Task configuration

As we saw in Getting started, you can run any Python function as a task in Flyte just by decorating it with @env.task.

This allows you to run your Python code in a distributed manner, with each function running in its own container. Flyte manages the spinning up of the containers, the execution of the code, and the passing of data between the tasks.

In Getting started we demonstrated the simplest possible case, a TaskEnvironment with only a name parameter, and an env.task decorator, with no parameters:

env = flyte.TaskEnvironment(name="hello_world")

@env.task
async def say_hello(data: str, lt: List[int]) -> str:
    ...

Notice how the TaskEnvironment is assigned to the variable env and then that variable is used in the @env.task. This is what connects the TaskEnvironment to the task definition.

In the following we will often use @env.task generically to refer to the decorator, but it is important to remember that it is actually a decorator attached to a specific TaskEnvironment object, and the env part can be any variable name you like.

This will run your task in the default container environment with default settings.

But, of course, one of the key advantages of Flyte is the ability to control the software environment, hardware environment, and other execution parameters for each task, right in your Python code. In this section we will explore the various configuration options available for tasks in Flyte.

Task configuration levels

Task configuration is done at three levels. From most general to most specific, they are:

  • The TaskEnvironment level: setting parameters when defining the TaskEnvironment object.
  • The @env.task decorator level: Setting parameters in the @env.task decorator when defining a task function.
  • The task invocation level: Using the task.override() method when invoking task execution.

Each level has its own set of parameters, and some parameters are shared across levels. For shared parameters, the more specific level will override the more general one.

Example

Here is an example of how these levels work together, showing each level with all available parameters:

import flyte

# Level 1: TaskEnvironment - Base configuration
env = flyte.TaskEnvironment(
    name="data_processing_env",
    image=flyte.Image.from_debian_base(),
    resources=flyte.Resources(cpu=1, memory="512Mi"),
    env_vars={"MY_VAR": "value"},
    secrets=flyte.Secret(key="my_api_key", as_env_var="MY_API_KEY"),
    cache="disable",
    pod_template=my_pod_template_spec,
    reusable=flyte.ReusePolicy(replicas=2, idle_ttl=300),
    depends_on=[another_env],
    description="My task environment",
    plugin_config=my_plugin_config
)

# Level 2: Decorator - Override some environment settings
@env.task(
    short_name="process",
    secrets=flyte.Secret(key="my_api_key_2", as_env_var="MY_API_KEY"),
    cache="auto"
    pod_template=my_pod_template_spec_2,
    report=True,
    max_inline_io_bytes=100 * 1024
    retries=3,
    timeout=60
    docs="This task processes data and generates a report."
)
async def process_data(data_path: str) -> str:
    return f"Processed {data_path}"

@env.task
async def main() -> str:
    result = await process_data.override(
        resources=flyte.Resources(cpu=4, memory="2Gi"),
        env_vars={"MY_VAR": "new_value"},
        secrets=flyte.Secret(key="my_api_key_3", as_env_var="MY_API_KEY"),
        cache="enable",
        max_inline_io_bytes=100 * 1024,
        retries=3,
        timeout=60
    )("input.csv")
    return result

Parameter interaction

Here is an overview of all task configuration parameters available at each level and how they interact:

Parameter TaskEnvironment @env.task decorator override on task invocation
name ✅ Yes (required) ❌ No ❌ No
short_name ❌ No ✅ Yes ✅ Yes
image ✅ Yes ❌ No ❌ No
resources ✅ Yes ❌ No ✅ Yes (if not reusable)
env_vars ✅ Yes ❌ No ✅ Yes (if not reusable)
secrets ✅ Yes ✅ Yes (if not reusable) ✅ Yes (if not reusable)
cache ✅ Yes ✅ Yes ✅ Yes
pod_template ✅ Yes ✅ Yes ❌ No
reusable ✅ Yes (see below) ❌ No ✅ Yes
depends_on ✅ Yes ❌ No ❌ No
description ✅ Yes ❌ No ❌ No
plugin_config ✅ Yes ❌ No ❌ No
report ❌ No ✅ Yes ❌ No
max_inline_io_bytes ❌ No ✅ Yes ✅ Yes
retries ❌ No ✅ Yes ✅ Yes
timeout ❌ No ✅ Yes ✅ Yes
docs ❌ No ✅ Yes ❌ No

Task configuration parameters

The full set of parameters available for configuring a task environment, task definition, and task invocation are:

name

  • Type: str (required)

  • Defines the name of the TaskEnvironment. Since it specifies the name of the environment, it cannot, logically, be overridden at the @env.task decorator or the task.override() invocation level.

    It is used in conjunction with the name of each @env.task function to define the fully-qualified name of the task. The fully qualified name is always the TaskEnvironment name (the one above) followed by a period and then the task function name (the name of the Python function being decorated). For example:

    env = flyte.TaskEnvironment(name="my_env")

@env.task
async def my_task(data: str) -> str:
    ...

