@Marvin I'm using a for loop in a flow to iterate through a list. I'd like to create tasks within the flow for each iteration and dynamically name each task. For example, instead of

task-0

,

task-1

, etc, I'd like to use the string that comes from each iteration to name tasks like

customer

,

product

, etc.

I understand the concept you're getting at. To find precise steps to accomplish this, I'll search Prefect documentation and retrieve relevant code examples. One moment while I gather this information. I'll look for: 1. How to create tasks dynamically within a flow. 2. How to name tasks dynamically based on iteration values. Let me run these searches. The documentation search had an error, but I did find a relevant code example for dynamically naming tasks using Prefect. Below is a basic implementation to dynamically name tasks within a flow:

python
from prefect import flow, task

# Define the task with a templated name
@task(task_run_name="Processing {item}")
def process_item(item: str):
    # Perform some processing with the item
    print(f"Processing {item}")

# Define the flow
@flow
def dynamic_naming_flow(items: list):
    for item in items:
        process_item(item)  # Task name will be "Processing {item}"

# Example usage
if __name__ == "__main__":
    items_to_process = ["customer", "product", "order"]
    dynamic_naming_flow(items_to_process)

In this example: - The

@task

decorator is used to define a task named

process_item

. - The

task_run_name

parameter within the decorator allows dynamic naming using string templating

{item}

. - The flow

dynamic_naming_flow

iterates over

items

and calls

process_item

for each item. This way, tasks are named according to the item being processed (e.g., "Processing customer", "Processing product"). For more details on templating in task names, you can refer to the relevant part in the Prefect documentation. Would you like me to try searching for more examples or details?

@Marvin What's the difference between

name

and

task_run_name

parameter within the

@task

decorator?

It appears our search didn't retrieve relevant information from GitHub issues. However, I can explain the difference based on my understanding of Prefect's task decorators

name

and

task_run_name

. In Prefect: 1.

name

: - This parameter sets a static name for the task itself. This name is used in logs, the Prefect UI, and when referring to the task in code and configuration. - Example:

python
     @task(name="My Custom Task")
     def my_task():
         pass

- If you have many instances of this task inside the same flow, they will all share this name. 2.

task_run_name

: - This parameter allows dynamic naming for each instance (or run) of the task when the flow is executed. It is useful for templating parts of the task name based on input parameters or other context-specific information. - Example:

python
     @task(task_run_name="Processing {item}")
     def my_task(item: str):
         pass

- Each execution of this task will have a different name formatted with the specific

item

being processed, e.g., "Processing customer", "Processing product". In essence,

name

is for the task itself (static), while

task_run_name

is for the individual executions of the task (dynamic). Would you like me to search for more details or examples from the Prefect documentation?