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import schedule
import time
import logging
import json
import psutil
import signal
import sys
from pathlib import Path
from datetime import datetime, timedelta
from typing import Dict, List, Optional, Callable, Any
from concurrent.futures import ThreadPoolExecutor, as_completed
import threading
from contextlib import contextmanager
import subprocess
import traceback
# Configure logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s',
handlers=[
logging.FileHandler('/tmp/scheduler.log'),
logging.StreamHandler()
]
)
logger = logging.getLogger(__name__)
class RobustTaskScheduler:
"""Production-ready task scheduler with comprehensive error handling and monitoring"""
def __init__(self):
self.setup_paths()
self.setup_scheduler_config()
self.setup_task_registry()
self.setup_monitoring()
self.setup_signal_handlers()
self.executor = ThreadPoolExecutor(max_workers=3)
self.running = True
self.lock = threading.Lock()
def setup_paths(self):
"""Setup all necessary paths"""
self.base_dir = Path("/tmp")
self.logs_dir = self.base_dir / "logs"
self.logs_dir.mkdir(parents=True, exist_ok=True)
# Log files
self.activity_log_path = Path("/tmp/activity_log.json")
self.scheduler_log_path = self.logs_dir / "scheduler_execution.json"
self.error_log_path = self.logs_dir / "scheduler_errors.json"
self.performance_log_path = self.logs_dir / "scheduler_performance.json"
def setup_scheduler_config(self):
"""Setup scheduler configuration"""
self.config = {
'scraping_interval': 'hourly',
'generation_interval': 'hourly',
'retraining_interval': 'hourly',
'monitoring_interval': 'hourly',
'health_check_interval': 'every(10).minutes',
'cleanup_interval': 'daily',
'max_task_duration': 1800, # 30 minutes
'max_retries': 3,
'retry_delay': 300, # 5 minutes
'resource_limits': {
'max_cpu_percent': 80,
'max_memory_percent': 85,
'max_disk_usage_percent': 90
}
}
def setup_task_registry(self):
"""Setup task registry with metadata"""
self.task_registry = {
'scrape_news': {
'function': self.scrape_news_task,
'description': 'Scrape real news articles from various sources',
'dependencies': [],
'timeout': 900, # 15 minutes
'retry_count': 0,
'last_run': None,
'last_success': None,
'enabled': True
},
'generate_fake_news': {
'function': self.generate_fake_news_task,
'description': 'Generate synthetic fake news articles',
'dependencies': [],
'timeout': 300, # 5 minutes
'retry_count': 0,
'last_run': None,
'last_success': None,
'enabled': True
},
'retrain_model': {
'function': self.retrain_model_task,
'description': 'Retrain ML model with new data',
'dependencies': ['scrape_news', 'generate_fake_news'],
'timeout': 1800, # 30 minutes
'retry_count': 0,
'last_run': None,
'last_success': None,
'enabled': True
},
'monitor_drift': {
'function': self.monitor_drift_task,
'description': 'Monitor data and model drift',
'dependencies': ['retrain_model'],
'timeout': 600, # 10 minutes
'retry_count': 0,
'last_run': None,
'last_success': None,
'enabled': True
},
'system_health_check': {
'function': self.system_health_check_task,
'description': 'Check system health and resources',
'dependencies': [],
'timeout': 60, # 1 minute
'retry_count': 0,
'last_run': None,
'last_success': None,
'enabled': True
},
'cleanup_old_files': {
'function': self.cleanup_old_files_task,
'description': 'Clean up old log files and temporary data',
'dependencies': [],
'timeout': 300, # 5 minutes
'retry_count': 0,
'last_run': None,
'last_success': None,
'enabled': True
}
}
def setup_monitoring(self):
"""Setup monitoring and metrics"""
self.metrics = {
'tasks_executed': 0,
'tasks_succeeded': 0,
'tasks_failed': 0,
'total_execution_time': 0,
'average_execution_time': 0,
'last_health_check': None,
'system_status': 'healthy',
'startup_time': datetime.now().isoformat()
}
def setup_signal_handlers(self):
"""Setup signal handlers for graceful shutdown"""
signal.signal(signal.SIGTERM, self.signal_handler)
signal.signal(signal.SIGINT, self.signal_handler)
def signal_handler(self, signum, frame):
"""Handle shutdown signals gracefully"""
logger.info(f"Received signal {signum}, shutting down gracefully...")
