mirror of
https://github.com/NicolasBohn/NexQuant.git
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TPTBusiness
cbe1c52e00
Rename all source files, scripts, tests, documentation, and configuration from Predix/predix to NexQuant/nexquant across the entire codebase.
869 lines
29 KiB
Python
869 lines
29 KiB
Python
"""
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Tests for Strategy Worker (LLMStrategyGenerator, BacktestEngine, AcceptanceGate, StrategySaver).
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Public test file - references closed-source module at rdagent/scenarios/qlib/local/strategy_worker.py
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"""
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import os
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import json
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import time
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import tempfile
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import subprocess
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from pathlib import Path
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from unittest.mock import Mock, patch, MagicMock
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import pytest
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import numpy as np
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import pandas as pd
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from rdagent.scenarios.qlib.local.strategy_worker import (
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LLMStrategyGenerator,
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BacktestEngine,
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AcceptanceGate,
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StrategySaver,
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StrategyWorker,
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)
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# =============================================================================
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# Fixtures
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# =============================================================================
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@pytest.fixture
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def sample_factors():
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"""Sample factor metadata list."""
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return [
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{'name': 'momentum_1d', 'ic': 0.15, 'description': '1-day momentum'},
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{'name': 'mean_reversion', 'ic': -0.12, 'description': 'Mean reversion signal'},
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{'name': 'volatility', 'ic': 0.08, 'description': 'Volatility indicator'},
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]
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@pytest.fixture
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def sample_close():
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"""Sample OHLCV close price series."""
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dates = pd.date_range('2024-01-01', periods=1000, freq='1min')
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np.random.seed(42)
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prices = 1.0850 + np.cumsum(np.random.randn(1000) * 0.0001)
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return pd.Series(prices, index=dates, name='$close')
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@pytest.fixture
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def sample_factors_df(sample_close):
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"""Sample factor values DataFrame."""
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np.random.seed(42)
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return pd.DataFrame({
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'momentum_1d': np.random.randn(len(sample_close)),
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'mean_reversion': np.random.randn(len(sample_close)),
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'volatility': np.random.randn(len(sample_close)),
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}, index=sample_close.index)
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@pytest.fixture
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def llm_generator():
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"""LLM Strategy Generator instance."""
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return LLMStrategyGenerator()
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@pytest.fixture
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def backtest_engine():
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"""Backtest Engine instance."""
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return BacktestEngine(timeout=60)
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@pytest.fixture
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def acceptance_gate():
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"""Acceptance Gate instance."""
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return AcceptanceGate()
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@pytest.fixture
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def strategy_saver(tmp_path):
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"""Strategy Saver instance with temp directory."""
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return StrategySaver(output_dir=str(tmp_path))
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# =============================================================================
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# LLMStrategyGenerator Tests
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# =============================================================================
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class TestLLMStrategyGenerator:
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"""Test LLM strategy generation."""
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def test_init_defaults(self):
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"""Test initialization with defaults."""
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gen = LLMStrategyGenerator()
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assert gen.llm_url == 'http://localhost:8081/v1/chat/completions'
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assert gen.model_name == 'qwen3.5-35b'
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assert gen.timeout == 120
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assert gen.max_tokens == 4096
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assert gen.temperature == 0.5
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def test_init_custom(self):
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"""Test initialization with custom parameters."""
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gen = LLMStrategyGenerator(
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llm_url='http://custom:9999/v1',
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model_name='custom-model',
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timeout=60,
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max_tokens=2048,
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temperature=0.8,
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)
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assert gen.llm_url == 'http://custom:9999/v1'
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assert gen.model_name == 'custom-model'
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assert gen.timeout == 60
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assert gen.max_tokens == 2048
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assert gen.temperature == 0.8
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@patch('rdagent.scenarios.qlib.local.strategy_worker.requests.post')
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def test_generate_strategy_success(self, mock_post, llm_generator, sample_factors, sample_close):
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"""Test successful strategy generation."""
