Update GlobalRegulatoryComplianceEngine.py

src/stabilizer/GlobalRegulatoryComplianceEngine.py

@@ -4,165 +4,162 @@
 import uuid
 import logging
 import asyncio
-import json
 from typing import Dict, List, Any, Optional
-from dataclasses import dataclass, field
-from datetime import datetime, timedelta
 
-# Advanced Imports
-import pandas as pd
+# Advanced Blockchain and Cryptographic Libraries
+from web3 import Web3
+from eth_account import Account
+from cryptography.hazmat.primitives import serialization
+
+# Machine Learning and Data Processing
 import numpy as np
+import pandas as pd
 import tensorflow as tf
-import sqlalchemy as sa
-from sqlalchemy.ext.declarative import declarative_base
-from sqlalchemy.orm import sessionmaker, Session
-from sqlalchemy.dialects.postgresql import JSONB
-
-# Machine Learning
 from sklearn.ensemble import RandomForestClassifier
-from sklearn.preprocessing import StandardScaler
-from tensorflow.keras.models import Sequential
-from tensorflow.keras.layers import Dense, Dropout
 
-# Blockchain and Cryptography
-from web3 import Web3
-import jwt
-from cryptography.fernet import Fernet
-
-# Compliance Frameworks
+# Compliance and Regulatory Frameworks
 import pandera as pa
-from pydantic import BaseModel, validator, Field
-
-# Logging Configuration
-logging.basicConfig(
-    level=logging.INFO,
-    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
-    handlers=[
-        logging.FileHandler('regulatory_compliance_engine.log'),
-        logging.StreamHandler()
-    ]
-)
-logger = logging.getLogger(__name__)
+from pydantic import BaseModel, Field, validator
 
-# Database Configuration
-Base = declarative_base()
-DATABASE_URL = os.getenv('COMPLIANCE_DATABASE_URL', 'postgresql://user:password@localhost/compliance_engine')
-engine = sa.create_engine(DATABASE_URL, pool_pre_ping=True)
-SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
+# Distributed Systems Components
+from multiprocessing import Process, Queue
+from concurrent.futures import ThreadPoolExecutor
 
-@dataclass
-class ComplianceReport:
-    report_id: str = field(default_factory=lambda: str(uuid.uuid4()))
-    timestamp: datetime = field(default_factory=datetime.utcnow)
-    compliance_score: float = 0.0
-    risk_level: str = 'UNASSESSED'
-    regulatory_coverage: List[str] = field(default_factory=list)
-    detailed_assessment: Dict[str, Any] = field(default_factory=dict)
-
-class ComplianceLogModel(Base):
-    __tablename__ = 'compliance_logs'
-
-    id = sa.Column(sa.Integer, primary_key=True, index=True)
-    report_id = sa.Column(sa.String, unique=True, index=True)
-    timestamp = sa.Column(sa.DateTime, default=datetime.utcnow)
-    compliance_data = sa.Column(JSONB)
-    risk_level = sa.Column(sa.String)
-
-class TransactionDataModel(BaseModel):
-    """Pydantic model for transaction data validation"""
-    transaction_id: str = Field(..., description="Unique transaction identifier")
-    amount: float = Field(..., gt=0, description="Transaction amount")
-    currency: str = Field(..., description="Transaction currency")
-    timestamp: datetime = Field(default_factory=datetime.utcnow)
-
-    @validator('currency')
-    def validate_currency(cls, v):
-        valid_currencies = ['USD', 'EUR', 'GBP', 'JPY']
-        if v not in valid_currencies:
-            raise ValueError(f"Invalid currency. Must be one of {valid_currencies}")
-        return v
-
-class RegulatoryComplianceSchema(BaseModel):
-    """Pydantic model for compliance configuration"""
-    organization_id: str = Field(..., description="Unique organization identifier")
-    compliance_level: int = Field(
-        default=3, 
-        ge=1, 
-        le=5, 
-        description="Compliance level between 1-5"
-    )
-
-class GlobalRegulatoryComplianceEngine:
+class PistellarRegulatoryComplianceEngine:
     def __init__(
         self, 
-        organization_id: Optional[str] = None,
-        compliance_level: int = 3
+        organization_id: str,
+        blockchain_provider: str = "https://mainnet.infura.io/v3/PROJECT_ID"
     ):
-        # Validate input configuration
-        validated_config = RegulatoryComplianceSchema(
-            organization_id=organization_id or str(uuid.uuid4()),
-            compliance_level=compliance_level
-        )
-
-        # Set core attributes
-        self.organization_id = validated_config.organization_id
-        self.compliance_level = validated_config.compliance_level
+        # Core Configuration
+        self.organization_id = organization_id
+        self.blockchain_provider = blockchain_provider
 
-        # Compliance Modules Configuration
-        self.compliance_modules = {
-            'international_financial_reporting': True,
-            'cross_border_transaction_monitoring': True,
-            'adaptive_regulatory_response_system': True,
-            'AI_compliance_assessment': True,
-            'real_time_regulatory_updates': True,
-            'blockchain_audit_trail': True
-        }
+        # Advanced Security Initialization
+        self._initialize_security_protocols()
 
-        # Initialize Security and ML Components
-        self._initialize_security_components()
-        self._initialize_ml_models()
+        # Machine Learning Models
+        self._initialize_ml_compliance_models()
 
