union.remote
Directory
Classes
| Class | Description |
|---|---|
HuggingFaceModelInfo |
Captures information about a Hugging Face model. |
ShardConfig |
|
UnionRemote |
Main entrypoint for programmatically accessing a Flyte remote backend. |
VLLMShardArgs |
union.remote.HuggingFaceModelInfo
Captures information about a Hugging Face model. Only repo is required, all other fields are optional, and are automatically determined from the model’s config.json file. If not found, the fields are initialized to defaults.
class HuggingFaceModelInfo(
repo: str,
artifact_name: str | None,
model_type: str | None,
architecture: str | None,
task: str,
modality: typing.List[str] | None,
serial_format: str,
short_description: str | None,
shard_config: ShardConfig | None,
)| Parameter | Type | Description |
|---|---|---|
repo |
str |
|
artifact_name |
str | None |
|
model_type |
str | None |
|
architecture |
str | None |
|
task |
str |
|
modality |
typing.List[str] | None |
|
serial_format |
str |
|
short_description |
str | None |
|
shard_config |
ShardConfig | None |
union.remote.ShardConfig
class ShardConfig(
engine: str,
args: *args,
)| Parameter | Type | Description |
|---|---|---|
engine |
str |
|
args |
*args |
union.remote.UnionRemote
Main entrypoint for programmatically accessing a Flyte remote backend.
The term ‘remote’ is synonymous with ‘backend’ or ‘deployment’ and refers to a hosted instance of the Flyte platform, which comes with a Flyte Admin server on some known URI.
class UnionRemote(
config: typing.Optional[Union[Config, str]],
default_project: typing.Optional[str],
default_domain: typing.Optional[str],
data_upload_location: str,
interactive_mode_enabled: typing.Optional[bool],
kwargs,
)Initialize a FlyteRemote object.
:type kwargs: All arguments that can be passed to create the SynchronousFlyteClient. These are usually grpc parameters, if you want to customize credentials, ssl handling etc.
| Parameter | Type | Description |
|---|---|---|
config |
typing.Optional[Union[Config, str]] |
|
default_project |
typing.Optional[str] |
default project to use when fetching or executing flyte entities. |
default_domain |
typing.Optional[str] |
default domain to use when fetching or executing flyte entities. |
data_upload_location |
str |
this is where all the default data will be uploaded when providing inputs. The default location - s3://my-s3-bucket/data works for sandbox/demo environment. Please override this for non-sandbox cases. |
interactive_mode_enabled |
typing.Optional[bool] |
If set to True, the FlyteRemote will pickle the task/workflow, if False, it will not. If set to None, then it will automatically detect if it is running in an interactive environment like a Jupyter notebook and enable interactive mode. |
kwargs |
**kwargs |
Methods
| Method | Description |
|---|---|
activate_launchplan() |
Given a launchplan, activate it, all previous versions are deactivated. |
approve() |
|
async_channel() |
|
auto() |
|
create_artifact() |
Create an artifact in FlyteAdmin. |
deactivate_launchplan() |
Given a launchplan, deactivate it, all previous versions are deactivated. |
deploy_app() |
Deploy an application. |
download() |
Download the data to the specified location. |
execute() |
Execute a task, workflow, or launchplan, either something that’s been declared locally, or a fetched entity. |
execute_local_launch_plan() |
Execute a locally defined LaunchPlan. |
execute_local_task() |
Execute a @task-decorated function or TaskTemplate task. |
execute_local_workflow() |
Execute an @workflow decorated function. |
execute_reference_launch_plan() |
Execute a ReferenceLaunchPlan. |
execute_reference_task() |
Execute a ReferenceTask. |
execute_reference_workflow() |
Execute a ReferenceWorkflow. |
execute_remote_task_lp() |
Execute a FlyteTask, or FlyteLaunchplan. |
execute_remote_wf() |
Execute a FlyteWorkflow. |
fast_package() |
Packages the given paths into an installable zip and returns the md5_bytes and the URL of the uploaded location. |
fast_register_workflow() |
Use this method to register a workflow with zip mode. |
fetch_active_launchplan() |
Returns the active version of the launch plan if it exists or returns None. |
fetch_execution() |
Fetch a workflow execution entity from flyte admin. |
fetch_launch_plan() |
Fetch a launchplan entity from flyte admin. |
fetch_task() |
Fetch a task entity from flyte admin. |
fetch_task_lazy() |
Similar to fetch_task, just that it returns a LazyEntity, which will fetch the workflow lazily. |
fetch_workflow() |
Fetch a workflow entity from flyte admin. |
fetch_workflow_lazy() |
Similar to fetch_workflow, just that it returns a LazyEntity, which will fetch the workflow lazily. |
find_launch_plan() |
|
find_launch_plan_for_node() |
|
for_endpoint() |
|
for_sandbox() |
|
from_api_key() |
Call this if you want to directly instantiate a UnionRemote from an API key. |
generate_console_http_domain() |
This should generate the domain where console is hosted. |
generate_console_url() |
Generate a UnionAI console URL for the given Flyte remote endpoint. |
get() |
General function that works with flyte tiny urls. |
get_artifact() |
Get the specified artifact. |
get_domains() |
Lists registered domains from flyte admin. |
get_execution_metrics() |
Get the metrics for a given execution. |
get_extra_headers_for_protocol() |
|
launch_backfill() |
Creates and launches a backfill workflow for the given launchplan. |
list_projects() |
Lists registered projects from flyte admin. |
list_signals() |
|
list_tasks_by_version() |
|
raw_register() |
Raw register method, can be used to register control plane entities. |
recent_executions() |
|
register_launch_plan() |
Register a given launchplan, possibly applying overrides from the provided options. |
register_script() |
Use this method to register a workflow via script mode. |
register_task() |
Register a qualified task (PythonTask) with Remote. |
register_workflow() |
Use this method to register a workflow. |
reject() |
|
remote_context() |
Context manager with remote-specific configuration. |
search_artifacts() |
|
set_input() |
|
set_signal() |
|
stop_app() |
Stop an application. |
stream_execution_events() |
Stream execution events from the given tenant. |
sync() |
This function was previously a singledispatchmethod. |
sync_execution() |
Sync a FlyteWorkflowExecution object with its corresponding remote state. |
sync_node_execution() |
Get data backing a node execution. |
sync_task_execution() |
Sync a FlyteTaskExecution object with its corresponding remote state. |
terminate() |
Terminate a workflow execution. |
upload_file() |
Function will use remote’s client to hash and then upload the file using Admin’s data proxy service. |
wait() |
Wait for an execution to finish. |
activate_launchplan()
def activate_launchplan(
ident: Identifier,
)Given a launchplan, activate it, all previous versions are deactivated.