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# Mock LLM response
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mock_response = Mock()
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mock_response.json.return_value = {
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'choices': [{
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'message': {
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'content': '''Here is the strategy:
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```python
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def generate_signal(factors, close):
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import pandas as pd
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import numpy as np
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signal = pd.Series(0, index=close.index)
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signal[factors['momentum_1d'] > 0.5] = 1
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signal[factors['momentum_1d'] < -0.5] = -1
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return signal
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```
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'''
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}
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}]
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}
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mock_response.raise_for_status = Mock()
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mock_post.return_value = mock_response
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result = llm_generator.generate_strategy(
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factors=sample_factors,
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close=sample_close,
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)
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assert result['success'] is True
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assert 'def generate_signal' in result['code']
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assert result['error'] is None
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assert len(result['factor_names']) == 3
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assert result['attempt_time'] > 0
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@patch('rdagent.scenarios.qlib.local.strategy_worker.requests.post')
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def test_generate_strategy_no_code_block(self, mock_post, llm_generator, sample_factors, sample_close):
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"""Test failure when no code block found."""
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mock_response = Mock()
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mock_response.json.return_value = {
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'choices': [{
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'message': {
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'content': 'This is just text, no code.'
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}
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}]
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}
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mock_response.raise_for_status = Mock()
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mock_post.return_value = mock_response
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result = llm_generator.generate_strategy(
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factors=sample_factors,
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close=sample_close,
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)
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assert result['success'] is False
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assert 'No Python code block found' in result['error']
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@patch('rdagent.scenarios.qlib.local.strategy_worker.requests.post')
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def test_generate_strategy_syntax_error(self, mock_post, llm_generator, sample_factors, sample_close):
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"""Test failure when generated code has syntax errors."""
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mock_response = Mock()
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mock_response.json.return_value = {
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'choices': [{
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'message': {
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'content': '''```python
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def generate_signal(factors, close):
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import pandas as pd
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if True
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print("missing colon")
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```'''
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}
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}]
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}
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mock_response.raise_for_status = Mock()
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mock_post.return_value = mock_response
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result = llm_generator.generate_strategy(
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factors=sample_factors,
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close=sample_close,
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)
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assert result['success'] is False
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assert 'syntax errors' in result['error']
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@patch('rdagent.scenarios.qlib.local.strategy_worker.requests.post')
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def test_generate_strategy_timeout(self, mock_post, llm_generator, sample_factors, sample_close):
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"""Test timeout handling."""
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import requests
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mock_post.side_effect = requests.Timeout('Request timed out')
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result = llm_generator.generate_strategy(
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factors=sample_factors,
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close=sample_close,
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)
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assert result['success'] is False
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assert 'Timeout' in result['error']
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@patch('rdagent.scenarios.qlib.local.strategy_worker.requests.post')
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def test_generate_strategy_connection_error(self, mock_post, llm_generator, sample_factors, sample_close):
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"""Test connection error handling."""
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import requests
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mock_post.side_effect = requests.ConnectionError('Connection refused')
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result = llm_generator.generate_strategy(
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factors=sample_factors,
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close=sample_close,
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)
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assert result['success'] is False
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assert 'Connection failed' in result['error']
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def test_extract_code_python_block(self):
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"""Test extracting code from ```python block."""
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gen = LLMStrategyGenerator()
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response = '''Some text
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```python
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def my_func():
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pass
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```
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More text'''
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code = gen._extract_code(response)
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assert code == 'def my_func():\n pass'
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def test_extract_code_plain_block(self):
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"""Test extracting code from ``` block."""
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gen = LLMStrategyGenerator()
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response = '''```
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def my_func():
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pass
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```'''
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code = gen._extract_code(response)
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assert code == 'def my_func():\n pass'
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def test_extract_code_no_block(self):
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"""Test when no code block present."""
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gen = LLMStrategyGenerator()
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response = 'Just plain text, no code.'
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code = gen._extract_code(response)
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assert code is None
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def test_validate_code_valid(self):
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"""Test validation of valid code."""
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gen = LLMStrategyGenerator()
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assert gen._validate_code('def foo(): pass') is True
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def test_validate_code_invalid(self):
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"""Test validation of invalid code."""
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gen = LLMStrategyGenerator()
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assert gen._validate_code('def foo(\n') is False
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@patch.object(LLMStrategyGenerator, 'generate_strategy')
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def test_generate_with_retry_success(self, mock_gen, llm_generator, sample_factors, sample_close):
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"""Test successful generation with retry logic."""
