_returns
+
+
+@pytest.fixture
+def mock_portfolio_returns():
+    """Generate mock portfolio return data."""
+    np.random.seed(42)
+    n_assets = 5
+    n_days = 252
+    dates = pd.date_range("2024-01-01", periods=n_days, freq="B")
+    returns = pd.DataFrame(
+        np.random.randn(n_days, n_assets) * 0.01,
+        index=dates,
+        columns=[f"asset_{i}" for i in range(n_assets)]
+    )
+    return returns
+
+
+@pytest.fixture
+def mock_expected_returns():
+    """Generate mock expected returns."""
+    return pd.Series({
+        "asset_0": 0.10, "asset_1": 0.08, "asset_2": 0.06,
+        "asset_3": 0.07, "asset_4": 0.12
+    })
+
+
+@pytest.fixture
+def mock_covariance_matrix(mock_portfolio_returns):
+    """Generate mock covariance matrix."""
+    return mock_portfolio_returns.cov() * 252
+
+
+@pytest.fixture
+def mock_backtest_metrics():
+    """Generate mock backtest metrics dictionary."""
+    return {
+        "ic": 0.08,
+        "sharpe_ratio": 1.5,
+        "annualized_return": 0.12,
+        "max_drawdown": -0.08,
+        "win_rate": 0.55,
+        "total_trades": 252,
+        "total_return": 0.15,
+        "factor_name": "TestFactor",
+        "timestamp": datetime.now().isoformat(),
+    }
+
+
+# =============================================================================
+# TEMPORARY RESOURCE FIXTURES
+# =============================================================================
+
+
+@pytest.fixture
+def temp_database_path():
+    """Create a temporary database path for testing."""
+    with tempfile.TemporaryDirectory() as tmpdir:
+        db_path = os.path.join(tmpdir, "test.db")
+        yield db_path
+
+
+@pytest.fixture
+def temp_output_dir():
+    """Create a temporary output directory for testing."""
+    with tempfile.TemporaryDirectory() as tmpdir:
+        yield Path(tmpdir)
+
+
+@pytest.fixture
+def temp_env_file():
+    """Create a temporary .env file for testing."""
+    with tempfile.TemporaryDirectory() as tmpdir:
+        env_path = os.path.join(tmpdir, ".env")
+        with open(env_path, "w") as f:
+            f.write("OPENAI_API_KEY=local\n")
+            f.write("OPENAI_API_BASE=http://localhost:8081/v1\n")
+            f.write("CHAT_MODEL=qwen3.5-35b\n")
+            f.write("EMBEDD_MODEL=nomic-embed-text\n")
+            f.write("LITELLM_PROXY_API_BASE=http://localhost:11434/v1\n")
+        yield env_path
+
+
+# =============================================================================
+# COMPONENT FIXTURES
+# =============================================================================
+
+
+@pytest.fixture
+def backtest_metrics_instance():
+    """BacktestMetrics instance for testing."""
+    from rdagent.components.backtesting.backtest_engine import BacktestMetrics
+    return BacktestMetrics(risk_free_rate=0.02)
+
+
+@pytest.fixture
+def factor_backtester_instance(temp_output_dir):
+    """FactorBacktester instance with temporary output directory."""
+    from rdagent.components.backtesting.backtest_engine import FactorBacktester
+    backtester = FactorBacktester()
+    backtester.results_path = temp_output_dir
+    return backtester
+
+
+@pytest.fixture
+def results_database_instance(temp_database_path):
+    """ResultsDatabase instance with temporary database."""
+    from rdagent.components.backtesting.results_db import ResultsDatabase
+    db = ResultsDatabase(db_path=temp_database_path)
+    yield db
+    db.close()
+
+
+@pytest.fixture
+def populated_database_instance(results_database_instance):
+    """ResultsDatabase pre-populated with test data."""
+    db = results_database_instance
+
+    # Add factors
+    db.add_factor("Momentum", "price_based")
+    db.add_factor("MeanReversion", "price_based")
+    db.add_factor("Volatility", "risk_based")
+    db.add_factor("ML_Factor", "ml_based")
+
+    # Add backtest results
+    db.add_backtest("Momentum", {
+        "ic": 0.08, "sharpe_ratio": 1.5, "annualized_return": 0.12,
+        "max_drawdown": -0.08, "win_rate": 0.55
+    })
+    db.add_backtest("MeanReversion", {
+        "ic": 0.05, "sharpe_ratio": 1.2, "annualized_return": 0.08,
+        "max_drawdown": -0.05, "win_rate": 0.52
+    })
+    db.add_backtest("Volatility", {
+        "ic": -0.03, "sharpe_ratio": 0.8, "annualized_return": 0.04,
+        "max_drawdown": -0.03, "win_rate": 0.48
+    })
+    db.add_backtest("ML_Factor", {
+        "ic": 0.12, "sharpe_ratio": 2.1, "annualized_return": 0.18,
+        "max_drawdown": -0.10, "win_rate": 0.60
+    })
+
+    # Add loop results
+    db.add_loop(1, 4, 6, 0.08, "completed")
+    db.add_loop(2, 5, 5, 0.10, "completed")
+
+    return db
+
+
+@pytest.fixture
+def correlation_analyzer_instance():
+    """CorrelationAnalyzer instance for testing."""
+    from rdagent.components.backtesting.risk_management import CorrelationAnalyzer
+    return CorrelationAnalyzer(lookback=60)
+
+
+@pytest.fixture
+def portfolio_optimizer_instance():
+    """PortfolioOptimizer instance for testing."""
+    from rdagent.components.backtesting.risk_management import PortfolioOptimizer
+    return PortfolioOptimizer()
+
+
+@pytest.fixture
+def risk_manager_instance():
+    """AdvancedRiskManager instance for testing."""
+    from rdagent.components.backtesting.risk_management import AdvancedRiskManager
+    return AdvancedRiskManager(max_pos=0.2, max_lev=5.0, max_dd=0.20)