    Here, the name of the TaskEnvironment is my_env and the fully qualified name of the task is my_env.my_task. The TaskEnvironment name and fully qualified name of a task name are both fixed and cannot be overridden.

short_name

  • Type: str (required)

  • Defines the short name of the task or action (the execution of a task). Since it specifies the name of the task, it is not, logically, available to be set at the ``TaskEnvironment` level.

    By default, the short name of a task is the name of the task function (the name of the Python function being decorated). The short name is used, for example, in parts of the UI. Overriding it does not change the fully qualified name of the task.

image

  • Type: Union[str, Image, Literal['auto']]

  • Specifies the Docker image to use for the task container. Can be a URL reference to a Docker image, an Image object, or the string auto. If set to auto, or if this parameter is not set, the default image will be used. See Container images.

  • Only settable at the TaskEnvironment level.

resources

  • Type: Optional[Resources]

  • Specifies the compute resources, such as CPU and Memory, required by the task environment using a Resources object.

  • Can be set at the TaskEnvironment level and overridden at the task.override() invocation level (but only if reuseable is not in effect).

env_vars

  • Type: Optional[Dict[str, str]]

  • A dictionary of environment variables to be made available in the task container. These variables can be used to configure the task at runtime, such as setting API keys or other configuration values.

secrets

  • Type: Optional[SecretRequest] where SecretRequest is an alias for Union[str, Secret, List[str | Secret]]

  • The secrets to be made available in the task container. See the Secrets section and the API docs for the Secret object.

  • Can be set at the TaskEnvironment level and overridden at the @env.task decorator level and at the task.override() invocation level, but, in both cases, only if reuseable is not in effect.

cache

  • Type: Union[CacheRequest] where CacheRequest is an alias for Literal["auto", "override", "disable", "enabled"] | Cache.

  • Specifies the caching policy to be used for this task. See Caching.

  • Can be set at the TaskEnvironment level and overridden at the @env.task decorator level and at the task.override() invocation level.

pod_template

  • Type: Optional[Union[str, kubernetes.client.V1PodTemplate]]

  • A pod template that defines the Kubernetes pod configuration for the task. A string reference to a named template or a kubernetes.client.V1PodTemplate object.

  • Can be set at the TaskEnvironment level and overridden at the @env.task decorator level, but not at the task.override() invocation level.

reusable

The reusable setting controls the reusable containers feature. This feature is only available when running your Flyte code on a Union.ai backend. See one of the Union.ai product variants of this page for details.

depends_on

  • Type: List[Environment]

  • A list of Environment objects that this TaskEnvironment depends on. When deploying this TaskEnvironment, the system will ensure that any dependencies of the listed Environments are also available. This is useful when you have a set of task environments that depend on each other.

  • Can only be set at the TaskEnvironment level, not at the @env.task decorator level or the task.override() invocation level.

description

  • Type: Optional[str]

  • A description of the task environment. This can be used to provide additional context about the task environment, such as its purpose or usage.

  • Can only be set at the TaskEnvironment level, not at the @env.task decorator level or the task.override() invocation level.

plugin_config

  • Type: Optional[Any]

  • Additional configuration for plugins that can be used with the task environment. This can include settings for specific plugins that are used in the task environment.

  • Can only be set at the TaskEnvironment level, not at the @env.task decorator level or the task.override() invocation level.

report

  • Type: bool
  • Whether to generate the HTML report for the task. If set to True, the task will generate an HTML report that can be viewed in the Flyte UI.
  • Can only be set at the @env.task decorator level, not at the TaskEnvironment level or the task.override() invocation level.
  • See Reports.

max_inline_io_bytes

  • Type: int

  • Maximum allowed size (in bytes) for all inputs and outputs passed directly to the task (e.g., primitives, strings, dicts). Does not apply to flyte.File, flyte.Dir, or flyte.DataFrame (since these are passed by reference).

  • Can be set at the @env.task decorator level and overridden at the task.override() invocation level. If not set, the default value is MAX_INLINE_IO_BYTES (which is 100 MiB).

retries

  • Type: Union[int, RetryStrategy]

  • The number of retries for the task, or a RetryStrategy object that defines the retry behavior. If set to 0, no retries will be attempted.

  • Can be set at the @env.task decorator level and overridden at the task.override() invocation level.

timeout

  • Type: Union[timedelta, int]

  • The timeout for the task, either as a timedelta object or an integer representing seconds. If set to 0, no timeout will be applied.

  • Can be set at the @env.task decorator level and overridden at the task.override() invocation level.

docs

  • Type: Optional[Documentation]

  • Documentation for the task, including usage examples and explanations of the task’s behavior.

  • Can only be set at the @env.task decorator level. It cannot be overridden.