AI platform insights monitoring and website analysis monitoring services added
This commit is contained in:
ajaysi
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"""
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Website Analysis Task Executor
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Handles execution of website analysis tasks for user and competitor websites.
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"""
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import logging
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import os
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import time
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import asyncio
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from datetime import datetime, timedelta
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from typing import Dict, Any, Optional
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from sqlalchemy.orm import Session
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from functools import partial
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from urllib.parse import urlparse
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from ..core.executor_interface import TaskExecutor, TaskExecutionResult
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from ..core.exception_handler import TaskExecutionError, DatabaseError, SchedulerExceptionHandler
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from models.website_analysis_monitoring_models import WebsiteAnalysisTask, WebsiteAnalysisExecutionLog
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from models.onboarding import CompetitorAnalysis, OnboardingSession
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from utils.logger_utils import get_service_logger
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# Import website analysis services
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from services.component_logic.web_crawler_logic import WebCrawlerLogic
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from services.component_logic.style_detection_logic import StyleDetectionLogic
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from services.website_analysis_service import WebsiteAnalysisService
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logger = get_service_logger("website_analysis_executor")
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class WebsiteAnalysisExecutor(TaskExecutor):
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"""
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Executor for website analysis tasks.
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Handles:
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- Analyzing user's website (updates existing WebsiteAnalysis record)
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- Analyzing competitor websites (stores in CompetitorAnalysis table)
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- Logging results and updating task status
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- Scheduling next execution based on frequency_days
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"""
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def __init__(self):
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self.logger = logger
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self.exception_handler = SchedulerExceptionHandler()
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self.crawler_logic = WebCrawlerLogic()
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self.style_logic = StyleDetectionLogic()
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async def execute_task(
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self,
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task: WebsiteAnalysisTask,
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db: Session
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) -> TaskExecutionResult:
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"""
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Execute a website analysis task.
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This performs complete website analysis using the same logic as
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/api/onboarding/style-detection/complete endpoint.
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Args:
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task: WebsiteAnalysisTask instance
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db: Database session
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Returns:
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TaskExecutionResult
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"""
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start_time = time.time()
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user_id = task.user_id
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website_url = task.website_url
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task_type = task.task_type
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try:
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self.logger.info(
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f"Executing website analysis: task_id={task.id} | "
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f"user_id={user_id} | url={website_url} | type={task_type}"
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)
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# Create execution log
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execution_log = WebsiteAnalysisExecutionLog(
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task_id=task.id,
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execution_date=datetime.utcnow(),
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status='running'
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)
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db.add(execution_log)
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db.flush()
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# Perform website analysis
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result = await self._perform_website_analysis(
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website_url=website_url,
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user_id=user_id,
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task_type=task_type,
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task=task,
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db=db
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)
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# Update execution log
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execution_time_ms = int((time.time() - start_time) * 1000)
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execution_log.status = 'success' if result.success else 'failed'
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execution_log.result_data = result.result_data
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execution_log.error_message = result.error_message
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execution_log.execution_time_ms = execution_time_ms
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# Update task based on result
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task.last_check = datetime.utcnow()
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task.updated_at = datetime.utcnow()
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if result.success:
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task.last_success = datetime.utcnow()
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task.status = 'active'
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task.failure_reason = None
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# Schedule next check based on frequency_days
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task.next_check = self.calculate_next_execution(
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task=task,
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frequency='Custom',
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last_execution=task.last_check,
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custom_days=task.frequency_days
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)
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# Commit all changes to database
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db.commit()
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self.logger.info(
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f"Website analysis completed successfully for task {task.id}. "
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f"Next check scheduled for {task.next_check}"
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)
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return result
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else:
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task.last_failure = datetime.utcnow()
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task.failure_reason = result.error_message
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task.status = 'failed'
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# Do NOT update next_check - wait for manual retry
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# Commit all changes to database
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db.commit()
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self.logger.warning(
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f"Website analysis failed for task {task.id}. "
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f"Error: {result.error_message}. Waiting for manual retry."
