Flyte enables production-grade orchestration for machine learning workflows and data processing created to accelerate local workflows to production.

Flyte

I'm currently looking at how map_task works and <https://www.union.ai/docs/flyte/user-guide/core-concepts/tasks/map-tasks/|followed the example here>, however if I add a second parameter to the `detect_anomalies` task, I get the error:

```TypeTransformerFailedError: Failed to Bind variable 'threshold' for function 
'map_task.map_detect_anomalies_6b3bd0353da5de6e84d7982921ead2b3-arraynode':
 Expected a list```
Could someone explain why this error gets thrown?

Code snippet in :thread:

```import logging
from flytekit import task, workflow, map_task

logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)

@task
def detect_anomalies(data_point: int, threshold: int) -&gt; bool:
    return data_point &gt; threshold

@task
def coalesce(evals: List[bool]) -&gt; None:
    <http://logger.info|logger.info>('Result: {}'.format(evals))

@workflow
def map_workflow(data: list[int] = [10, 12, 11, 10, 13, 12, 100, 11, 12, 10]) -&gt; None:
    # Use the map task to apply the anomaly detection function to each data point
    mapped_tasks = map_task(detect_anomalies)(data_point=data, threshold=11)
    return coalesce(mapped_tasks)```

I think this is best shown in the legacy documentation here: <https://docs-legacy.flyte.org/en/latest/user_guide/advanced_composition/map_tasks.html#map-a-task-with-multiple-inputs>

The `map_task` only wants to step through a single list, you have to bind the static values first

so you'd end up with something like
```partial_task = functools.partial(detect_anomalies, threshold=11)
map_task(partial_task)(data_point=data)```

Superb! Thank you very much <@U05LEL74N66>, especially for the explanation. Now <https://flyte-org.slack.com/archives/CNMKCU6FR/p1747684543489539|that docs are public> I'll open an MR so that this legacy documentation gets surfaced as it clearly still applies.