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<@ULVA73B9P> how do i run tasks asynchronously in ...
# ask-marvin
g
@Marvin how do i run tasks asynchronously in prefect 3.x
m
In Prefect 3.x, you can run tasks asynchronously by using asynchronous Python functions. Prefect supports both synchronous and asynchronous tasks, allowing you to leverage Python's 
async
and 
await
features. Here's a concise guide on how to create and run asynchronous tasks: 1. Define an Asynchronous Task: Use the 
@task
decorator on an asynchronous function:
Copy code
python
   from prefect import task

   @task
   async def async_task():
       # Your asynchronous code here
       pass
2. Run Asynchronous Tasks: Asynchronous tasks can be awaited or run concurrently, following standard async Python behavior. When you define a flow, you can await these tasks:
Copy code
python
   from prefect import flow

   @flow
   async def my_flow():
       await async_task()
3. Considerations: - Prefect's 
.map
and 
.submit
methods are synchronous, even if the underlying function is asynchronous. Futures returned by these methods must be resolved manually or by passing them to another task. - Prefect 3.x uses 
pydantic 2
, and there are notable changes from Prefect 2.x, such as the replacement of agents with workers. For more detailed guidance, you can refer to the Prefect documentation on writing tasks. If you have any specific implementation questions or need further assistance, feel free to ask!
g
@Marvin how do i make multiple tasks run at the same time
m
To run multiple tasks concurrently in Prefect 3.x, you can utilize task workers to execute tasks in parallel. Here's a concise guide on how to achieve this: 1. Set Up Task Workers: Prefect allows you to run tasks in parallel by using multiple task workers. You can start several instances of task workers to handle concurrent task execution.
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bash
   python task_worker.py
2. Submit Multiple Tasks: Modify your task submission script to dispatch multiple tasks to the task workers. This can be done by calling the task with different inputs:
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python
   from tasks import my_background_task

   if __name__ == "__main__":
       my_background_task.delay("Ford")
       my_background_task.delay("Prefect")
       my_background_task.delay("Slartibartfast")
This setup allows tasks to be distributed across available workers, enabling parallel execution. 3. Monitor Task Execution: You can observe the execution of these tasks in Prefect's UI, which provides insights into task runs and their statuses. For more details on setting up concurrent task execution, you can refer to the Prefect background task examples. If you have any specific questions about implementing this setup, feel free to ask!
g
@Marvin lets say i have 'task_a' and 'task_b' on a flow and they don't depend on each other, how would i make them run simultaneously?
m
In Prefect 3.x, if you have two tasks, 
task_a
and 
task_b
, that do not depend on each other, they can naturally run concurrently within a flow. Prefect's task scheduling automatically handles the execution of independent tasks in parallel when possible. Here's how you can define such a flow:
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python
from prefect import flow, task

@task
def task_a():
    # Task A logic here
    pass

@task
def task_b():
    # Task B logic here
    pass

@flow
def my_flow():
    future_a = task_a.submit()  # Submit task_a
    future_b = task_b.submit()  # Submit task_b
    # Both tasks will run concurrently as they don't depend on each other

my_flow()
### Key Points: - Task Submission: Use 
task.submit()
to initiate tasks, allowing Prefect to manage their execution. This method returns a future, which can be awaited or used to retrieve results later. - Concurrency: Prefect automatically runs tasks concurrently if there are no dependencies between them. You don't need to explicitly define parallelism; Prefect's engine handles it for you. By submitting tasks independently within the flow, Prefect will execute them in parallel, assuming there are sufficient resources and no explicit dependencies. For further details, you can explore Prefect's task execution documentation.
g
@Marvin how can i use submit with an async task?
m
To use the 
submit
method with an asynchronous task in Prefect 3.x, you can follow these steps: 1. Define an Asynchronous Task: Use the 
@task
decorator to define an asynchronous task:
Copy code
python
   from prefect import task

   @task
   async def async_task():
       # Your asynchronous logic here
       pass
2. Submit the Asynchronous Task: In your flow, you can submit the asynchronous task using the 
submit
method. This method will handle the task execution and return a future.
Copy code
python
   from prefect import flow

   @flow
   async def my_flow():
       future = async_task.submit()  # Submit the async task
       result = await future.result()  # Await the result of the task

   my_flow()
### Key Points: - Task Submission: The 
submit
method is used to schedule the task for execution. It returns a future object which can be awaited to get the task's result. - Handling Results: Use 
await future.result()
to retrieve the result of the asynchronous task. By following this pattern, you can effectively manage and execute asynchronous tasks within a Prefect flow. For additional details, you can refer to the Prefect task documentation.
g
@Marvin can i use .submit() with .map()?
m
In Prefect 3.x, you can use 
.submit()
and 
.map()
together, but it's important to understand their distinct roles: - 
.submit()
: This method is used to schedule a single task execution and returns a future. It allows you to execute tasks asynchronously within a flow. - 
.map()
: This method is used to apply a task across an iterable of inputs, creating multiple task runs. It returns a list of futures corresponding to each mapped task run. ### Key Points: - Execution Context: Both methods must be called within a flow run context. - Concurrency: 
.map()
is inherently synchronous in how it schedules tasks, even if the underlying function is asynchronous. However, once tasks are submitted, they can run concurrently. - Combining Use: You can use 
.submit()
for individual tasks and 
.map()
for batch processing within the same flow, but they operate independently. 
.submit()
is for single tasks, while 
.map()
is for iterables. Here's an example of using both within a flow:
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python
from prefect import flow, task

@task
def process_item(item):
    # Task logic here
    pass

@task
def single_task():
    # Single task logic here
    pass

@flow
def my_flow():
    # Map task across an iterable
    mapped_results = process_item.map(range(10))
    
    # Submit a single task
    single_result = single_task.submit()
    
    # Wait for results if needed
    results = [result.result() for result in mapped_results]
    single_output = single_result.result()

my_flow()
This setup allows you to handle both batch and individual task executions efficiently. For more details, you can refer to Prefect's task documentation.
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