| Parameter | Type | Description |
|---|---|---|
ident |
Identifier |
approve()
def approve(
signal_id: str,
execution_name: str,
project: str,
domain: str,
)| Parameter | Type | Description |
|---|---|---|
signal_id |
str |
The name of the signal, this is the key used in the approve() or wait_for_input() call. |
execution_name |
str |
The name of the execution. This is the tail-end of the URL when looking at the workflow execution. |
project |
str |
The execution project, will default to the Remote’s default project. |
domain |
str |
The execution domain, will default to the Remote’s default domain. |
async_channel()
def async_channel()auto()
def auto(
config_file: typing.Union[str, ConfigFile],
default_project: typing.Optional[str],
default_domain: typing.Optional[str],
data_upload_location: str,
interactive_mode_enabled: bool,
kwargs,
) -> 'FlyteRemote'| Parameter | Type | Description |
|---|---|---|
config_file |
typing.Union[str, ConfigFile] |
|
default_project |
typing.Optional[str] |
|
default_domain |
typing.Optional[str] |
|
data_upload_location |
str |
|
interactive_mode_enabled |
bool |
|
kwargs |
**kwargs |
create_artifact()
def create_artifact(
artifact: Artifact,
) -> ArtifactCreate an artifact in FlyteAdmin.
| Parameter | Type | Description |
|---|---|---|
artifact |
Artifact |
The artifact to create. :return: The artifact as persisted in the service. |
deactivate_launchplan()
def deactivate_launchplan(
ident: Identifier,
)Given a launchplan, deactivate it, all previous versions are deactivated.
| Parameter | Type | Description |
|---|---|---|
ident |
Identifier |
deploy_app()
def deploy_app(
app: App,
project: Optional[str],
domain: Optional[str],
) -> AppIDLDeploy an application.
| Parameter | Type | Description |
|---|---|---|
app |
App |
Application to deploy. |
project |
Optional[str] |
Domain name. If None, uses default_domain. :return: The App IDL for the deployed application. |
domain |
Optional[str] |
download()
def download(
data: typing.Union[LiteralsResolver, Literal, LiteralMap],
download_to: str,
recursive: bool,
)Download the data to the specified location. If the data is a LiteralsResolver, LiteralMap and if recursive is specified, then all file like objects will be recursively downloaded (e.g. FlyteFile/Dir (blob), StructuredDataset etc).
Note: That it will use your sessions credentials to access the remote location. For sandbox, this should be automatically configured, assuming you are running sandbox locally. For other environments, you will need to configure your credentials appropriately.
| Parameter | Type | Description |
|---|---|---|
data |
typing.Union[LiteralsResolver, Literal, LiteralMap] |
data to be downloaded |
download_to |
str |
location to download to (str) that should be a valid path |
recursive |
bool |
if the data is a LiteralsResolver or LiteralMap, then this flag will recursively download |
execute()
def execute(
entity: typing.Union[FlyteTask, FlyteLaunchPlan, FlyteWorkflow, PythonTask, WorkflowBase, LaunchPlan, ReferenceEntity],
inputs: typing.Optional[typing.Dict[str, typing.Any]],
project: str,
domain: str,
name: str,
version: str,
execution_name: typing.Optional[str],
execution_name_prefix: typing.Optional[str],
image_config: typing.Optional[ImageConfig],
options: typing.Optional[Options],
wait: bool,
type_hints: typing.Optional[typing.Dict[str, typing.Type]],
overwrite_cache: typing.Optional[bool],
interruptible: typing.Optional[bool],
envs: typing.Optional[typing.Dict[str, str]],
tags: typing.Optional[typing.List[str]],
cluster_pool: typing.Optional[str],
execution_cluster_label: typing.Optional[str],
serialization_settings: typing.Optional[SerializationSettings],
) -> FlyteWorkflowExecutionExecute a task, workflow, or launchplan, either something that’s been declared locally, or a fetched entity.
This method supports:
Flyte{Task, Workflow, LaunchPlan}remote module objects.@task-decorated functions andTaskTemplatetasks.@workflow-decorated functions.LaunchPlanobjects.
