diff --git a/src/stabilizer/GlobalRegulatoryComplianceEngine.py b/src/stabilizer/GlobalRegulatoryComplianceEngine.py index 2148d46..d812d62 100644 --- a/src/stabilizer/GlobalRegulatoryComplianceEngine.py +++ b/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())