self.running = False
# Wait for running tasks to complete
self.executor.shutdown(wait=True, timeout=60)
# Log shutdown
self.log_event("Scheduler shutdown completed")
sys.exit(0)
def log_event(self, event: str, level: str = "INFO", metadata: Dict = None):
"""Log events with timestamps and metadata"""
log_entry = {
"timestamp": datetime.now().strftime("%Y-%m-%d %I:%M %p"),
"event": event,
"level": level,
"metadata": metadata or {}
}
try:
# Load existing logs
logs = []
if self.activity_log_path.exists():
try:
with open(self.activity_log_path, 'r') as f:
logs = json.load(f)
except:
logs = []
# Add new log
logs.append(log_entry)
# Keep only last 1000 entries
if len(logs) > 1000:
logs = logs[-1000:]
# Save logs
with open(self.activity_log_path, 'w') as f:
json.dump(logs, f, indent=2)
except Exception as e:
logger.error(f"Failed to log event: {e}")
def check_system_resources(self) -> Dict:
"""Check system resource usage"""
try:
cpu_percent = psutil.cpu_percent(interval=1)
memory = psutil.virtual_memory()
disk = psutil.disk_usage('/')
return {
'cpu_percent': cpu_percent,
'memory_percent': memory.percent,
'disk_percent': disk.percent,
'memory_available_gb': memory.available / (1024**3),
'disk_free_gb': disk.free / (1024**3),
'healthy': (
cpu_percent < self.config['resource_limits']['max_cpu_percent'] and
memory.percent < self.config['resource_limits']['max_memory_percent'] and
disk.percent < self.config['resource_limits']['max_disk_usage_percent']
)
}
except Exception as e:
logger.error(f"Failed to check system resources: {e}")
return {'healthy': False, 'error': str(e)}
def can_run_task(self, task_name: str) -> Tuple[bool, str]:
"""Check if a task can be run based on system resources and dependencies"""
# Check if task is enabled
if not self.task_registry[task_name]['enabled']:
return False, f"Task {task_name} is disabled"
# Check system resources
resources = self.check_system_resources()
if not resources['healthy']:
return False, f"System resources insufficient: {resources}"
# Check dependencies
dependencies = self.task_registry[task_name]['dependencies']
for dep in dependencies:
dep_task = self.task_registry.get(dep)
if dep_task is None:
return False, f"Dependency {dep} not found"
# Check if dependency ran recently and successfully
if dep_task['last_success'] is None:
return False, f"Dependency {dep} has never run successfully"
# Check if dependency ran within reasonable time
last_success = datetime.fromisoformat(dep_task['last_success'])
if datetime.now() - last_success > timedelta(hours=2):
return False, f"Dependency {dep} last success too old"
return True, "OK"
@contextmanager
def task_execution_context(self, task_name: str):
"""Context manager for task execution with timing and error handling"""
start_time = time.time()
try:
self.task_registry[task_name]['last_run'] = datetime.now().isoformat()
self.metrics['tasks_executed'] += 1
logger.info(f"Starting task: {task_name}")
yield
# Task succeeded
execution_time = time.time() - start_time
self.task_registry[task_name]['last_success'] = datetime.now().isoformat()
self.task_registry[task_name]['retry_count'] = 0
self.metrics['tasks_succeeded'] += 1
self.metrics['total_execution_time'] += execution_time
self.metrics['average_execution_time'] = (
self.metrics['total_execution_time'] / self.metrics['tasks_executed']
)
logger.info(f"Task {task_name} completed successfully in {execution_time:.2f}s")
except Exception as e:
# Task failed
execution_time = time.time() - start_time
self.task_registry[task_name]['retry_count'] += 1
self.metrics['tasks_failed'] += 1
error_details = {
'task': task_name,
'error': str(e),
'traceback': traceback.format_exc(),
'execution_time': execution_time,
