kanban-app/backend/app/celery/tasks/example_tasks.py

"""
Example Celery tasks for the Crafting Shop application.
These tasks demonstrate various Celery features and best practices.
"""
import logging
import time
from datetime import datetime

from celery import shared_task

# Get logger for this module
logger = logging.getLogger(__name__)


@shared_task(bind=True, name="tasks.print_hello")
def print_hello(self, name: str = "World") -> str:
    """
    Simple task that prints a greeting.

    Args:
        name: Name to greet (default: "World")

    Returns:
        Greeting message
    """
    message = f"Hello {name} from Celery! Task ID: {self.request.id}"
    print(message)
    logger.info(message)
    return message


@shared_task(
    bind=True,
    name="tasks.divide_numbers",
    autoretry_for=(ZeroDivisionError,),
    retry_backoff=True,
    retry_backoff_max=60,
    retry_jitter=True,
    max_retries=3,
)
def divide_numbers(self, x: float, y: float) -> float:
    """
    Task that demonstrates error handling and retry logic.

    Args:
        x: Numerator
        y: Denominator

    Returns:
        Result of division

    Raises:
        ZeroDivisionError: If y is zero (will trigger retry)
    """
    logger.info(f"Dividing {x} by {y} (attempt {self.request.retries + 1})")

    if y == 0:
        logger.warning("Division by zero detected, retrying...")
        raise ZeroDivisionError("Cannot divide by zero")

    result = x / y
    logger.info(f"Division result: {result}")
    return result


@shared_task(bind=True, name="tasks.send_daily_report", ignore_result=False)
def send_daily_report(self) -> dict:
    """
    Simulates sending a daily report.
    This task would typically send emails, generate reports, etc.

    Returns:
        Dictionary with report details
    """
    logger.info("Starting daily report generation...")

    # Simulate some work
    time.sleep(2)

    report_data = {
        "date": datetime.now().isoformat(),
        "task_id": self.request.id,
        "report_type": "daily",
        "status": "generated",
        "metrics": {
            "total_products": 150,
            "total_orders": 42,
            "total_users": 89,
            "revenue": 12500.75,
        },
    }

    logger.info(f"Daily report generated: {report_data}")
    print(f"📊 Daily Report Generated at {report_data['date']}")

    return report_data


@shared_task(
    bind=True, name="tasks.update_product_statistics", queue="stats", priority=5
)
def update_product_statistics(self, product_id: int = None) -> dict:
    """
    Simulates updating product statistics.
    Demonstrates task routing to a specific queue.

    Args:
        product_id: Optional specific product ID to update.
                   If None, updates all products.

    Returns:
        Dictionary with update results
    """
    logger.info(f"Updating product statistics for product_id={product_id}")

    # Simulate database work
    time.sleep(1)

    if product_id is None:
        # Update all products
        result = {
            "task": "update_all_product_stats",
            "status": "completed",
            "products_updated": 150,
            "timestamp": datetime.now().isoformat(),
        }
    else:
        # Update specific product
        result = {
            "task": "update_single_product_stats",
            "product_id": product_id,
            "status": "completed",
            "timestamp": datetime.now().isoformat(),
            "new_stats": {"views": 125, "purchases": 15, "rating": 4.5},
        }

    logger.info(f"Product statistics updated: {result}")
    return result


@shared_task(
    bind=True,
    name="tasks.long_running_task",
    time_limit=300,  # 5 minutes
    soft_time_limit=240,  # 4 minutes
)
def long_running_task(self, iterations: int = 10) -> dict:
    """
    Simulates a long-running task with progress tracking.

    Args:
        iterations: Number of iterations to simulate

    Returns:
        Dictionary with results
    """
    logger.info(f"Starting long-running task with {iterations} iterations")

    results = []
    for i in range(iterations):
        # Check if task has been revoked
        if self.is_aborted():
            logger.warning("Task was aborted")
            return {"status": "aborted", "completed_iterations": i}

        # Simulate work
        time.sleep(1)

        # Update progress
        progress = (i + 1) / iterations * 100
        self.update_state(
            state="PROGRESS",
            meta={"current": i + 1, "total": iterations, "progress": progress},
        )

        results.append(f"iteration_{i + 1}")
        logger.info(f"Completed iteration {i + 1}/{iterations}")

    final_result = {
        "status": "completed",
        "iterations": iterations,
        "results": results,
        "completed_at": datetime.now().isoformat(),
    }

    logger.info(f"Long-running task completed: {final_result}")
    return final_result