"""
ML Service Tests

Tests for machine learning analytics endpoints.
Covers pattern detection, anomaly detection, and behavioral analysis.
"""

import pytest
from typing import List, Dict, Any


class TestMLServiceHealth:
    """Tests for ML service health and basic functionality."""
    
    def test_ml_health_check(self, ml_client):
        """Test ML service health check endpoint."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        response = ml_client.get("/health")
        assert response.status_code == 200
        data = response.json()
        assert data["status"] == "healthy"
        assert "ml_available" in data
    
    def test_ml_root_endpoint(self, ml_client):
        """Test ML service root endpoint."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        response = ml_client.get("/")
        assert response.status_code == 200
        data = response.json()
        assert data["name"] == "Tikker ML Service"
        assert "endpoints" in data


class TestPatternDetection:
    """Tests for keystroke pattern detection."""
    
    @staticmethod
    def _create_keystroke_events(count: int = 100, wpm: float = 50) -> List[Dict]:
        """Create mock keystroke events."""
        events = []
        interval = int((60000 / (wpm * 5)))
        
        for i in range(count):
            events.append({
                "timestamp": i * interval,
                "key_code": 65 + (i % 26),
                "event_type": "press"
            })
        
        return events
    
    def test_detect_fast_typing_pattern(self, ml_client):
        """Test detection of fast typing pattern."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        fast_events = self._create_keystroke_events(count=150, wpm=80)
        
        payload = {
            "events": fast_events,
            "user_id": "test_user"
        }
        
        response = ml_client.post("/patterns/detect", json=payload)
        
        if response.status_code == 200:
            data = response.json()
            assert isinstance(data, list)
            
            pattern_names = [p["name"] for p in data]
            assert any("fast" in name for name in pattern_names)
    
    def test_detect_slow_typing_pattern(self, ml_client):
        """Test detection of slow typing pattern."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        slow_events = self._create_keystroke_events(count=50, wpm=20)
        
        payload = {
            "events": slow_events,
            "user_id": "test_user"
        }
        
        response = ml_client.post("/patterns/detect", json=payload)
        
        if response.status_code == 200:
            data = response.json()
            pattern_names = [p["name"] for p in data]
            assert any("slow" in name for name in pattern_names)
    
    def test_pattern_detection_empty_events(self, ml_client):
        """Test pattern detection with empty events."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        payload = {
            "events": [],
            "user_id": "test_user"
        }
        
        response = ml_client.post("/patterns/detect", json=payload)
        assert response.status_code == 400


class TestAnomalyDetection:
    """Tests for keystroke anomaly detection."""
    
    @staticmethod
    def _create_keystroke_events(count: int = 100, wpm: float = 50) -> List[Dict]:
        """Create mock keystroke events."""
        events = []
        interval = int((60000 / (wpm * 5)))
        
        for i in range(count):
            events.append({
                "timestamp": i * interval,
                "key_code": 65 + (i % 26),
                "event_type": "press"
            })
        
        return events
    
    def test_detect_typing_speed_anomaly(self, ml_client):
        """Test detection of typing speed anomaly."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        normal_events = self._create_keystroke_events(count=100, wpm=50)
        
        payload = {
            "events": normal_events,
            "user_id": "test_user_anom"
        }
        
        response = ml_client.post("/anomalies/detect", json=payload)
        
        if response.status_code == 200:
            data = response.json()
            assert isinstance(data, list)
    
    def test_anomaly_detection_empty_events(self, ml_client):
        """Test anomaly detection with empty events."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        payload = {
            "events": [],
            "user_id": "test_user"
        }
        
        response = ml_client.post("/anomalies/detect", json=payload)
        assert response.status_code == 400


class TestBehavioralProfile:
    """Tests for behavioral profile building."""
    
    @staticmethod
    def _create_keystroke_events(count: int = 200) -> List[Dict]:
        """Create mock keystroke events."""
        events = []
        
        for i in range(count):
            events.append({
                "timestamp": i * 100,
                "key_code": 65 + (i % 26),
                "event_type": "press"
            })
        
        return events
    
    def test_build_behavioral_profile(self, ml_client):
        """Test building behavioral profile from events."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        events = self._create_keystroke_events(count=200)
        
        payload = {
            "events": events,
            "user_id": "profile_test_user"
        }
        
        response = ml_client.post("/profile/build", json=payload)
        
        if response.status_code == 200:
            data = response.json()
            
            assert "user_id" in data
            assert "avg_typing_speed" in data
            assert "peak_hours" in data
            assert "common_words" in data
            assert "consistency_score" in data
            assert "patterns" in data
            
            assert data["user_id"] == "profile_test_user"
            assert data["consistency_score"] >= 0
            assert data["consistency_score"] <= 1
    
    def test_profile_empty_events(self, ml_client):
        """Test profile building with empty events."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        payload = {
            "events": [],
            "user_id": "test_user"
        }
        
        response = ml_client.post("/profile/build", json=payload)
        assert response.status_code == 400


class TestAuthenticityCheck:
    """Tests for user authenticity verification."""
    