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)
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return result
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except Exception as e:
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execution_time_ms = int((time.time() - start_time) * 1000)
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# Set database session for exception handler
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self.exception_handler.db = db
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# Create structured error
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error = TaskExecutionError(
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message=f"Error executing website analysis task {task.id}: {str(e)}",
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user_id=user_id,
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task_id=task.id,
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task_type="website_analysis",
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execution_time_ms=execution_time_ms,
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context={
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"website_url": website_url,
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"task_type": task_type,
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"user_id": user_id
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},
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original_error=e
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)
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# Handle exception with structured logging
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self.exception_handler.handle_exception(error)
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# Update execution log with error
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try:
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execution_log = WebsiteAnalysisExecutionLog(
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task_id=task.id,
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execution_date=datetime.utcnow(),
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status='failed',
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error_message=str(e),
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execution_time_ms=execution_time_ms,
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result_data={
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"error_type": error.error_type.value,
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"severity": error.severity.value,
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"context": error.context
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}
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)
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db.add(execution_log)
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task.last_failure = datetime.utcnow()
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task.failure_reason = str(e)
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task.status = 'failed'
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task.last_check = datetime.utcnow()
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task.updated_at = datetime.utcnow()
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# Do NOT update next_check - wait for manual retry
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db.commit()
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except Exception as commit_error:
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db_error = DatabaseError(
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message=f"Error saving execution log: {str(commit_error)}",
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user_id=user_id,
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task_id=task.id,
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original_error=commit_error
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)
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self.exception_handler.handle_exception(db_error)
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db.rollback()
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return TaskExecutionResult(
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success=False,
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error_message=str(e),
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execution_time_ms=execution_time_ms,
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retryable=True
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)
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async def _perform_website_analysis(
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self,
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website_url: str,
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user_id: str,
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task_type: str,
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task: WebsiteAnalysisTask,
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db: Session
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) -> TaskExecutionResult:
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"""
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Perform website analysis using existing service logic.
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Reuses the same logic as /api/onboarding/style-detection/complete.
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"""
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try:
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# Step 1: Crawl website content
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self.logger.info(f"Crawling website: {website_url}")
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crawl_result = await self.crawler_logic.crawl_website(website_url)
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if not crawl_result.get('success'):
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error_msg = crawl_result.get('error', 'Crawling failed')
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self.logger.error(f"Crawling failed for {website_url}: {error_msg}")
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return TaskExecutionResult(
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success=False,
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error_message=f"Crawling failed: {error_msg}",
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result_data={'crawl_result': crawl_result},
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retryable=True
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)
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# Step 2: Run style analysis and patterns analysis in parallel
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self.logger.info(f"Running style analysis for {website_url}")
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async def run_style_analysis():
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"""Run style analysis in executor"""
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loop = asyncio.get_event_loop()
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return await loop.run_in_executor(
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None,
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partial(self.style_logic.analyze_content_style, crawl_result['content'])
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)
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async def run_patterns_analysis():
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"""Run patterns analysis in executor"""
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loop = asyncio.get_event_loop()
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return await loop.run_in_executor(
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None,
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partial(self.style_logic.analyze_style_patterns, crawl_result['content'])
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)
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# Execute style and patterns analysis in parallel
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style_analysis, patterns_result = await asyncio.gather(
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run_style_analysis(),
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run_patterns_analysis(),
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return_exceptions=True
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)
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# Check for exceptions
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if isinstance(style_analysis, Exception):
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self.logger.error(f"Style analysis exception: {style_analysis}")
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return TaskExecutionResult(
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success=False,
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error_message=f"Style analysis failed: {str(style_analysis)}",
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retryable=True
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)
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if isinstance(patterns_result, Exception):
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self.logger.warning(f"Patterns analysis exception: {patterns_result}")
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patterns_result = None
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# Step 3: Generate style guidelines
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style_guidelines = None
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if style_analysis and style_analysis.get('success'):
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loop = asyncio.get_event_loop()
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guidelines_result = await loop.run_in_executor(
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None,
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partial(self.style_logic.generate_style_guidelines, style_analysis.get('analysis', {}))
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)
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if guidelines_result and guidelines_result.get('success'):
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style_guidelines = guidelines_result.get('guidelines')
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# Prepare analysis data
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analysis_data = {
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'crawl_result': crawl_result,
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'style_analysis': style_analysis.get('analysis') if style_analysis and style_analysis.get('success') else None,
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'style_patterns': patterns_result if patterns_result and not isinstance(patterns_result, Exception) else None,
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'style_guidelines': style_guidelines,
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}
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# Step 4: Store results based on task type
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if task_type == 'user_website':
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# Update existing WebsiteAnalysis record
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await self._update_user_website_analysis(
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user_id=user_id,
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website_url=website_url,
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analysis_data=analysis_data,
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db=db
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)
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elif task_type == 'competitor':
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# Store in CompetitorAnalysis table
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await self._store_competitor_analysis(
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user_id=user_id,
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competitor_url=website_url,
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competitor_id=task.competitor_id,
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analysis_data=analysis_data,
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db=db
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)
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self.logger.info(f"Website analysis completed successfully for {website_url}")
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return TaskExecutionResult(
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success=True,
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result_data=analysis_data,
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retryable=False
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)
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except Exception as e:
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self.logger.error(f"Error performing website analysis: {e}", exc_info=True)
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return TaskExecutionResult(
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success=False,
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error_message=str(e),
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retryable=True
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)
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async def _update_user_website_analysis(
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self,
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user_id: str,
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website_url: str,
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analysis_data: Dict[str, Any],
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db: Session
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):
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"""Update existing WebsiteAnalysis record for user's website."""