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mock_gen.return_value = {
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'success': True,
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'code': 'def generate_signal(f, c): pass',
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'factor_names': ['f1'],
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'llm_response': 'response',
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'error': None,
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'attempt_time': 1.5,
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}
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result = llm_generator.generate_with_retry(
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factors=sample_factors,
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close=sample_close,
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max_retries=3,
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)
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assert result['success'] is True
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assert mock_gen.call_count == 1
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@patch.object(LLMStrategyGenerator, 'generate_strategy')
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def test_generate_with_retry_all_fail(self, mock_gen, llm_generator, sample_factors, sample_close):
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"""Test all retries failing."""
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mock_gen.return_value = {
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'success': False,
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'code': '',
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'factor_names': ['f1'],
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'llm_response': '',
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'error': 'Test error',
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'attempt_time': 1.0,
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}
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result = llm_generator.generate_with_retry(
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factors=sample_factors,
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close=sample_close,
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max_retries=3,
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)
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assert result['success'] is False
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assert mock_gen.call_count == 3
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def test_format_factors(self, llm_generator, sample_factors):
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"""Test factor formatting for LLM prompt."""
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text = llm_generator._format_factors(sample_factors)
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assert 'momentum_1d' in text
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assert 'IC=0.1500' in text
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assert 'Mean reversion signal' in text
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# =============================================================================
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# BacktestEngine Tests
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# =============================================================================
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class TestBacktestEngine:
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"""Test backtest engine."""
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def test_init_defaults(self):
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"""Test initialization with defaults."""
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engine = BacktestEngine()
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assert engine.stop_loss == 0.02
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assert engine.take_profit == 0.04
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assert engine.trail_activation == 0.015
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assert engine.trailing_stop == 0.015
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assert engine.transaction_cost == 0.00015
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assert engine.timeout == 300
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def test_init_custom(self):
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"""Test initialization with custom parameters."""
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engine = BacktestEngine(
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stop_loss=0.01,
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take_profit=0.03,
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trail_activation=0.01,
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trailing_stop=0.01,
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transaction_cost=0.0001,
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timeout=120,
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)
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assert engine.stop_loss == 0.01
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assert engine.take_profit == 0.03
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assert engine.trail_activation == 0.01
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assert engine.trailing_stop == 0.01
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assert engine.transaction_cost == 0.0001
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assert engine.timeout == 120
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def test_run_backtest_valid_strategy(self, backtest_engine, sample_factors_df, sample_close):
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"""Test backtest with valid strategy."""
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strategy_code = '''
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def generate_signal(factors, close):
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import pandas as pd
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import numpy as np
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signal = pd.Series(0, index=close.index)
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signal[factors['momentum_1d'] > 0.5] = 1
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signal[factors['momentum_1d'] < -0.5] = -1
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return signal
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'''
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result = backtest_engine.run_backtest(
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strategy_code=strategy_code,
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factors=sample_factors_df,
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close=sample_close,
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)
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assert result['success'] is True
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assert 'total_trades' in result
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assert 'sharpe_ratio' in result
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assert 'max_drawdown' in result
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assert isinstance(result['total_trades'], int)
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def test_run_backtest_invalid_strategy(self, backtest_engine, sample_factors_df, sample_close):
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"""Test backtest with strategy that raises error."""
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strategy_code = '''
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def generate_signal(factors, close):
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raise ValueError("Test error")
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'''
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result = backtest_engine.run_backtest(
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strategy_code=strategy_code,
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factors=sample_factors_df,
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close=sample_close,
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)
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assert result['success'] is False
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assert 'error' in result
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@patch('rdagent.scenarios.qlib.local.strategy_worker.subprocess.run')
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def test_run_subprocess_timeout(self, mock_run, backtest_engine):
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"""Test subprocess timeout handling."""
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import subprocess
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mock_run.side_effect = subprocess.TimeoutExpired(cmd='python', timeout=60)
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result = backtest_engine._run_subprocess(Path('/tmp/run.py'))
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assert result['success'] is False
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assert 'Timeout' in result['error']
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@patch('rdagent.scenarios.qlib.local.strategy_worker.subprocess.run')
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def test_run_subprocess_success(self, mock_run, backtest_engine):
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"""Test successful subprocess execution."""