For local entities, this code will attempt to find the entity first, and if missing, will compile and register the object.
Not all arguments are relevant in all circumstances. For example, there’s no reason to use the serialization settings for entities that have already been registered on Admin.
| Parameter | Type | Description |
|---|---|---|
entity |
typing.Union[FlyteTask, FlyteLaunchPlan, FlyteWorkflow, PythonTask, WorkflowBase, LaunchPlan, ReferenceEntity] |
entity to execute |
inputs |
typing.Optional[typing.Dict[str, typing.Any]] |
dictionary mapping argument names to values |
project |
str |
execute entity in this project. If entity doesn’t exist in the project, register the entity first before executing. |
domain |
str |
execute entity in this domain. If entity doesn’t exist in the domain, register the entity first before executing. |
name |
str |
execute entity using this name. If not None, use this value instead of entity.name |
version |
str |
execute entity using this version. If None, uses auto-generated value. |
execution_name |
typing.Optional[str] |
name of the execution. If None, uses auto-generated value. |
execution_name_prefix |
typing.Optional[str] |
execution prefix to use. If provided, a random suffix will be appended |
image_config |
typing.Optional[ImageConfig] |
|
options |
typing.Optional[Options] |
|
wait |
bool |
if True, waits for execution to complete |
type_hints |
typing.Optional[typing.Dict[str, typing.Type]] |
Python types to be passed to the TypeEngine so that it knows how to properly convert the input values for the execution into Flyte literals. If missing, will default to first guessing the type using the type engine, and then to type(v). Providing the correct Python types is particularly important if the inputs are containers like lists or maps, or if the Python type is one of the more complex Flyte provided classes (like a StructuredDataset that’s annotated with columns). |
overwrite_cache |
typing.Optional[bool] |
Allows for all cached values of a workflow and its tasks to be overwritten for a single execution. If enabled, all calculations are performed even if cached results would be available, overwriting the stored data once execution finishes successfully. |
interruptible |
typing.Optional[bool] |
Optional flag to override the default interruptible flag of the executed entity. |
envs |
typing.Optional[typing.Dict[str, str]] |
Environment variables to be set for the execution. |
tags |
typing.Optional[typing.List[str]] |
Tags to be set for the execution. |
cluster_pool |
typing.Optional[str] |
Specify cluster pool on which newly created execution should be placed. |
execution_cluster_label |
typing.Optional[str] |
Specify label of cluster(s) on which newly created execution should be placed. |
serialization_settings |
typing.Optional[SerializationSettings] |
Optionally provide serialization settings, in case the entity being run needs to first be registered. If not provided, a default will be used. > [!NOTE] > The name and version arguments do not apply to FlyteTask, FlyteLaunchPlan, and FlyteWorkflow entity inputs. These values are determined by referencing the entity identifier values. |
execute_local_launch_plan()
def execute_local_launch_plan(
entity: LaunchPlan,
inputs: typing.Optional[typing.Dict[str, typing.Any]],
version: str,
project: typing.Optional[str],
domain: typing.Optional[str],
name: typing.Optional[str],
execution_name: typing.Optional[str],
execution_name_prefix: typing.Optional[str],
options: typing.Optional[Options],
wait: bool,
overwrite_cache: typing.Optional[bool],
interruptible: typing.Optional[bool],
envs: typing.Optional[typing.Dict[str, str]],
tags: typing.Optional[typing.List[str]],
cluster_pool: typing.Optional[str],
execution_cluster_label: typing.Optional[str],
serialization_settings: typing.Optional[SerializationSettings],
) -> FlyteWorkflowExecutionExecute a locally defined LaunchPlan.
| Parameter | Type | Description |
|---|---|---|
entity |
LaunchPlan |
The locally defined launch plan object |
inputs |
typing.Optional[typing.Dict[str, typing.Any]] |
Inputs to be passed into the execution as a dict with Python native values. |
version |
str |
The version to look up/register the launch plan (if not already exists) |
project |
typing.Optional[str] |
The same as version, but will default to the Remote object’s project |
domain |
typing.Optional[str] |
The same as version, but will default to the Remote object’s domain |
name |
typing.Optional[str] |
The same as version, but will default to the entity’s name |
execution_name |
typing.Optional[str] |
If specified, will be used as the execution name instead of randomly generating. |
execution_name_prefix |
typing.Optional[str] |
|
options |
typing.Optional[Options] |
Options to be passed into the execution. |
wait |
bool |
If True, will wait for the execution to complete before returning. |
overwrite_cache |
typing.Optional[bool] |
If True, will overwrite the cache. |
interruptible |
typing.Optional[bool] |
Optional flag to override the default interruptible flag of the executed entity. |
envs |
typing.Optional[typing.Dict[str, str]] |
Environment variables to be passed into the execution. |
tags |
typing.Optional[typing.List[str]] |
Tags to be passed into the execution. |
cluster_pool |
typing.Optional[str] |
Specify cluster pool on which newly created execution should be placed. |
execution_cluster_label |
typing.Optional[str] |
Specify label of cluster(s) on which newly created execution should be placed. |
serialization_settings |
typing.Optional[SerializationSettings] |
Optionally provide serialization settings, in case the entity being run needs :return: FlyteWorkflowExecution object |
execute_local_task()
def execute_local_task(
entity: PythonTask,
inputs: typing.Optional[typing.Dict[str, typing.Any]],
project: str,
domain: str,
name: str,
version: str,
execution_name: typing.Optional[str],
execution_name_prefix: typing.Optional[str],
image_config: typing.Optional[ImageConfig],
wait: bool,
overwrite_cache: typing.Optional[bool],
interruptible: typing.Optional[bool],
envs: typing.Optional[typing.Dict[str, str]],
tags: typing.Optional[typing.List[str]],
cluster_pool: typing.Optional[str],
execution_cluster_label: typing.Optional[str],
options: typing.Optional[Options],
serialization_settings: typing.Optional[SerializationSettings],
) -> FlyteWorkflowExecutionExecute a @task-decorated function or TaskTemplate task.