'retry_count': self.task_registry[task_name]['retry_count']
}
self.log_error(error_details)
logger.error(f"Task {task_name} failed after {execution_time:.2f}s: {e}")
raise
def log_error(self, error_details: Dict):
"""Log error details for debugging"""
try:
error_entry = {
'timestamp': datetime.now().isoformat(),
**error_details
}
# Load existing errors
errors = []
if self.error_log_path.exists():
try:
with open(self.error_log_path, 'r') as f:
errors = json.load(f)
except:
errors = []
# Add new error
errors.append(error_entry)
# Keep only last 100 errors
if len(errors) > 100:
errors = errors[-100:]
# Save errors
with open(self.error_log_path, 'w') as f:
json.dump(errors, f, indent=2)
except Exception as e:
logger.error(f"Failed to log error: {e}")
def run_task_with_retry(self, task_name: str):
"""Run a task with retry logic"""
task_info = self.task_registry[task_name]
max_retries = self.config['max_retries']
for attempt in range(max_retries + 1):
try:
# Check if we can run the task
can_run, reason = self.can_run_task(task_name)
if not can_run:
logger.warning(f"Cannot run task {task_name}: {reason}")
return False
# Execute task
with self.task_execution_context(task_name):
task_info['function']()
return True
except Exception as e:
if attempt < max_retries:
wait_time = self.config['retry_delay'] * (2 ** attempt) # Exponential backoff
logger.warning(f"Task {task_name} failed (attempt {attempt + 1}/{max_retries + 1}), retrying in {wait_time}s")
time.sleep(wait_time)
else:
logger.error(f"Task {task_name} failed after {max_retries + 1} attempts")
self.log_event(f"Task {task_name} failed permanently", "ERROR", {"attempts": max_retries + 1})
return False
return False
# Task implementations
def scrape_news_task(self):
"""Scrape news articles task"""
try:
from data.scrape_real_news import scrape_articles
success = scrape_articles()
if not success:
raise Exception("News scraping failed")
self.log_event("News scraping completed successfully")
except Exception as e:
raise Exception(f"News scraping failed: {e}")
def generate_fake_news_task(self):
"""Generate fake news task"""
try:
from data.generate_fake_news import generate_fake_news
success = generate_fake_news(25)
if not success:
raise Exception("Fake news generation failed")
self.log_event("Fake news generation completed successfully")
except Exception as e:
raise Exception(f"Fake news generation failed: {e}")
def retrain_model_task(self):
"""Retrain model task"""
try:
from model.retrain import main as retrain_main
retrain_main()
self.log_event("Model retraining completed successfully")
except Exception as e:
raise Exception(f"Model retraining failed: {e}")
def monitor_drift_task(self):
"""Monitor drift task"""
try:
from monitor.monitor_drift import monitor_drift
drift_score = monitor_drift()
if drift_score is not None:
self.log_event(f"Drift monitoring completed", metadata={"drift_score": drift_score})
else:
raise Exception("Drift monitoring returned None")
except Exception as e:
raise Exception(f"Drift monitoring failed: {e}")
def system_health_check_task(self):
"""System health check task"""
try:
resources = self.check_system_resources()
# Check critical files
critical_files = [
Path("/tmp/model.pkl"),
Path("/tmp/vectorizer.pkl"),
Path("/tmp/data/combined_dataset.csv")
]
missing_files = [f for f in critical_files if not f.exists()]
health_status = {
'resources': resources,
'missing_files': [str(f) for f in missing_files],
'healthy': resources['healthy'] and len(missing_files) == 0
}
self.metrics['last_health_check'] = datetime.now().isoformat()
self.metrics['system_status'] = 'healthy' if health_status['healthy'] else 'unhealthy'
if not health_status['healthy']:
self.log_event("System health check failed", "WARNING", health_status)
logger.info(f"System health check completed: {health_status['healthy']}")
except Exception as e:
raise Exception(f"System health check failed: {e}")
def cleanup_old_files_task(self):
"""Clean up old files task"""
try:
cleanup_count = 0
# Clean up old log files
log_dirs = [Path("/tmp/logs"), Path("/tmp")]
for log_dir in log_dirs:
if log_dir.exists():
for log_file in log_dir.glob("*.log"):
if log_file.stat().st_mtime < time.time() - (7 * 24 * 3600): # 7 days
log_file.unlink()
cleanup_count += 1
# Clean up old backup files
backup_dir = Path("/tmp/backups")
if backup_dir.exists():
for backup_file in backup_dir.glob("backup_*"):
if backup_file.stat().st_mtime < time.time() - (30 * 24 * 3600): # 30 days
if backup_file.is_dir():
import shutil
shutil.rmtree(backup_file)
else:
backup_file.unlink()
cleanup_count += 1
self.log_event(f"Cleanup completed: {cleanup_count} files removed")
except Exception as e:
raise Exception(f"Cleanup failed: {e}")
def run_pipeline_sequence(self):
"""Run the main pipeline sequence"""
logger.info("Starting pipeline sequence...")
# Define task sequence
pipeline_tasks = [
'scrape_news',
'generate_fake_news',
'retrain_model',
'monitor_drift'
]
success_count = 0
for task_name in pipeline_tasks:
if self.run_task_with_retry(task_name):
success_count += 1
else:
logger.error(f"Pipeline halted due to task failure: {task_name}")
break
if success_count == len(pipeline_tasks):
self.log_event("Pipeline sequence completed successfully")
else:
self.log_event(f"Pipeline sequence partially completed: {success_count}/{len(pipeline_tasks)} tasks")
def schedule_tasks(self):
"""Schedule all tasks according to configuration"""
logger.info("Scheduling tasks...")
# Schedule main pipeline
schedule.every().hour.do(self.run_pipeline_sequence)
# Schedule individual monitoring tasks
schedule.every(10).minutes.do(self.run_task_with_retry, 'system_health_check')
schedule.every().day.at("02:00").do(self.run_task_with_retry, 'cleanup_old_files')
logger.info("All tasks scheduled successfully")
def save_performance_metrics(self):
"""Save performance metrics periodically"""
try:
metrics_entry = {
'timestamp': datetime.now().isoformat(),
'metrics': self.metrics.copy()
}
# Load existing metrics
metrics_log = []
if self.performance_log_path.exists():
try:
with open(self.performance_log_path, 'r') as f:
metrics_log = json.load(f)
except:
metrics_log = []
# Add new metrics
metrics_log.append(metrics_entry)
# Keep only last 100 entries
if len(metrics_log) > 100:
metrics_log = metrics_log[-100:]
# Save metrics
with open(self.performance_log_path, 'w') as f:
json.dump(metrics_log, f, indent=2)
except Exception as e:
logger.error(f"Failed to save performance metrics: {e}")
def run(self):
"""Main scheduler loop"""
logger.info("Starting robust task scheduler...")
# Initial system health check
self.run_task_with_retry('system_health_check')
# Schedule all tasks
self.schedule_tasks()
# Run initial pipeline
self.run_pipeline_sequence()
# Main loop
last_metrics_save = time.time()
while self.running:
try:
schedule.run_pending()
# Save metrics every 10 minutes
if time.time() - last_metrics_save > 600:
self.save_performance_metrics()
last_metrics_save = time.time()
time.sleep(30) # Check every 30 seconds
except KeyboardInterrupt:
logger.info("Received keyboard interrupt, shutting down...")
break
except Exception as e:
logger.error(f"Scheduler error: {e}")
time.sleep(60) # Wait a minute before retrying
logger.info("Scheduler shutdown complete")
def main():
"""Main execution function"""
scheduler = RobustTaskScheduler()
scheduler.run()
if __name__ == "__main__":
main() |