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mock_proc = Mock()
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mock_proc.returncode = 0
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mock_proc.stdout = json.dumps({
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'ic': 0.05,
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'sharpe_ratio': 1.2,
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'max_drawdown': -0.08,
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'win_rate': 0.55,
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'total_trades': 25,
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'wins': 14,
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'losses': 11,
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'total_return': 0.05,
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'final_equity': 1.05,
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'avg_trade_pnl': 0.002,
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'sl_pct': 0.02,
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'tp_pct': 0.04,
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'trail_activation': 0.015,
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'trail_stop': 0.015,
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'transaction_cost': 0.00015,
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})
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mock_run.return_value = mock_proc
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result = backtest_engine._run_subprocess(Path('/tmp/run.py'))
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assert result['success'] is True
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assert result['sharpe_ratio'] == 1.2
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assert result['total_trades'] == 25
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# =============================================================================
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# AcceptanceGate Tests
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# =============================================================================
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class TestAcceptanceGate:
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"""Test acceptance gate."""
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def test_init_defaults(self):
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"""Test initialization with defaults."""
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gate = AcceptanceGate()
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assert gate.min_ic == 0.02
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assert gate.min_sharpe == 0.5
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assert gate.min_trades == 10
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assert gate.max_drawdown == -0.15
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assert gate.ftmo_max_sl == 0.02
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assert gate.ftmo_max_daily_loss == 0.05
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assert gate.ftmo_max_dd == 0.10
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def test_evaluate_passing_strategy(self, acceptance_gate):
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"""Test evaluation of passing strategy."""
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result = {
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'ic': 0.05,
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'sharpe_ratio': 1.2,
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'max_drawdown': -0.08,
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'total_trades': 25,
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'sl_pct': 0.02,
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}
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evaluation = acceptance_gate.evaluate(result)
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assert evaluation['passed'] is True
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assert len(evaluation['reasons']) == 0
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assert evaluation['checks']['ic']['passed'] is True
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assert evaluation['checks']['sharpe']['passed'] is True
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assert evaluation['checks']['trades']['passed'] is True
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assert evaluation['checks']['max_drawdown']['passed'] is True
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assert evaluation['checks']['ftmo_sl']['passed'] is True
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assert evaluation['checks']['ftmo_max_dd']['passed'] is True
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def test_evaluate_failing_ic(self, acceptance_gate):
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"""Test failure due to low IC."""
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result = {
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'ic': 0.01,
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'sharpe_ratio': 1.2,
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'max_drawdown': -0.08,
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'total_trades': 25,
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'sl_pct': 0.02,
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}
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evaluation = acceptance_gate.evaluate(result)
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assert evaluation['passed'] is False
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assert any('IC' in r for r in evaluation['reasons'])
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assert evaluation['checks']['ic']['passed'] is False
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def test_evaluate_failing_sharpe(self, acceptance_gate):
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"""Test failure due to low Sharpe."""
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result = {
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'ic': 0.05,
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'sharpe_ratio': 0.3,
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'max_drawdown': -0.08,
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'total_trades': 25,
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'sl_pct': 0.02,
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}
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evaluation = acceptance_gate.evaluate(result)
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assert evaluation['passed'] is False
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assert any('Sharpe' in r for r in evaluation['reasons'])
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assert evaluation['checks']['sharpe']['passed'] is False
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def test_evaluate_failing_trades(self, acceptance_gate):
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"""Test failure due to insufficient trades."""
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result = {
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'ic': 0.05,
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'sharpe_ratio': 1.2,
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'max_drawdown': -0.08,
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'total_trades': 5,
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'sl_pct': 0.02,
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}
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evaluation = acceptance_gate.evaluate(result)
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assert evaluation['passed'] is False
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assert any('trades' in r.lower() for r in evaluation['reasons'])
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assert evaluation['checks']['trades']['passed'] is False
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def test_evaluate_failing_drawdown(self, acceptance_gate):
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"""Test failure due to excessive drawdown."""