| Parameter | Type | Description |
|---|---|---|
entity |
PythonTask |
local task entity. |
inputs |
typing.Optional[typing.Dict[str, typing.Any]] |
register the task, which requires compiling the task, before running it. |
project |
str |
The execution project, will default to the Remote’s default project. |
domain |
str |
The execution domain, will default to the Remote’s default domain. |
name |
str |
specific name of the task to run. |
version |
str |
specific version of the task to run, default is a special string latest, which implies latest version by time |
execution_name |
typing.Optional[str] |
If provided, will use this name for the execution. |
execution_name_prefix |
typing.Optional[str] |
If provided, will use this prefix for the execution name. |
image_config |
typing.Optional[ImageConfig] |
If provided, will use this image config in the pod. |
wait |
bool |
If True, will wait for the execution to complete before returning. |
overwrite_cache |
typing.Optional[bool] |
If True, will overwrite the cache. |
interruptible |
typing.Optional[bool] |
Optional flag to override the default interruptible flag of the executed entity. |
envs |
typing.Optional[typing.Dict[str, str]] |
Environment variables to set for the execution. |
tags |
typing.Optional[typing.List[str]] |
Tags to set for the execution. |
cluster_pool |
typing.Optional[str] |
Specify cluster pool on which newly created execution should be placed. |
execution_cluster_label |
typing.Optional[str] |
Specify label of cluster(s) on which newly created execution should be placed. |
options |
typing.Optional[Options] |
Options to customize the execution. |
serialization_settings |
typing.Optional[SerializationSettings] |
If the task needs to be registered, this can be passed in. :return: FlyteWorkflowExecution object. |
execute_local_workflow()
def execute_local_workflow(
entity: WorkflowBase,
inputs: typing.Optional[typing.Dict[str, typing.Any]],
project: str,
domain: str,
name: str,
version: str,
execution_name: typing.Optional[str],
execution_name_prefix: typing.Optional[str],
image_config: typing.Optional[ImageConfig],
options: typing.Optional[Options],
wait: bool,
overwrite_cache: typing.Optional[bool],
interruptible: typing.Optional[bool],
envs: typing.Optional[typing.Dict[str, str]],
tags: typing.Optional[typing.List[str]],
cluster_pool: typing.Optional[str],
execution_cluster_label: typing.Optional[str],
serialization_settings: typing.Optional[SerializationSettings],
) -> FlyteWorkflowExecutionExecute an @workflow decorated function.
| Parameter | Type | Description |
|---|---|---|
entity |
WorkflowBase |
The workflow to execute |
inputs |
typing.Optional[typing.Dict[str, typing.Any]] |
Input dictionary |
project |
str |
Project to execute in |
domain |
str |
Domain to execute in |
name |
str |
Optional name override for the workflow |
version |
str |
Optional version for the workflow |
execution_name |
typing.Optional[str] |
Optional name for the execution |
execution_name_prefix |
typing.Optional[str] |
|
image_config |
typing.Optional[ImageConfig] |
Optional image config override |
options |
typing.Optional[Options] |
Optional Options object |
wait |
bool |
Whether to wait for execution completion |
overwrite_cache |
typing.Optional[bool] |
If True, will overwrite the cache |
interruptible |
typing.Optional[bool] |
Optional flag to override the default interruptible flag of the executed entity |
envs |
typing.Optional[typing.Dict[str, str]] |
Environment variables to set for the execution |
tags |
typing.Optional[typing.List[str]] |
Tags to set for the execution |
cluster_pool |
typing.Optional[str] |
Specify cluster pool on which newly created execution should be placed |
execution_cluster_label |
typing.Optional[str] |
Specify label of cluster(s) on which newly created execution should be placed |
serialization_settings |
typing.Optional[SerializationSettings] |
Optionally provide serialization settings, in case the entity being run needs to be registered :return: FlyteWorkflowExecution object |
execute_reference_launch_plan()
def execute_reference_launch_plan(
entity: ReferenceLaunchPlan,
inputs: typing.Optional[typing.Dict[str, typing.Any]],
execution_name: typing.Optional[str],
execution_name_prefix: typing.Optional[str],
options: typing.Optional[Options],
wait: bool,
type_hints: typing.Optional[typing.Dict[str, typing.Type]],
overwrite_cache: typing.Optional[bool],
interruptible: typing.Optional[bool],
envs: typing.Optional[typing.Dict[str, str]],
tags: typing.Optional[typing.List[str]],
cluster_pool: typing.Optional[str],
execution_cluster_label: typing.Optional[str],
) -> FlyteWorkflowExecutionExecute a ReferenceLaunchPlan.
