Named Outputs#

Tags: Basic

By default, Flyte employs a standardized convention to assign names to the outputs of tasks or workflows. Each output is sequentially labeled as o1, o2, o3, โ€ฆ on, where o serves as the standard prefix, and 1, 2, โ€ฆ n indicates the positional index within the returned values.

However, Flyte allows the customization of output names for tasks or workflows. This customization becomes beneficial when youโ€™re returning multiple outputs and you wish to assign a distinct name to each of them.

The following example illustrates the process of assigning names to outputs for both a task and a workflow.

To begin, import the required dependencies.

from typing import NamedTuple

from flytekit import task, workflow

Define a NamedTuple and assign it as an output to a task.

slope_value = NamedTuple("slope_value", [("slope", float)])

def slope(x: list[int], y: list[int]) -> slope_value:
    sum_xy = sum([x[i] * y[i] for i in range(len(x))])
    sum_x_squared = sum([x[i] ** 2 for i in range(len(x))])
    n = len(x)
    return (n * sum_xy - sum(x) * sum(y)) / (n * sum_x_squared - sum(x) ** 2)

Likewise, assign a NamedTuple to the output of intercept task.

intercept_value = NamedTuple("intercept_value", [("intercept", float)])

def intercept(x: list[int], y: list[int], slope: float) -> intercept_value:
    mean_x = sum(x) / len(x)
    mean_y = sum(y) / len(y)
    intercept = mean_y - slope * mean_x
    return intercept


While itโ€™s possible to create NamedTuples directly within the code, itโ€™s often better to declare them explicitly. This helps prevent potential linting errors in tools like pypy.

def slope() -> NamedTuple("slope_value", slope=float):

You can easily unpack the NamedTuple outputs directly within a workflow. Additionally, you can also have the workflow return a NamedTuple as an output.


Remember that we are extracting individual task execution outputs by dereferencing them. This is necessary because NamedTuples function as tuples and require this dereferencing.

slope_and_intercept_values = NamedTuple("slope_and_intercept_values", [("slope", float), ("intercept", float)])

def simple_wf_with_named_outputs(x: list[int] = [-3, 0, 3], y: list[int] = [7, 4, -2]) -> slope_and_intercept_values:
    slope_value = slope(x=x, y=y)
    intercept_value = intercept(x=x, y=y, slope=slope_value.slope)
    return slope_and_intercept_values(slope=slope_value.slope, intercept=intercept_value.intercept)

You can run the workflow locally as follows:

if __name__ == "__main__":
    print(f"Running simple_wf_with_named_outputs() {simple_wf_with_named_outputs()}")