trading-platform-ml-engine-v2/tests/test_api.py

"""
Test ML Engine API endpoints
"""

import pytest
from fastapi.testclient import TestClient
from datetime import datetime

from src.api.main import app


@pytest.fixture
def client():
    """Create test client"""
    return TestClient(app)


def test_health_check(client):
    """Test health check endpoint"""
    response = client.get("/health")
    assert response.status_code == 200

    data = response.json()
    assert data["status"] == "healthy"
    assert "version" in data
    assert "timestamp" in data
    assert isinstance(data["models_loaded"], bool)


def test_list_models(client):
    """Test list models endpoint"""
    response = client.get("/models")
    assert response.status_code == 200
    assert isinstance(response.json(), list)


def test_list_symbols(client):
    """Test list symbols endpoint"""
    response = client.get("/symbols")
    assert response.status_code == 200

    symbols = response.json()
    assert isinstance(symbols, list)
    assert "XAUUSD" in symbols
    assert "EURUSD" in symbols


def test_predict_range(client):
    """Test range prediction endpoint"""
    request_data = {
        "symbol": "XAUUSD",
        "timeframe": "15m",
        "horizon": "15m"
    }

    response = client.post("/predict/range", json=request_data)

    # May return 503 if models not loaded, which is acceptable
    assert response.status_code in [200, 503]

    if response.status_code == 200:
        data = response.json()
        assert isinstance(data, list)
        assert len(data) > 0


def test_predict_tpsl(client):
    """Test TP/SL prediction endpoint"""
    request_data = {
        "symbol": "XAUUSD",
        "timeframe": "15m",
        "horizon": "15m"
    }

    response = client.post("/predict/tpsl?rr_config=rr_2_1", json=request_data)

    # May return 503 if models not loaded
    assert response.status_code in [200, 503]

    if response.status_code == 200:
        data = response.json()
        assert "prob_tp_first" in data
        assert "rr_config" in data
        assert "confidence" in data


def test_generate_signal(client):
    """Test signal generation endpoint"""
    request_data = {
        "symbol": "XAUUSD",
        "timeframe": "15m",
        "horizon": "15m"
    }

    response = client.post("/generate/signal?rr_config=rr_2_1", json=request_data)

    # May return 503 if models not loaded
    assert response.status_code in [200, 503]

    if response.status_code == 200:
        data = response.json()
        assert "signal_id" in data
        assert "symbol" in data
        assert "direction" in data
        assert "entry_price" in data
        assert "stop_loss" in data
        assert "take_profit" in data


def test_amd_detection(client):
    """Test AMD phase detection endpoint"""
    response = client.post("/api/amd/XAUUSD?timeframe=15m&lookback_periods=100")

    # May return 503 if AMD detector not loaded
    assert response.status_code in [200, 503]

    if response.status_code == 200:
        data = response.json()
        assert "phase" in data
        assert "confidence" in data
        assert "strength" in data
        assert "characteristics" in data
        assert "signals" in data
        assert "trading_bias" in data


def test_backtest(client):
    """Test backtesting endpoint"""
    request_data = {
        "symbol": "XAUUSD",
        "start_date": "2024-01-01T00:00:00",
        "end_date": "2024-02-01T00:00:00",
        "initial_capital": 10000.0,
        "risk_per_trade": 0.02,
        "rr_config": "rr_2_1",
        "filter_by_amd": True,
        "min_confidence": 0.55
    }

    response = client.post("/api/backtest", json=request_data)

    # May return 503 if backtester not loaded
    assert response.status_code in [200, 503]

    if response.status_code == 200:
        data = response.json()
        assert "total_trades" in data
        assert "winrate" in data
        assert "net_profit" in data
        assert "profit_factor" in data
        assert "max_drawdown" in data


def test_train_models(client):
    """Test model training endpoint"""
    request_data = {
        "symbol": "XAUUSD",
        "start_date": "2023-01-01T00:00:00",
        "end_date": "2024-01-01T00:00:00",
        "models_to_train": ["range_predictor", "tpsl_classifier"],
        "use_walk_forward": True,
        "n_splits": 5
    }

    response = client.post("/api/train/full", json=request_data)

    # May return 503 if pipeline not loaded
    assert response.status_code in [200, 503]

    if response.status_code == 200:
        data = response.json()
        assert "status" in data
        assert "models_trained" in data
        assert "metrics" in data
        assert "model_paths" in data


def test_websocket_connection(client):
    """Test WebSocket connection"""
    with client.websocket_connect("/ws/signals") as websocket:
        # Send a test message
        websocket.send_text("test")

        # Receive response
        data = websocket.receive_json()
        assert "type" in data
        assert "data" in data


if __name__ == "__main__":
    pytest.main([__file__, "-v"])