| Parameter | Type | Description |
|---|---|---|
entity |
ReferenceLaunchPlan |
|
inputs |
typing.Optional[typing.Dict[str, typing.Any]] |
|
execution_name |
typing.Optional[str] |
|
execution_name_prefix |
typing.Optional[str] |
|
options |
typing.Optional[Options] |
|
wait |
bool |
|
type_hints |
typing.Optional[typing.Dict[str, typing.Type]] |
|
overwrite_cache |
typing.Optional[bool] |
|
interruptible |
typing.Optional[bool] |
|
envs |
typing.Optional[typing.Dict[str, str]] |
|
tags |
typing.Optional[typing.List[str]] |
|
cluster_pool |
typing.Optional[str] |
|
execution_cluster_label |
typing.Optional[str] |
execute_reference_task()
def execute_reference_task(
entity: ReferenceTask,
inputs: typing.Optional[typing.Dict[str, typing.Any]],
execution_name: typing.Optional[str],
execution_name_prefix: typing.Optional[str],
options: typing.Optional[Options],
wait: bool,
type_hints: typing.Optional[typing.Dict[str, typing.Type]],
overwrite_cache: typing.Optional[bool],
interruptible: typing.Optional[bool],
envs: typing.Optional[typing.Dict[str, str]],
tags: typing.Optional[typing.List[str]],
cluster_pool: typing.Optional[str],
execution_cluster_label: typing.Optional[str],
) -> FlyteWorkflowExecutionExecute a ReferenceTask.
| Parameter | Type | Description |
|---|---|---|
entity |
ReferenceTask |
|
inputs |
typing.Optional[typing.Dict[str, typing.Any]] |
|
execution_name |
typing.Optional[str] |
|
execution_name_prefix |
typing.Optional[str] |
|
options |
typing.Optional[Options] |
|
wait |
bool |
|
type_hints |
typing.Optional[typing.Dict[str, typing.Type]] |
|
overwrite_cache |
typing.Optional[bool] |
|
interruptible |
typing.Optional[bool] |
|
envs |
typing.Optional[typing.Dict[str, str]] |
|
tags |
typing.Optional[typing.List[str]] |
|
cluster_pool |
typing.Optional[str] |
|
execution_cluster_label |
typing.Optional[str] |
execute_reference_workflow()
def execute_reference_workflow(
entity: ReferenceWorkflow,
inputs: typing.Optional[typing.Dict[str, typing.Any]],
execution_name: typing.Optional[str],
execution_name_prefix: typing.Optional[str],
options: typing.Optional[Options],
wait: bool,
type_hints: typing.Optional[typing.Dict[str, typing.Type]],
overwrite_cache: typing.Optional[bool],
interruptible: typing.Optional[bool],
envs: typing.Optional[typing.Dict[str, str]],
tags: typing.Optional[typing.List[str]],
cluster_pool: typing.Optional[str],
execution_cluster_label: typing.Optional[str],
) -> FlyteWorkflowExecutionExecute a ReferenceWorkflow.
| Parameter | Type | Description |
|---|---|---|
entity |
ReferenceWorkflow |
|
inputs |
typing.Optional[typing.Dict[str, typing.Any]] |
|
execution_name |
typing.Optional[str] |
|
execution_name_prefix |
typing.Optional[str] |
|
options |
typing.Optional[Options] |
|
wait |
bool |
|
type_hints |
typing.Optional[typing.Dict[str, typing.Type]] |
|
overwrite_cache |
typing.Optional[bool] |
|
interruptible |
typing.Optional[bool] |
|
envs |
typing.Optional[typing.Dict[str, str]] |
|
tags |
typing.Optional[typing.List[str]] |
|
cluster_pool |
typing.Optional[str] |
|
execution_cluster_label |
typing.Optional[str] |
execute_remote_task_lp()
def execute_remote_task_lp(
entity: typing.Union[FlyteTask, FlyteLaunchPlan],
inputs: typing.Optional[typing.Dict[str, typing.Any]],
project: str,
domain: str,
execution_name: typing.Optional[str],
execution_name_prefix: typing.Optional[str],
options: typing.Optional[Options],
wait: bool,
type_hints: typing.Optional[typing.Dict[str, typing.Type]],
overwrite_cache: typing.Optional[bool],
interruptible: typing.Optional[bool],
envs: typing.Optional[typing.Dict[str, str]],
tags: typing.Optional[typing.List[str]],
cluster_pool: typing.Optional[str],
execution_cluster_label: typing.Optional[str],
) -> FlyteWorkflowExecutionExecute a FlyteTask, or FlyteLaunchplan.
NOTE: the name and version arguments are currently not used and only there consistency in the function signature
| Parameter | Type | Description |
|---|---|---|
entity |
typing.Union[FlyteTask, FlyteLaunchPlan] |
|
inputs |
typing.Optional[typing.Dict[str, typing.Any]] |
|
project |
str |
|
domain |
str |
|
execution_name |
typing.Optional[str] |
|
execution_name_prefix |
typing.Optional[str] |
|
options |
typing.Optional[Options] |
|
wait |
bool |
|
type_hints |
typing.Optional[typing.Dict[str, typing.Type]] |
|
overwrite_cache |
typing.Optional[bool] |
|
interruptible |
typing.Optional[bool] |
|
envs |
typing.Optional[typing.Dict[str, str]] |
|
tags |
typing.Optional[typing.List[str]] |
|
cluster_pool |
typing.Optional[str] |
|
execution_cluster_label |
typing.Optional[str] |
execute_remote_wf()
def execute_remote_wf(
entity: FlyteWorkflow,
inputs: typing.Optional[typing.Dict[str, typing.Any]],
project: str,
domain: str,
execution_name: typing.Optional[str],
execution_name_prefix: typing.Optional[str],
options: typing.Optional[Options],
wait: bool,
type_hints: typing.Optional[typing.Dict[str, typing.Type]],
overwrite_cache: typing.Optional[bool],
interruptible: typing.Optional[bool],
envs: typing.Optional[typing.Dict[str, str]],
tags: typing.Optional[typing.List[str]],
cluster_pool: typing.Optional[str],
execution_cluster_label: typing.Optional[str],
) -> FlyteWorkflowExecutionExecute a FlyteWorkflow.