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result = {
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'ic': 0.05,
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'sharpe_ratio': 1.2,
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'max_drawdown': -0.20,
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'total_trades': 25,
|
|
'sl_pct': 0.02,
|
|
}
|
|
|
|
evaluation = acceptance_gate.evaluate(result)
|
|
|
|
assert evaluation['passed'] is False
|
|
assert any('DD' in r or 'drawdown' in r.lower() for r in evaluation['reasons'])
|
|
assert evaluation['checks']['max_drawdown']['passed'] is False
|
|
assert evaluation['checks']['ftmo_max_dd']['passed'] is False
|
|
|
|
def test_evaluate_failing_ftmo_sl(self, acceptance_gate):
|
|
"""Test FTMO stop loss violation."""
|
|
result = {
|
|
'ic': 0.05,
|
|
'sharpe_ratio': 1.2,
|
|
'max_drawdown': -0.08,
|
|
'total_trades': 25,
|
|
'sl_pct': 0.03,
|
|
}
|
|
|
|
evaluation = acceptance_gate.evaluate(result)
|
|
|
|
assert evaluation['passed'] is False
|
|
assert evaluation['checks']['ftmo_sl']['passed'] is False
|
|
|
|
def test_evaluate_ic_none(self, acceptance_gate):
|
|
"""Test when IC is None."""
|
|
result = {
|
|
'ic': None,
|
|
'sharpe_ratio': 1.2,
|
|
'max_drawdown': -0.08,
|
|
'total_trades': 25,
|
|
'sl_pct': 0.02,
|
|
}
|
|
|
|
evaluation = acceptance_gate.evaluate(result)
|
|
|
|
assert evaluation['passed'] is False
|
|
assert any('IC is None' in r for r in evaluation['reasons'])
|
|
|
|
|
|
# =============================================================================
|
|
# StrategySaver Tests
|
|
# =============================================================================
|
|
|
|
class TestStrategySaver:
|
|
"""Test strategy saver."""
|
|
|
|
def test_init_default(self):
|
|
"""Test initialization with defaults."""
|
|
saver = StrategySaver()
|
|
assert 'results/strategies_new' in str(saver.output_dir)
|
|
|
|
def test_init_custom(self, tmp_path):
|
|
"""Test initialization with custom directory."""
|
|
saver = StrategySaver(output_dir=str(tmp_path))
|
|
assert saver.output_dir == tmp_path
|
|
|
|
def test_save_strategy(self, strategy_saver):
|
|
"""Test saving accepted strategy."""
|
|
filepath = strategy_saver.save_strategy(
|
|
name='TestStrategy',
|
|
code='def generate_signal(f, c): pass',
|
|
factor_names=['f1', 'f2'],
|
|
backtest_result={
|
|
'ic': 0.05,
|
|
'sharpe_ratio': 1.2,
|
|
'max_drawdown': -0.08,
|
|
'total_trades': 25,
|
|
'sl_pct': 0.02,
|
|
'tp_pct': 0.04,
|
|
},
|
|
acceptance_result={
|
|
'passed': True,
|
|
'checks': {},
|
|
},
|
|
)
|
|
|
|
assert filepath.exists()
|
|
assert filepath.suffix == '.json'
|
|
|
|
# Verify content
|
|
with open(filepath) as f:
|
|
data = json.load(f)
|
|
|
|
assert data['strategy_name'] == 'TestStrategy'
|
|
assert 'def generate_signal' in data['code']
|
|
assert data['factor_names'] == ['f1', 'f2']
|
|
assert data['metrics']['ic'] == 0.05
|
|
assert data['metrics']['sharpe_ratio'] == 1.2
|
|
assert 'risk_config' in data
|
|
assert 'acceptance_result' in data
|
|
|
|
def test_save_strategy_with_metadata(self, strategy_saver):
|
|
"""Test saving strategy with additional metadata."""
|
|
filepath = strategy_saver.save_strategy(
|
|
name='TestStrategy',
|
|
code='def generate_signal(f, c): pass',
|
|
factor_names=['f1'],
|
|
backtest_result={
|
|
'ic': 0.05,
|
|
'sharpe_ratio': 1.2,
|
|
'max_drawdown': -0.08,
|
|
'total_trades': 25,
|
|
'sl_pct': 0.02,
|
|
'tp_pct': 0.04,
|
|
},
|
|
acceptance_result={
|
|
'passed': True,
|
|
'checks': {},
|
|
},
|
|
metadata={'version': '1.0', 'author': 'NexQuant'},
|
|
)
|
|
|
|
with open(filepath) as f:
|
|
data = json.load(f)
|
|
|
|
assert data['metadata']['version'] == '1.0'
|
|
assert data['metadata']['author'] == 'NexQuant'
|
|
|
|
def test_save_strategy_with_llm_response(self, strategy_saver):
|
|
"""Test saving strategy with LLM response preview."""
