# Task runs

A task run is created for each task in your flow during a flow run. Like flow runs, task runs have a backend generated unique id and their state is updated as they are executed.


Prefect does not store the results of your task runs. The data that your task returns is stored safely on your own infrastructure unless explicitly sent to Prefect's backend.

# Inspecting task runs

# Python

The Prefect Core library provides an object for inspecting task runs without writing queries at prefect.backend.TaskRunView.

# Creating a TaskRunView


You should typically access task runs from a FlowRunView object. This will cache TaskRunView objects for finished tasks and pass the flow_run_id for you. Read the flow run inspection documentation to get started.

A TaskRunView is created by querying the backend for task run data. You can use the task slug or the task run id to look up the data for a TaskRunView.

# Task run results

Results from task runs are persisted to the location you've specified in the task's result attribute. The Result type allows you to store task results in many locations on your own infrastructure. See the results documentation for more details on configuring results.

TaskRunView provides a get_result method which will load and cache the return value of your task from the result location.

# Presume we have a flow with the following task
def foo():
  return "foobar!"

task_run = TaskRunView.from_task_slug("foo-1", flow_run_id="<id>")
task_run.get_result()  # "foobar!"
# Mapped task results

The get_result method of a child of a mapped task will return the single result for that task run. For the parent task, an additional query will be run to get the result locations all of the children and a list will be returned populated with all of the child results.

For example, with the following flow:

from prefect import task, Flow

def inc(x):
  return x + 1

with Flow("example-mapped") as flow:
  inc.map([0, 1, 2, 3, 4, 5])

You can retrieve all of the mapped results or a single result:

from prefect.backend import TaskRunView

inc_parent = TaskRunView.from_task_slug("inc-1", flow_run_id="<id>")
inc_parent.get_result()  # [1, 2, 3, 4, 5, 6]

inc_child = TaskRunView.from_task_slug("inc-1", flow_run_id="<id>", map_index=2)
inc_child.get_result()  # 3

If your mapped task has many children, you can iterate through the children one at a time:

from prefect.backend import TaskRunView

inc_parent = TaskRunView.from_task_slug("inc-1", flow_run_id="<id>")
for child_task_run in inc_parent.iter_mapped():
# 1
# 2
# 3
# 4
# 5
# 6

# Task

For composing flows, the Prefect task library provides a task to retrieve the result of a task run from another flow run. This uses the TaskRunView.get_result() method under the hood, it may be helpful to get familiar with how that works first.

Given a very simple 'child' flow

from prefect import Flow, task

def create_some_data():
    return list(range(5))

with Flow("child") as child_flow:
    data = create_some_data()

We can create a 'parent' flow that runs the 'child' flow and retrieves the results

from prefect import Flow
from prefect.tasks.prefect import create_flow_run, get_task_run_result

with Flow("parent") as parent_flow:
    child_run_id = create_flow_run(flow_name="child")

    child_data = get_task_run_result(child_run_id, "create_some_data-1")
    # At runtime, `child_data` will be `[0, 1, 2, 3, 4]`

For more details on creating child flow runs, see the create_flow_run task documentation

Results require completion

Task run results will not be retrieved until the flow run with the task run is finished. This is because the flow run may make changes to the task run before completion. This means that if your 'create_some_data' task run finishes but the 'child' flow run continues to do some other work, 'get_task_run_result' will block until all the tasks in the 'child' flow run are finished.

# GraphQL

# Querying for task runs in a flow run

Here we query for all of the task runs in a run of the prefect.hello_world flow

query {
  task_run(where: {flow_run_id: {_eq: "8e445d74-9ca6-425b-98e5-72754b7ea174"}}) {
    task {

Example response

  "data": {
    "task_run": [
        "id": "c8751f34-9d5e-4ea7-aead-8b50978dabb7",
        "state": "Success",
        "start_time": "2021-05-12T18:00:01.696849+00:00",
        "task": {
          "slug": "say_hello-1"
        "id": "f5f422f6-4f56-45d2-bd55-5ea048070d84",
        "state": "Success",
        "start_time": "2021-05-12T18:00:00.229202+00:00",
        "task": {
          "slug": "capitalize-1"
        "id": "7cc167d3-737d-4187-85d8-d5e5a75fbd93",
        "state": "Success",
        "start_time": "2021-05-12T17:59:58.33804+00:00",
        "task": {
          "slug": "name"

# UI

For monitoring task runs from the UI, see the UI documentation on task runs.


The CLI does not currently support looking up task run information. Would this be useful to you? Chime in on GitHub.