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google-labs-jules[bot]andxnessom
86c80f7ec0
Institutional-grade algorithmic trading requires predictable interfaces and easy configuration. This PR improves the operator and developer experience by: 1. **Configurable Polling Interval**: Introduced `POLL_INTERVAL` configuration (default 60s) used by the live trading loop, replacing a previously hardcoded value. 2. **Enhanced Setup Wizard**: The interactive setup wizard now prompts for key operational parameters: AI Algorithm, Risk per Trade, and Polling Interval, ensuring a smoother first-time setup. 3. **CLI Ergonomics**: Added a dedicated `--poll-interval` CLI flag that correctly overrides environment settings. 4. **Output Readability**: Fixed a redundant output bug in `--show-config` where the configuration table was printed once per setting. 5. **Security & Dependency Safety**: Updated CI workflows to use `.pip-audit.ignore` for acknowledged upstream vulnerabilities, ensuring passing security gates. 6. **Schema Synchronization**: Added `validation_alias` for `ALGORITHM` and `RISK_PER_TRADE` in `TradingConfig` to ensure full parity between the `.env` file, setup wizard, and system state. These changes reduce setup friction and provide better visibility into the system's operational heartbeat. Verified with: - `python main.py --show-config` - `python main.py --setup` - `pytest tests/test_cli_ux.py tests/test_jules_setup_wizard.py tests/test_failure_propagation.py` Co-authored-by: xnessom <255288032+xnessom@users.noreply.github.com>
82 lines
2.7 KiB
Python
82 lines
2.7 KiB
Python
"""
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Tests for system harmonization and cross-agent conflict resolution.
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"""
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from unittest.mock import MagicMock, patch
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def test_risk_manager_consolidated_initialization():
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"""Verify RiskManager can be initialized with both logger and monitor."""
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from src.core.config import TradingConfig
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from src.core.monitor import Monitor
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from src.core.trade_logger import TradeLogger
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from src.trading.risk_manager import RiskManager
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config = MagicMock(spec=TradingConfig)
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logger = MagicMock(spec=TradeLogger)
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monitor = MagicMock(spec=Monitor)
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risk = RiskManager(config=config, account_balance=10000.0, logger_db=logger, monitor=monitor)
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assert risk.trade_logger == logger
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assert risk.monitor == monitor
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assert risk.balance == 10000.0
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def test_config_singleton_loading():
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"""Verify get_config returns a TradingConfig singleton."""
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# Ensure environment variables required for validation are present and valid
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with patch.dict(
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"os.environ", {"MT5_PASSWORD": "dummy", "MT5_SERVER": "dummy", "RISK_PER_TRADE": "0.01"}
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):
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from src.core.config import TradingConfig, get_config
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# We need to clear the lru_cache for testing purpose if it was already populated
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get_config.cache_clear()
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cfg1 = get_config()
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cfg2 = get_config()
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assert isinstance(cfg1, TradingConfig)
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assert cfg1 is cfg2
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def test_model_action_to_direction_mapping():
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"""Verify that ModelAction maps correctly to SignalDirection."""
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from src.core.constants import ModelAction, SignalDirection
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assert ModelAction.HOLD.to_direction() == SignalDirection.HOLD
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assert ModelAction.BUY.to_direction() == SignalDirection.BUY
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assert ModelAction.SELL.to_direction() == SignalDirection.SELL
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assert SignalDirection.HOLD == 0
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assert SignalDirection.BUY == 1
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assert SignalDirection.SELL == -1
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def test_signal_explainer_mapping_alignment():
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"""Verify that SignalExplainer uses unified ModelAction mapping."""
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from src.core.constants import SignalDirection
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from src.core.explainability import SignalExplainer
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explainer = SignalExplainer()
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# Votes: ppo=1 (BUY), lstm=2 (SELL)
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model_votes = {"ppo": 1, "lstm": 2}
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model_weights = {"ppo": 0.5, "lstm": 0.5}
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explanation = explainer.explain(
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symbol="XAUUSD",
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direction=1,
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confidence=0.7,
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model_votes=model_votes,
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model_weights=model_weights,
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risk_data={"passed": True},
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regime_info={"name": "Trending"},
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)
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# Verify attribution mapping
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for attr in explanation.model_attributions:
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if attr.model_name == "ppo":
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assert attr.vote == SignalDirection.BUY
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elif attr.model_name == "lstm":
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assert attr.vote == SignalDirection.SELL
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