-        # Logging
-        self.logger = logger
+        # Distributed Processing Setup
+        self.processing_queue = Queue()
+        self.thread_executor = ThreadPoolExecutor(max_workers=4)
 
-    def _initialize_security_components(self):
-        """Initialize Cryptographic and Security Components"""
+    def _initialize_security_protocols(self):
+        """
+        Advanced Multi-Layer Security Initialization
+        - Blockchain Account Generation
+        - Cryptographic Key Management
+        - Secure Communication Channels
+        """
         try:
-            # Encryption Key Generation
-            self.encryption_key = Fernet.generate_key()
-            self.cipher_suite = Fernet(self.encryption_key)
+            # Generate Ethereum Account
+            self.eth_account = Account.create()
 
-            # Blockchain Configuration
-            self.w3 = Web3(Web3.HTTPProvider(
-                os.getenv('ETHEREUM_NODE_URL', 'https://mainnet.infura.io/v3/YOUR-PROJECT-ID')
-            ))
-        except Exception as e:
-            self.logger.error(f"Security Initialization Failed: {e}")
+            # Blockchain Web3 Connection
+            self.w3 = Web3(Web3.HTTPProvider(self.blockchain_provider))
+
+            # Advanced Cryptographic Key Generation
+            self.private_key = self.eth_account.privateKey
+            self.public_key = self.eth_account.address
+
+        except Exception as security_error:
+            logging.error(f"Security Protocol Initialization Failed: {security_error}")
             raise
 
-    def _initialize_ml_models(self):
-        """Advanced Machine Learning Model Initialization"""
+    def _initialize_ml_compliance_models(self):
+        """
+        Advanced Machine Learning Compliance Models
+        - Risk Assessment Neural Network
+        - Regulatory Compliance Classifier
+        """
+        # Random Forest Compliance Classifier
+        self.compliance_classifier = RandomForestClassifier(
+            n_estimators=100,
+            max_depth=10,
+            random_state=42
+        )
+
+        # TensorFlow Risk Assessment Model
+        self.risk_assessment_model = tf.keras.Sequential([
+            tf.keras.layers.Dense(64, activation='relu', input_shape=(10,)),
+            tf.keras.layers.Dropout(0.3),
+            tf.keras.layers.Dense(32, activation='relu'),
+            tf.keras.layers.Dense(1, activation='sigmoid')
+        ])
+
+        self.risk_assessment_model.compile(
+            optimizer='adam',
+            loss='binary_crossentropy',
+            metrics=['accuracy']
+        )
+
+    async def perform_comprehensive_compliance_assessment(
+        self, 
+        transaction_data: Dict[str, Any]
+    ) -> Dict[str, Any]:
+        """
+        Comprehensive Regulatory Compliance Assessment
+        
+        Args:
+            transaction_data (Dict): Transaction details for compliance check
+        
+        Returns:
+            Dict: Comprehensive compliance assessment results
+        """
         try:
-            # Scikit-learn Risk Classifier
-            self.risk_classifier = RandomForestClassifier(
-                n_estimators=100, 
-                random_state=42,
-                max_depth=10
-            )
-            self.scaler = StandardScaler()
+            # Distributed Processing of Compliance Check
+            compliance_result = await self._distributed_compliance_processing(transaction_data)
 
-            # TensorFlow Neural Network for Complex Risk Assessment
-            self.neural_risk_model = Sequential([
-                Dense(64, activation='relu', input_shape=(10,)),
-                Dropout(0.3),
-                Dense(32, activation='relu'),
-                Dense(1, activation='sigmoid')
-            ])
-            self.neural_risk_model.compile(
-                optimizer='adam', 
-                loss='binary_crossentropy', 
-                metrics=['accuracy']
-            )
-        except Exception as e:
-            self.logger.error(f"ML Model Initialization Failed: {e}")
+            return {
+                "compliance_score": compliance_result.get("score", 0),
+                "risk_level": compliance_result.get("risk_level", "UNDEFINED"),
+                "regulatory_flags": compliance_result.get("flags", [])
+            }
+
+        except Exception as assessment_error:
+            logging.error(f"Compliance Assessment Error: {assessment_error}")
             raise
+
+    def _distributed_compliance_processing(self, transaction_data):
+        """
+        Distributed Multi-Process Compliance Processing
+        """
+        def process_compliance_module(data, result_queue):
+            # Simulate complex compliance processing
+            compliance_score = np.random.uniform(0, 1)
+            result_queue.put({
+                "score": compliance_score,
+                "risk_level": "LOW" if compliance_score > 0.7 else "HIGH",
+                "flags": []
+            })
+
+        result_queue = Queue()
+        compliance_process = Process(
+            target=process_compliance_module, 
+            args=(transaction_data, result_queue)
+        )
+        compliance_process.start()
+        compliance_process.join()
+
+        return result_queue.get()
+
+# Example Usage
+async def main():
+    compliance_engine = PistellarRegulatoryComplianceEngine(
+        organization_id="example_org_123"
+    )
+
+    transaction_data = {
+        "amount": 10000,
+        "currency": "USD",
+        "timestamp": datetime.now()
+    }
+
+    result = await compliance_engine.perform_comprehensive_compliance_assessment(
+        transaction_data
+    )
+    print(result)
+
+if __name__ == "__main__":
+    asyncio.run(main())