Route IIoT Alarm Events to Lakehouse Partitions with Redpanda and Apache Flink

"""
Production implementation for routing IIoT alarm events to Lakehouse partitions.
Provides secure, scalable operations using Redpanda and Apache Flink.
"""
from typing import List, Dict, Any, Optional
import os
import logging
import time
import json
import requests
from concurrent.futures import ThreadPoolExecutor

# Configure logging with INFO level
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """
    Configuration class to manage environment settings.
    """
    redpanda_url: str = os.getenv('REDPANDA_URL', 'http://localhost:9092')
    flink_url: str = os.getenv('FLINK_URL', 'http://localhost:8081')
    lakehouse_url: str = os.getenv('LAKEHOUSE_URL', 'http://localhost:5432')

async def validate_input(data: Dict[str, Any]) -> bool:
    """Validate input data structure for IIoT alarms.
    
    Args:
        data: Input data dictionary to validate
    Returns:
        True if the data structure is valid
    Raises:
        ValueError: If validation fails
    """
    if 'alarm_id' not in data:
        raise ValueError('Missing alarm_id in input data')
    if 'timestamp' not in data:
        raise ValueError('Missing timestamp in input data')
    return True

async def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input fields to prevent security issues.
    
    Args:
        data: Raw input data dictionary
    Returns:
        Sanitized data dictionary
    """
    return {k: str(v).strip() for k, v in data.items()}

async def normalize_data(data: Dict[str, Any]) -> Dict[str, Any]:
    """Normalize data for processing.
    
    Args:
        data: Input data dictionary
    Returns:
        Normalized data dictionary
    """
    data['timestamp'] = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(data['timestamp']))
    return data

async def transform_records(records: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Transform raw records into a format suitable for Redpanda.
    
    Args:
        records: List of raw input records
    Returns:
        List of transformed records
    """
    return [await normalize_data(record) for record in records]

async def fetch_data(source_url: str) -> List[Dict[str, Any]]:
    """Fetch data from the specified source URL.
    
    Args:
        source_url: URL to fetch data from
    Returns:
        List of fetched records
    Raises:
        RuntimeError: If data fetch fails
    """
    response = requests.get(source_url)
    if response.status_code != 200:
        raise RuntimeError('Failed to fetch data')
    return response.json()

async def save_to_db(data: List[Dict[str, Any]]) -> None:
    """Save processed data to the Lakehouse database.
    
    Args:
        data: List of processed records to save
    Raises:
        RuntimeError: If data saving fails
    """
    for record in data:
        response = requests.post(Config.lakehouse_url, json=record)
        if response.status_code != 200:
            logger.error('Failed to save record: %s', record)
            raise RuntimeError('Data saving error')

async def call_api(endpoint: str, data: Dict[str, Any]) -> None:
    """Call external API with the provided data.
    
    Args:
        endpoint: API endpoint to call
        data: Data to send in the API request
    Raises:
        RuntimeError: If API call fails
    """
    response = requests.post(endpoint, json=data)
    if response.status_code != 200:
        raise RuntimeError('API call failed')

async def process_batch(records: List[Dict[str, Any]]) -> None:
    """Process a batch of records: validate, transform, and save.
    
    Args:
        records: List of records to process
    Raises:
        ValueError: If validation fails
    """
    for record in records:
        await validate_input(record)  # Validate each record
        sanitized = await sanitize_fields(record)
        await save_to_db([sanitized])  # Save validated and sanitized data

class IIoTEventProcessor:
    """Main orchestrator for IIoT event processing.
    """
    def __init__(self, source_url: str):
        self.source_url = source_url

    async def run(self) -> None:
        """Run the main process for fetching and processing IIoT events.
        """
        try:
            raw_data = await fetch_data(self.source_url)  # Fetch raw data
            await process_batch(raw_data)  # Process the fetched data
        except Exception as e:
            logger.error('Error occurred during processing: %s', e)

if __name__ == '__main__':
    # Example usage of the IIoTEventProcessor
    processor = IIoTEventProcessor(source_url='http://example.com/iiot/events')
    processor.run()  # Start processing