    @staticmethod
    def _create_keystroke_events(count: int = 100, wpm: float = 50) -> List[Dict]:
        """Create mock keystroke events."""
        events = []
        interval = int((60000 / (wpm * 5)))
        
        for i in range(count):
            events.append({
                "timestamp": i * interval,
                "key_code": 65 + (i % 26),
                "event_type": "press"
            })
        
        return events
    
    def test_authenticity_check_unknown_user(self, ml_client):
        """Test authenticity check for unknown user."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        events = self._create_keystroke_events(count=100)
        
        payload = {
            "events": events,
            "user_id": "unknown_user_123"
        }
        
        response = ml_client.post("/authenticity/check", json=payload)
        
        if response.status_code == 200:
            data = response.json()
            assert "authenticity_score" in data
            assert "verdict" in data
            assert data["verdict"] == "unknown"
    
    def test_authenticity_check_established_user(self, ml_client):
        """Test authenticity check for user with established profile."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        user_id = "established_user_test"
        events = self._create_keystroke_events(count=100, wpm=50)
        
        build_payload = {
            "events": events,
            "user_id": user_id
        }
        
        build_response = ml_client.post("/profile/build", json=build_payload)
        
        if build_response.status_code == 200:
            check_payload = {
                "events": events,
                "user_id": user_id
            }
            
            check_response = ml_client.post("/authenticity/check", json=check_payload)
            
            if check_response.status_code == 200:
                data = check_response.json()
                assert "authenticity_score" in data
                assert "verdict" in data


class TestTemporalAnalysis:
    """Tests for temporal pattern analysis."""
    
    def test_temporal_analysis_default_range(self, ml_client):
        """Test temporal analysis with default date range."""
        if not ml_client:
            pytest.skip("ML client not available")

        payload = {"date_range_days": 7}

        response = ml_client.post("/temporal/analyze", json=payload)

        if response.status_code == 200:
            data = response.json()
            assert "trend" in data
            assert "date_range_days" in data or "error" in data
            if "date_range_days" in data:
                assert data["date_range_days"] == 7
    
    def test_temporal_analysis_custom_range(self, ml_client):
        """Test temporal analysis with custom date range."""
        if not ml_client:
            pytest.skip("ML client not available")

        payload = {"date_range_days": 30}

        response = ml_client.post("/temporal/analyze", json=payload)

        if response.status_code == 200:
            data = response.json()
            assert "date_range_days" in data or "error" in data
            if "date_range_days" in data:
                assert data["date_range_days"] == 30


class TestModelTraining:
    """Tests for ML model training."""
    
    def test_train_model_default(self, ml_client):
        """Test training ML model with default parameters."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        response = ml_client.post("/model/train")
        
        if response.status_code == 200:
            data = response.json()
            assert data["status"] == "trained"
            assert "samples" in data
            assert "features" in data
            assert "accuracy" in data
    
    def test_train_model_custom_size(self, ml_client):
        """Test training ML model with custom sample size."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        response = ml_client.post("/model/train?sample_size=500")
        
        if response.status_code == 200:
            data = response.json()
            assert data["samples"] == 500


class TestBehaviorPrediction:
    """Tests for behavior prediction."""
    
    @staticmethod
    def _create_keystroke_events(count: int = 100) -> List[Dict]:
        """Create mock keystroke events."""
        events = []
        
        for i in range(count):
            events.append({
                "timestamp": i * 100,
                "key_code": 65 + (i % 26),
                "event_type": "press"
            })
        
        return events
    
    def test_predict_behavior_untrained_model(self, ml_client):
        """Test behavior prediction with untrained model."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        events = self._create_keystroke_events(count=100)
        
        payload = {
            "events": events,
            "user_id": "test_user"
        }
        
        response = ml_client.post("/behavior/predict", json=payload)
        
        if response.status_code == 200:
            data = response.json()
            assert "behavior_category" in data or "status" in data
    
    def test_predict_behavior_after_training(self, ml_client):
        """Test behavior prediction after model training."""
        if not ml_client:
            pytest.skip("ML client not available")
        
        train_response = ml_client.post("/model/train?sample_size=100")
        
        if train_response.status_code == 200:
            events = self._create_keystroke_events(count=100)
            
            payload = {
                "events": events,
                "user_id": "test_user"
            }
            
            predict_response = ml_client.post("/behavior/predict", json=payload)
            
            if predict_response.status_code == 200:
                data = predict_response.json()
                assert "behavior_category" in data
                assert "confidence" in data


@pytest.fixture
def ml_client():
    """Create ML service test client."""
    from fastapi.testclient import TestClient
    try:
        from ml_service import app
        return TestClient(app)
    except:
        return None