NOTE: the name and version arguments are currently not used and only there consistency in the function signature
| Parameter | Type | Description |
|---|---|---|
entity |
FlyteWorkflow |
|
inputs |
typing.Optional[typing.Dict[str, typing.Any]] |
|
project |
str |
|
domain |
str |
|
execution_name |
typing.Optional[str] |
|
execution_name_prefix |
typing.Optional[str] |
|
options |
typing.Optional[Options] |
|
wait |
bool |
|
type_hints |
typing.Optional[typing.Dict[str, typing.Type]] |
|
overwrite_cache |
typing.Optional[bool] |
|
interruptible |
typing.Optional[bool] |
|
envs |
typing.Optional[typing.Dict[str, str]] |
|
tags |
typing.Optional[typing.List[str]] |
|
cluster_pool |
typing.Optional[str] |
|
execution_cluster_label |
typing.Optional[str] |
fast_package()
def fast_package(
root: os.PathLike,
deref_symlinks: bool,
output: str,
options: typing.Optional[FastPackageOptions],
) -> typing.Tuple[bytes, str]Packages the given paths into an installable zip and returns the md5_bytes and the URL of the uploaded location
| Parameter | Type | Description |
|---|---|---|
root |
os.PathLike |
path to the root of the package system that should be uploaded |
deref_symlinks |
bool |
if symlinks should be dereferenced. Defaults to True |
output |
str |
output path. Optional, will default to a tempdir |
options |
typing.Optional[FastPackageOptions] |
additional options to customize fast_package behavior :return: md5_bytes, url |
fast_register_workflow()
def fast_register_workflow(
entity: WorkflowBase,
serialization_settings: typing.Optional[SerializationSettings],
version: typing.Optional[str],
default_launch_plan: typing.Optional[bool],
options: typing.Optional[Options],
fast_package_options: typing.Optional[FastPackageOptions],
) -> FlyteWorkflowUse this method to register a workflow with zip mode.
| Parameter | Type | Description |
|---|---|---|
entity |
WorkflowBase |
The workflow to be registered |
serialization_settings |
typing.Optional[SerializationSettings] |
The serialization settings to be used |
version |
typing.Optional[str] |
version for the entity to be registered as |
default_launch_plan |
typing.Optional[bool] |
This should be true if a default launch plan should be created for the workflow |
options |
typing.Optional[Options] |
Additional execution options that can be configured for the default launchplan |
fast_package_options |
typing.Optional[FastPackageOptions] |
Options to customize copying behavior :return: |
fetch_active_launchplan()
def fetch_active_launchplan(
project: str,
domain: str,
name: str,
) -> typing.Optional[FlyteLaunchPlan]Returns the active version of the launch plan if it exists or returns None
| Parameter | Type | Description |
|---|---|---|
project |
str |
|
domain |
str |
|
name |
str |
fetch_execution()
def fetch_execution(
project: str,
domain: str,
name: str,
) -> FlyteWorkflowExecutionFetch a workflow execution entity from flyte admin.
| Parameter | Type | Description |
|---|---|---|
project |
str |
fetch entity from this project. If None, uses the default_project attribute. |
domain |
str |
fetch entity from this domain. If None, uses the default_domain attribute. |
name |
str |
fetch entity with matching name. :returns: :class:~flytekit.remote.workflow_execution.FlyteWorkflowExecution :raises: FlyteAssertion if name is None |
fetch_launch_plan()
def fetch_launch_plan(
project: str,
domain: str,
name: str,
version: str,
) -> FlyteLaunchPlanFetch a launchplan entity from flyte admin.
| Parameter | Type | Description |
|---|---|---|
project |
str |
fetch entity from this project. If None, uses the default_project attribute. |
domain |
str |
fetch entity from this domain. If None, uses the default_domain attribute. |
name |
str |
fetch entity with matching name. |
version |
str |
fetch entity with matching version. If None, gets the latest version of the entity. :returns: :class:~flytekit.remote.launch_plan.FlyteLaunchPlan :raises: FlyteAssertion if name is None |
fetch_task()
def fetch_task(
project: str,
domain: str,
name: str,
version: str,
) -> FlyteTaskFetch a task entity from flyte admin.
| Parameter | Type | Description |
|---|---|---|
project |
str |
fetch entity from this project. If None, uses the default_project attribute. |
domain |
str |
fetch entity from this domain. If None, uses the default_domain attribute. |
name |
str |
fetch entity with matching name. |
version |
str |
fetch entity with matching version. If None, gets the latest version of the entity. :returns: :class:~flytekit.remote.tasks.task.FlyteTask :raises: FlyteAssertion if name is None |
fetch_task_lazy()
def fetch_task_lazy(
project: str,
domain: str,
name: str,
version: str,
) -> LazyEntitySimilar to fetch_task, just that it returns a LazyEntity, which will fetch the workflow lazily.
