@Marvin I am aware that prefect task are designed to be standalone functions, not methods of a class. So if i call task which is one of the method in my class it throws error like missing a required argument: 'self'. But my use case is where I cannot make method of a class as standalone function since it takes many inputs from different methodws of a class as well attributes. So instead of using decorator I call task inside for loop like one below to achieve Concurrent Task runner. I use submit method in for loop to performs concurrent operation. class Elevator: def __init__(self): pass ) def stop_at_floor(self, floor): print(f"elevator moving to floor {floor}") time.sleep(floor) print(f"elevator stops on floor {floor}") def task_run( self, ): for floor, fname in zip(range(10, 0, -1), [f"t_{i+1}" for i in range(10)]): task_run = task(self.stop_at_floor, task_run_name=fname) task_run.submit(floor) Sometimes this halted in Pending state of the Task, so what should i try to achieve this ?

It appears that there are some quirks in accessing the documentation at the moment, but I do have some initial insight that might prove useful. To manage tasks within a class, you can use Prefect's

task

decorator alongside the

@staticmethod

or

@classmethod

decorators, which will bypass the need for an instance of the class (and thus, the 'self' argument). Then, you'll be able to call these static/class methods from your normal instance methods. Here's a restructured version of your class:

python
from prefect import task, Flow
import time

class Elevator:
    def __init__(self):
        pass

    @staticmethod
    @task
    def stop_at_floor(floor):
        print(f"elevator moving to floor {floor}")
        time.sleep(floor)
        print(f"elevator stops on floor {floor}")

    def task_run(self):
        with Flow("elevator-flow") as flow:
            for floor, fname in zip(range(10, 0, -1), [f"t_{i+1}" for i in range(10)]):
                task_run = Elevator.stop_at_floor(floor)
        # The flow is executed after it is fully defined
        flow.run()

elevator = Elevator()
elevator.task_run()

In this code snippet: 1. The

stop_at_floor

method is decorated with both

@staticmethod

and

@task

, making it a Prefect task that doesn't rely on an instance (

self

). 2. The

task_run

method defines a Prefect flow, within which it maps out the task executions. 3. Finally, the flow is run after it is defined completely. This should solve the issue of the tasks ending up in the "Pending" state due to incorrect instantiation. If you still run into issues, it might be worth investigating the specifics in the logs or checking if any dependencies/blockers are preventing the tasks from running. You might also want to ensure that the Prefect Flow is being scheduled or executed correctly in your environment. For further troubleshooting, please refer to Prefect's official documentation or their GitHub issues page. If I run into any more helpful information, I'll update you accordingly.

@Marvin Based on your code above how can I able to run my task concurrently since the core above runs sequentially which I am not interested.

To run tasks concurrently within your class-based approach, you can leverage the

submit

method for concurrent execution as shown in the given Prefect code example. Below is an adaptation of your class using this approach:

python
from prefect import task, Flow
import time

class Elevator:
    def __init__(self):
        pass

    @staticmethod
    @task
    def stop_at_floor(floor):
        print(f"elevator moving to floor {floor}")
        time.sleep(floor)
        print(f"elevator stops on floor {floor}")

    def task_run(self):
        with Flow("elevator-flow") as flow:
            future_tasks = []
            for floor, fname in zip(range(10, 0, -1), [f"t_{i+1}" for i in range(10)]):
                task_run = Elevator.stop_at_floor.submit(floor)
                future_tasks.append(task_run)
                
            # Optionally, you can wait for the tasks to complete if needed
            # for future_task in future_tasks:
            #     future_task.wait()

        # The flow is executed after it is fully defined
        flow.run()

elevator = Elevator()
elevator.task_run()

In this code snippet: - The

stop_at_floor

method is still defined as a

@staticmethod

and decorated with

@task

. - Inside the

task_run

method, the tasks are submitted using

Elevator.stop_at_floor.submit(floor)

within a loop, allowing concurrent execution. - Each task's future is stored in the

future_tasks

list. Optionally, you can wait for each task's completion using

future_task.wait()

if needed. This ensures that the tasks are run concurrently rather than sequentially. For further details, you can refer to the Prefect's code example on concurrent task submission.