|
|
filepath = strategy_saver.save_strategy(
|
|
name='TestStrategy',
|
|
code='def generate_signal(f, c): pass',
|
|
factor_names=['f1'],
|
|
backtest_result={
|
|
'ic': 0.05,
|
|
'sharpe_ratio': 1.2,
|
|
'max_drawdown': -0.08,
|
|
'total_trades': 25,
|
|
'sl_pct': 0.02,
|
|
'tp_pct': 0.04,
|
|
},
|
|
acceptance_result={
|
|
'passed': True,
|
|
'checks': {},
|
|
},
|
|
llm_response='This is a very long LLM response...',
|
|
)
|
|
|
|
with open(filepath) as f:
|
|
data = json.load(f)
|
|
|
|
assert 'llm_response_preview' in data
|
|
assert len(data['llm_response_preview']) <= 1000
|
|
|
|
def test_filename_format(self, strategy_saver):
|
|
"""Test filename format: timestamp_name.json."""
|
|
filepath = strategy_saver.save_strategy(
|
|
name='My Strategy',
|
|
code='pass',
|
|
factor_names=['f1'],
|
|
backtest_result={'ic': 0.05, 'sharpe_ratio': 1.2, 'max_drawdown': -0.08,
|
|
'total_trades': 25, 'sl_pct': 0.02, 'tp_pct': 0.04},
|
|
acceptance_result={'passed': True, 'checks': {}},
|
|
)
|
|
|
|
# Should match: {timestamp}_{name}.json
|
|
assert filepath.name.endswith('_My_Strategy.json')
|
|
assert filepath.name.split('_')[0].isdigit()
|
|
|
|
|
|
# =============================================================================
|
|
# StrategyWorker Integration Tests
|
|
# =============================================================================
|
|
|
|
class TestStrategyWorker:
|
|
"""Test Strategy Worker integration."""
|
|
|
|
def test_init_defaults(self):
|
|
"""Test initialization with defaults."""
|
|
worker = StrategyWorker()
|
|
assert isinstance(worker.llm_generator, LLMStrategyGenerator)
|
|
assert isinstance(worker.backtest_engine, BacktestEngine)
|
|
assert isinstance(worker.acceptance_gate, AcceptanceGate)
|
|
assert isinstance(worker.strategy_saver, StrategySaver)
|
|
|
|
def test_init_custom(self):
|
|
"""Test initialization with custom components."""
|
|
custom_gen = Mock()
|
|
custom_bt = Mock()
|
|
custom_gate = Mock()
|
|
custom_saver = Mock()
|
|
|
|
worker = StrategyWorker(
|
|
llm_generator=custom_gen,
|
|
backtest_engine=custom_bt,
|
|
acceptance_gate=custom_gate,
|
|
strategy_saver=custom_saver,
|
|
)
|
|
|
|
assert worker.llm_generator == custom_gen
|
|
assert worker.backtest_engine == custom_bt
|
|
assert worker.acceptance_gate == custom_gate
|
|
assert worker.strategy_saver == custom_saver
|
|
|
|
@patch.object(StrategyWorker, '__init__', lambda self: None)
|
|
def test_workflow_generation_failure(self, sample_factors, sample_factors_df, sample_close):
|
|
"""Test workflow when generation fails."""
|
|
worker = StrategyWorker()
|
|
worker.llm_generator = Mock()
|
|
worker.llm_generator.generate_with_retry.return_value = {
|
|
'success': False,
|
|
'error': 'LLM error',
|
|
'code': '',
|
|
}
|
|
|
|
result = worker.run_workflow(
|
|
factors=sample_factors,
|
|
factor_data=sample_factors_df,
|
|
close=sample_close,
|
|
strategy_name='TestStrategy',
|
|
)
|
|
|
|
assert result['success'] is False
|
|
assert result['stage'] == 'generation'
|
|
assert result['error'] == 'LLM error'
|
|
|
|
@patch.object(StrategyWorker, '__init__', lambda self: None)
|
|
def test_workflow_backtest_failure(self, sample_factors, sample_factors_df, sample_close):
|
|
"""Test workflow when backtest fails."""