| Parameter | Type | Description |
|---|---|---|
project |
str |
|
domain |
str |
|
name |
str |
|
version |
str |
fetch_workflow()
def fetch_workflow(
project: str,
domain: str,
name: str,
version: str,
) -> FlyteWorkflowFetch a workflow entity from flyte admin.
| Parameter | Type | Description |
|---|---|---|
project |
str |
fetch entity from this project. If None, uses the default_project attribute. |
domain |
str |
fetch entity from this domain. If None, uses the default_domain attribute. |
name |
str |
fetch entity with matching name. |
version |
str |
fetch entity with matching version. If None, gets the latest version of the entity. :raises: FlyteAssertion if name is None |
fetch_workflow_lazy()
def fetch_workflow_lazy(
project: str,
domain: str,
name: str,
version: str,
) -> LazyEntity[FlyteWorkflow]Similar to fetch_workflow, just that it returns a LazyEntity, which will fetch the workflow lazily.
| Parameter | Type | Description |
|---|---|---|
project |
str |
|
domain |
str |
|
name |
str |
|
version |
str |
find_launch_plan()
def find_launch_plan(
lp_ref: id_models,
node_launch_plans: Dict[id_models, launch_plan_models.LaunchPlanSpec],
)| Parameter | Type | Description |
|---|---|---|
lp_ref |
id_models |
|
node_launch_plans |
Dict[id_models, launch_plan_models.LaunchPlanSpec] |
find_launch_plan_for_node()
def find_launch_plan_for_node(
node: Node,
node_launch_plans: Dict[id_models, launch_plan_models.LaunchPlanSpec],
)| Parameter | Type | Description |
|---|---|---|
node |
Node |
|
node_launch_plans |
Dict[id_models, launch_plan_models.LaunchPlanSpec] |
for_endpoint()
def for_endpoint(
endpoint: str,
insecure: bool,
data_config: typing.Optional[DataConfig],
config_file: typing.Union[str, ConfigFile],
default_project: typing.Optional[str],
default_domain: typing.Optional[str],
data_upload_location: str,
interactive_mode_enabled: bool,
kwargs,
) -> 'FlyteRemote'| Parameter | Type | Description |
|---|---|---|
endpoint |
str |
|
insecure |
bool |
|
data_config |
typing.Optional[DataConfig] |
|
config_file |
typing.Union[str, ConfigFile] |
|
default_project |
typing.Optional[str] |
|
default_domain |
typing.Optional[str] |
|
data_upload_location |
str |
|
interactive_mode_enabled |
bool |
|
kwargs |
**kwargs |
for_sandbox()
def for_sandbox(
default_project: typing.Optional[str],
default_domain: typing.Optional[str],
data_upload_location: str,
interactive_mode_enabled: bool,
kwargs,
) -> 'FlyteRemote'| Parameter | Type | Description |
|---|---|---|
default_project |
typing.Optional[str] |
|
default_domain |
typing.Optional[str] |
|
data_upload_location |
str |
|
interactive_mode_enabled |
bool |
|
kwargs |
**kwargs |
from_api_key()
def from_api_key(
api_key: str,
default_project: typing.Optional[str],
default_domain: typing.Optional[str],
data_upload_location: str,
kwargs,
) -> 'UnionRemote'Call this if you want to directly instantiate a UnionRemote from an API key
| Parameter | Type | Description |
|---|---|---|
api_key |
str |
|
default_project |
typing.Optional[str] |
|
default_domain |
typing.Optional[str] |
|
data_upload_location |
str |
|
kwargs |
**kwargs |
generate_console_http_domain()
def generate_console_http_domain()This should generate the domain where console is hosted.
:return:
generate_console_url()
def generate_console_url(
entity: typing.Union[FlyteWorkflowExecution, FlyteNodeExecution, FlyteTaskExecution, FlyteWorkflow, FlyteTask, FlyteLaunchPlan, Artifact],
)Generate a UnionAI console URL for the given Flyte remote endpoint. It will also handle Union AI specific entities like Artifacts.
This will automatically determine if this is an execution or an entity and change the type automatically.
| Parameter | Type | Description |
|---|---|---|
entity |
typing.Union[FlyteWorkflowExecution, FlyteNodeExecution, FlyteTaskExecution, FlyteWorkflow, FlyteTask, FlyteLaunchPlan, Artifact] |
get()
def get(
uri: typing.Optional[str],
) -> typing.Optional[typing.Union[LiteralsResolver, Literal, bytes]]General function that works with flyte tiny urls. This can return outputs (in the form of LiteralsResolver, or individual Literals for singular requests), or HTML if passed a deck link, or bytes containing HTML, if ipython is not available locally.
| Parameter | Type | Description |
|---|---|---|
uri |
typing.Optional[str] |
get_artifact()
def get_artifact(
uri: typing.Optional[str],
artifact_key: typing.Optional[art_id.ArtifactKey],
artifact_id: typing.Optional[art_id.ArtifactID],
query: typing.Optional[typing.Union[art_id.ArtifactQuery, ArtifactQuery]],
get_details: bool,
) -> typing.Optional[Artifact]Get the specified artifact.
| Parameter | Type | Description |
|---|---|---|
uri |
typing.Optional[str] |
An artifact URI. |
artifact_key |
typing.Optional[art_id.ArtifactKey] |
An artifact key. |
artifact_id |
typing.Optional[art_id.ArtifactID] |
The artifact ID. |
query |
typing.Optional[typing.Union[art_id.ArtifactQuery, ArtifactQuery]] |
An artifact query. |
get_details |
bool |
A bool to indicate whether or not to return artifact details. :return: The artifact as persisted in the service. |
get_domains()
def get_domains()Lists registered domains from flyte admin.
