The idiomatic way in Prefect 3.x is to use

task_run_name=

on the

@task

decorator. For a task parameter, the simplest pattern is:

python
from prefect import task

@task(task_run_name="process-{customer_id}")
def process_customer(customer_id: str):
    ...

If you call:

python
process_customer("abc-123")

the task run name will be

process-abc-123

. Recommended approach - Use a string template when the name is just based on task parameters - Use a callable if you need more logic Example with a callable:

python
from prefect import task

def make_name(parameters):
    return f"process-{parameters['customer_id']}"

@task(task_run_name=make_name)
def process_customer(customer_id: str):
    ...

A couple of notes: -

task_run_name

names the task run, not the task definition itself - The template uses task function parameters, so

{customer_id}

must match the argument name exactly - This is the most idiomatic Prefect 3.x solution Docs/code-backed behavior from Prefect 3.x:

task_run_name

supports either a string template or a callable. If you want, I can also show the equivalent pattern for flow run names using

flow_run_name=

.

Example for flow runs:

python
from prefect import flow

@flow(flow_run_name="etl-{dataset}")
def etl(dataset: str):
    ...

etl("customers")

That creates a flow run named

etl-customers

. And together with a task:

python
from prefect import flow, task

@task(task_run_name="extract-{table}")
def extract(table: str):
    ...

@flow(flow_run_name="pipeline-{table}")
def pipeline(table: str):
    extract(table)

pipeline("orders")

This gives you: - flow run name:

pipeline-orders

- task run name:

extract-orders

If you need more complex naming logic,

flow_run_name

can also be a callable, similar to

task_run_name

. Relevant docs/source-backed behavior: - Prefect supports dynamic

task_run_name

and

flow_run_name

via templates/callables in 3.x - Prefect docs: https://docs.prefect.io/ If you'd like, I can give you the exact pattern for your task signature.