Guilins
01/28/2025, 7:30 PMMarvin
01/28/2025, 7:30 PM.map() in Prefect 3.x, you can follow these steps:
1. Define Your Tasks: Create tasks that you want to run concurrently. In Prefect, tasks are defined using the @task decorator.
2. Use Task Runners: Prefect uses task runners to manage concurrent execution. The default task runner is ThreadPoolTaskRunner, which runs tasks concurrently within a thread pool. For more advanced parallel execution, you can use DaskTaskRunner or RayTaskRunner.
3. Map Tasks: Use the map method to apply a task across a collection of inputs, enabling concurrent execution. This is similar to Python's built-in map function but designed for concurrent execution in Prefect.
Here is a basic example:
python
from prefect import flow, task
from prefect.task_runners import ThreadPoolTaskRunner
@task
def my_task(x):
return x * x
@flow(task_runner=ThreadPoolTaskRunner())
def my_flow(data):
results = my_task.map(data)
return results
# Run the flow with a list of inputs
my_flow([1, 2, 3, 4, 5])
In this example, my_task will be executed concurrently across the list [1, 2, 3, 4, 5]. You can adjust the concurrency level by configuring the task runner.
For more details, you can refer to the Prefect Task Runners documentation.Bring your towel and join one of the fastest growing data communities. Welcome to our second-generation open source orchestration platform, a completely rethought approach to dataflow automation.
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