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try:
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# Convert Clerk user ID to integer (same as component_logic.py)
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# Use the same conversion logic as the website analysis API
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import hashlib
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user_id_int = int(hashlib.sha256(user_id.encode()).hexdigest()[:15], 16)
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# Use WebsiteAnalysisService to update
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analysis_service = WebsiteAnalysisService(db)
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# Prepare data in format expected by save_analysis
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response_data = {
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'crawl_result': analysis_data.get('crawl_result'),
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'style_analysis': analysis_data.get('style_analysis'),
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'style_patterns': analysis_data.get('style_patterns'),
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'style_guidelines': analysis_data.get('style_guidelines'),
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}
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# Save/update analysis
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analysis_id = analysis_service.save_analysis(
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session_id=user_id_int,
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website_url=website_url,
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analysis_data=response_data
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)
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if analysis_id:
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self.logger.info(f"Updated user website analysis for {website_url} (analysis_id: {analysis_id})")
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else:
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self.logger.warning(f"Failed to update user website analysis for {website_url}")
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except Exception as e:
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self.logger.error(f"Error updating user website analysis: {e}", exc_info=True)
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raise
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async def _store_competitor_analysis(
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self,
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user_id: str,
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competitor_url: str,
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competitor_id: Optional[str],
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analysis_data: Dict[str, Any],
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db: Session
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):
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"""Store competitor analysis in CompetitorAnalysis table."""
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try:
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# Get onboarding session for user
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session = db.query(OnboardingSession).filter(
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OnboardingSession.user_id == user_id
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).first()
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if not session:
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raise ValueError(f"No onboarding session found for user {user_id}")
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# Extract domain from URL
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parsed_url = urlparse(competitor_url)
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competitor_domain = parsed_url.netloc or competitor_id
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# Check if analysis already exists for this competitor
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existing = db.query(CompetitorAnalysis).filter(
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CompetitorAnalysis.session_id == session.id,
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CompetitorAnalysis.competitor_url == competitor_url
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).first()
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if existing:
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# Update existing analysis
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existing.analysis_data = analysis_data
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existing.analysis_date = datetime.utcnow()
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existing.status = 'completed'
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existing.error_message = None
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existing.warning_message = None
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existing.updated_at = datetime.utcnow()
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self.logger.info(f"Updated competitor analysis for {competitor_url}")
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else:
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# Create new analysis
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competitor_analysis = CompetitorAnalysis(
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session_id=session.id,
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competitor_url=competitor_url,
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competitor_domain=competitor_domain,
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analysis_data=analysis_data,
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status='completed',
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analysis_date=datetime.utcnow()
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)
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db.add(competitor_analysis)
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self.logger.info(f"Created new competitor analysis for {competitor_url}")
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db.commit()
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except Exception as e:
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db.rollback()
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self.logger.error(f"Error storing competitor analysis: {e}", exc_info=True)
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raise
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def calculate_next_execution(
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self,
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task: WebsiteAnalysisTask,
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frequency: str,
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last_execution: Optional[datetime] = None,
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custom_days: Optional[int] = None
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) -> datetime:
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"""
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Calculate next execution time based on frequency or custom days.
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Args:
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task: WebsiteAnalysisTask instance
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frequency: Frequency string ('Custom' for website analysis)
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last_execution: Last execution datetime (defaults to task.last_check or now)
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custom_days: Custom number of days (from task.frequency_days)
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Returns:
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Next execution datetime
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"""
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if last_execution is None:
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last_execution = task.last_check if task.last_check else datetime.utcnow()
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# Use custom_days if provided, otherwise use task.frequency_days
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days = custom_days if custom_days is not None else task.frequency_days
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if frequency == 'Custom' and days:
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return last_execution + timedelta(days=days)
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else:
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# Default to task's frequency_days
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self.logger.warning(
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f"Unknown frequency '{frequency}' for website analysis task {task.id}. "
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f"Using frequency_days={task.frequency_days}."
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)
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return last_execution + timedelta(days=task.frequency_days)
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