@Marvin Based on your above code, I want to run the flow separately and not inside the class. I want to have flow as a function which calls the task runs inside as in of the class methods. Could you refactor the code based on my interest ?

Certainly. Here’s a refactored version where the flow is defined as a separate function and calls the task runs from within the class method. 1. Define the flow function outside the class. 2. Ensure the class method responsible for running tasks can be invoked by the flow. Here's the refactored code:

python
from prefect import task, Flow
import time

class Elevator:
    def __init__(self):
        pass

    @staticmethod
    @task
    def stop_at_floor(floor):
        print(f"elevator moving to floor {floor}")
        time.sleep(floor)
        print(f"elevator stops on floor {floor}")

    def prepare_tasks(self):
        future_tasks = []
        for floor, fname in zip(range(10, 0, -1), [f"t_{i+1}" for i in range(10)]):
            task_run = Elevator.stop_at_floor.submit(floor)
            future_tasks.append(task_run)
        return future_tasks

def elevator_flow():
    elevator = Elevator()
    future_tasks = elevator.prepare_tasks()
    # Optionally, wait for the tasks to complete if needed
    # for future_task in future_tasks:
    #     future_task.wait()

if __name__ == "__main__":
    # Define and run the flow
    with Flow("elevator-flow") as flow:
        elevator_flow()
    
    flow.run()

Explanation: 1. Elevator Class: - Still defines

stop_at_floor

as a static method decorated with

@task

. - Contains a

prepare_tasks

method that submits the tasks concurrently and returns their futures. 2. elevator_flow Function: - Instantiates the

Elevator

class. - Calls the

prepare_tasks

method to submit tasks and run them concurrently. 3. Flow Definition and Execution: - The flow is defined outside the class and within a

__main__

block to allow it to run separately. - The

elevator_flow

function is called within the context of the flow. This separation ensures that the flow execution logic is decoupled from the class, allowing you to maintain cleaner and more modular code.

@Marvin Based on the above code, could you refactor such that I can some attribute activated inside the task, like tags, task_run_name, retries, retry_delay_second and timeout_seconds for each task which called from the For loop using submit method ?

Sure, you can add attributes like

tags

,

task_run_name

,

retries

,

retry_delay_seconds

, and

timeout_seconds

to each task submitted in the for loop. Here's how you can refactor the code:

python
from prefect import task, Flow
import time
from datetime import timedelta

class Elevator:
    def __init__(self):
        pass

    @staticmethod
    @task
    def stop_at_floor(floor):
        print(f"elevator moving to floor {floor}")
        time.sleep(floor)
        print(f"elevator stops on floor {floor}")

    def prepare_tasks(self):
        future_tasks = []
        for floor, fname in zip(range(10, 0, -1), [f"t_{i+1}" for i in range(10)]):
            task_run = Elevator.stop_at_floor.submit(
                floor,
                tags=["elevator", "operation"],
                task_run_name=fname,
                retries=3,
                retry_delay_seconds=10,
                timeout_seconds=120
            )
            future_tasks.append(task_run)
        return future_tasks

def elevator_flow():
    elevator = Elevator()
    future_tasks = elevator.prepare_tasks()
    # Optionally, wait for the tasks to complete if needed
    # for future_task in future_tasks:
    #     future_task.wait()

if __name__ == "__main__":
    # Define and run the flow
    with Flow("elevator-flow") as flow:
        elevator_flow()
    
    flow.run()

### Explanation: 1. Elevator Class: -

stop_at_floor

is still a

@staticmethod

decorated with

@task

. -

prepare_tasks

method has been updated to pass additional attributes to each task using the

.submit()

method. 2. Attributes: - `tags`: Tags for the task, set to

["elevator", "operation"]

. - `task_run_name`: A unique name for each task run, provided by the

fname

variable. - `retries`: Number of retries if the task fails, set to 3. - `retry_delay_seconds`: Delay between retries in seconds, set to 10 seconds. - `timeout_seconds`: Maximum time in seconds the task is allowed to run, set to 120 seconds. 3. Flow Definition and Execution: - The flow is defined outside the class and within a

__main__

block to allow it to run separately. - The

elevator_flow

function is called within the context of the flow. This setup will ensure that each task submitted in the loop has the specified attributes, and they are executed concurrently.