|
|
worker = StrategyWorker()
|
|
worker.llm_generator = Mock()
|
|
worker.llm_generator.generate_with_retry.return_value = {
|
|
'success': True,
|
|
'code': 'def generate_signal(f, c): pass',
|
|
'factor_names': ['f1'],
|
|
'llm_response': 'response',
|
|
'error': None,
|
|
'attempt_time': 1.0,
|
|
}
|
|
worker.backtest_engine = Mock()
|
|
worker.backtest_engine.run_backtest.return_value = {
|
|
'success': False,
|
|
'error': 'Backtest error',
|
|
}
|
|
|
|
result = worker.run_workflow(
|
|
factors=sample_factors,
|
|
factor_data=sample_factors_df,
|
|
close=sample_close,
|
|
strategy_name='TestStrategy',
|
|
)
|
|
|
|
assert result['success'] is False
|
|
assert result['stage'] == 'backtest'
|
|
assert result['error'] == 'Backtest error'
|
|
|
|
@patch.object(StrategyWorker, '__init__', lambda self: None)
|
|
def test_workflow_acceptance_failure(self, sample_factors, sample_factors_df, sample_close):
|
|
"""Test workflow when acceptance gate rejects."""
|
|
worker = StrategyWorker()
|
|
worker.llm_generator = Mock()
|
|
worker.llm_generator.generate_with_retry.return_value = {
|
|
'success': True,
|
|
'code': 'def generate_signal(f, c): pass',
|
|
'factor_names': ['f1'],
|
|
'llm_response': 'response',
|
|
'error': None,
|
|
'attempt_time': 1.0,
|
|
}
|
|
worker.backtest_engine = Mock()
|
|
worker.backtest_engine.run_backtest.return_value = {
|
|
'success': True,
|
|
'ic': 0.01,
|
|
'sharpe_ratio': 0.3,
|
|
'max_drawdown': -0.08,
|
|
'total_trades': 25,
|
|
'sl_pct': 0.02,
|
|
}
|
|
worker.acceptance_gate = Mock()
|
|
worker.acceptance_gate.evaluate.return_value = {
|
|
'passed': False,
|
|
'reasons': ['IC too low', 'Sharpe too low'],
|
|
'checks': {},
|
|
}
|
|
|
|
result = worker.run_workflow(
|
|
factors=sample_factors,
|
|
factor_data=sample_factors_df,
|
|
close=sample_close,
|
|
strategy_name='TestStrategy',
|
|
)
|
|
|
|
assert result['success'] is False
|
|
assert result['stage'] == 'acceptance'
|
|
assert 'IC too low' in result['rejection_reasons']
|
|
|
|
@patch.object(StrategyWorker, '__init__', lambda self: None)
|
|
def test_workflow_success(self, sample_factors, sample_factors_df, sample_close, tmp_path):
|
|
"""Test successful workflow completion."""
|
|
worker = StrategyWorker()
|
|
worker.llm_generator = Mock()
|
|
worker.llm_generator.generate_with_retry.return_value = {
|
|
'success': True,
|
|
'code': 'def generate_signal(f, c): pass',
|
|
'factor_names': ['f1'],
|
|
'llm_response': 'response',
|
|
'error': None,
|
|
'attempt_time': 1.0,
|
|
}
|
|
worker.backtest_engine = Mock()
|
|
worker.backtest_engine.run_backtest.return_value = {
|
|
'success': True,
|
|
'ic': 0.05,
|
|
'sharpe_ratio': 1.2,
|
|
'max_drawdown': -0.08,
|
|
'total_trades': 25,
|
|
'sl_pct': 0.02,
|
|
'tp_pct': 0.04,
|
|
'trail_activation': 0.015,
|
|
'trail_stop': 0.015,
|
|
'transaction_cost': 0.00015,
|
|
}
|
|
worker.acceptance_gate = Mock()
|
|
worker.acceptance_gate.evaluate.return_value = {
|
|
'passed': True,
|
|
'reasons': [],
|
|
'checks': {},
|
|
}
|
|
worker.strategy_saver = StrategySaver(output_dir=str(tmp_path))
|
|
worker.strategy_saver.save_strategy = Mock(return_value=tmp_path / 'test.json')
|
|
|
|
result = worker.run_workflow(
|
|
factors=sample_factors,
|
|
factor_data=sample_factors_df,
|
|
close=sample_close,
|
|
strategy_name='TestStrategy',
|
|
)
|
|
|
|
assert result['success'] is True
|
|
assert result['stage'] == 'complete'
|
|
worker.strategy_saver.save_strategy.assert_called_once()
|