"""
ML-Based Vulnerability Predictor - Learn from Historical Bugs.

[FUTURE_FEATURE] v3.4.0 - Machine learning for bug prediction

Train ML models on historical vulnerability data to:
- Predict which code paths are most likely buggy
- Prioritize security analysis on high-risk code
- Suggest similar past vulnerabilities
- Auto-classify vulnerability severity

Example:
    >>> from code_scalpel.security.ml.ml_vulnerability_predictor import VulnerabilityPredictor
    >>> predictor = VulnerabilityPredictor()
    >>> predictor.train(historical_vulnerabilities)
    >>> risk_score = predictor.predict(code_snippet)
    >>> if risk_score > 0.8:
    ...     print("High risk - prioritize security analysis")
"""

from dataclasses import dataclass
from typing import Any


@dataclass
class VulnerabilityPrediction:
    """Prediction result for code vulnerability."""

    risk_score: float  # 0.0-1.0
    confidence: float  # Model confidence
    predicted_type: str  # SQL injection, XSS, etc.
    similar_past_vulnerabilities: list[str]
    explanation: str


class VulnerabilityPredictor:
    """
    ML-based vulnerability predictor (stub).

    """

    def __init__(self, model_path: str | None = None):
        """
        - Load feature extractors
        - Initialize model architecture
        - Setup explainability tools (SHAP)
        """
        self.model = None

    def train(self, training_data: list[dict[str, Any]]) -> dict[str, float]:
        """
        - Extract features from code + labels
        - Train model with cross-validation
        - Evaluate on held-out test set
        - Save model to disk

        Returns:
            Training metrics (accuracy, precision, recall, F1)
        """
        raise NotImplementedError("Training not yet implemented")

    def predict(self, code: str) -> VulnerabilityPrediction:
        """
        - Extract features from code
        - Run model inference
        - Generate explanation
        - Find similar past vulnerabilities
        """
        raise NotImplementedError("Prediction not yet implemented")

    def explain(self, code: str, prediction: VulnerabilityPrediction) -> str:
        """
        - Use SHAP for feature importance
        - Highlight risky code sections
        - Reference similar past bugs
        - Suggest fixes
        """
        raise NotImplementedError("Explanation not yet implemented")