:returns: typing.List[flytekit.models.domain.Domain]
get_execution_metrics()
def get_execution_metrics(
id: WorkflowExecutionIdentifier,
depth: int,
) -> FlyteExecutionSpanGet the metrics for a given execution.
| Parameter | Type | Description |
|---|---|---|
id |
WorkflowExecutionIdentifier |
|
depth |
int |
get_extra_headers_for_protocol()
def get_extra_headers_for_protocol(
native_url,
)| Parameter | Type | Description |
|---|---|---|
native_url |
launch_backfill()
def launch_backfill(
project: str,
domain: str,
from_date: datetime,
to_date: datetime,
launchplan: str,
launchplan_version: str,
execution_name: str,
version: str,
dry_run: bool,
execute: bool,
parallel: bool,
failure_policy: typing.Optional[WorkflowFailurePolicy],
overwrite_cache: typing.Optional[bool],
) -> typing.Optional[FlyteWorkflowExecution, FlyteWorkflow, WorkflowBase]Creates and launches a backfill workflow for the given launchplan. If launchplan version is not specified, then the latest launchplan is retrieved. The from_date is exclusive and end_date is inclusive and backfill run for all instances in between. :: -> (start_date - exclusive, end_date inclusive)
If dry_run is specified, the workflow is created and returned. If execute==False is specified then the workflow is created and registered. In the last case, the workflow is created, registered and executed.
The parallel flag can be used to generate a workflow where all launchplans can be run in parallel. Default
is that execute backfill is run sequentially
| Parameter | Type | Description |
|---|---|---|
project |
str |
str project name |
domain |
str |
str domain name |
from_date |
datetime |
datetime generate a backfill starting at this datetime (exclusive) |
to_date |
datetime |
datetime generate a backfill ending at this datetime (inclusive) |
launchplan |
str |
str launchplan name in the flyte backend |
launchplan_version |
str |
str (optional) version for the launchplan. If not specified the most recent will be retrieved |
execution_name |
str |
str (optional) the generated execution will be named so. this can help in ensuring idempotency |
version |
str |
str (optional) version to be used for the newly created workflow. |
dry_run |
bool |
bool do not register or execute the workflow |
execute |
bool |
bool Register and execute the wwkflow. |
parallel |
bool |
if the backfill should be run in parallel. False (default) will run each bacfill sequentially. |
failure_policy |
typing.Optional[WorkflowFailurePolicy] |
WorkflowFailurePolicy (optional) to be used for the newly created workflow. This can control failure behavior - whether to continue on failure or stop immediately on failure |
overwrite_cache |
typing.Optional[bool] |
if True, will overwrite the cache. :return: In case of dry-run, return WorkflowBase, else if no_execute return FlyteWorkflow else in the default case return a FlyteWorkflowExecution |
list_projects()
def list_projects(
limit: typing.Optional[int],
filters: typing.Optional[typing.List[filter_models.Filter]],
sort_by: typing.Optional[admin_common_models.Sort],
) -> typing.List[Project]Lists registered projects from flyte admin.
| Parameter | Type | Description |
|---|---|---|
limit |
typing.Optional[int] |
[Optional[int]] The maximum number of entries to return. |
filters |
typing.Optional[typing.List[filter_models.Filter]] |
|
sort_by |
typing.Optional[admin_common_models.Sort] |
list_signals()
def list_signals(
execution_name: str,
project: typing.Optional[str],
domain: typing.Optional[str],
limit: int,
filters: typing.Optional[typing.List[filter_models.Filter]],
) -> typing.List[Signal]| Parameter | Type | Description |
|---|---|---|
execution_name |
str |
The name of the execution. This is the tailend of the URL when looking at the workflow execution. |
project |
typing.Optional[str] |
The execution project, will default to the Remote’s default project. |
domain |
typing.Optional[str] |
The execution domain, will default to the Remote’s default domain. |
limit |
int |
The number of signals to fetch |
filters |
typing.Optional[typing.List[filter_models.Filter]] |
Optional list of filters |
list_tasks_by_version()
def list_tasks_by_version(
version: str,
project: typing.Optional[str],
domain: typing.Optional[str],
limit: typing.Optional[int],
) -> typing.List[FlyteTask]| Parameter | Type | Description |
|---|---|---|
version |
str |
|
project |
typing.Optional[str] |
|
domain |
typing.Optional[str] |
|
limit |
typing.Optional[int] |
raw_register()
def raw_register(
cp_entity: FlyteControlPlaneEntity,
settings: SerializationSettings,
version: str,
create_default_launchplan: bool,
options: Options,
og_entity: FlyteLocalEntity,
) -> typing.Optional[Identifier]Raw register method, can be used to register control plane entities. Usually if you have a Flyte Entity like a WorkflowBase, Task, LaunchPlan then use other methods. This should be used only if you have already serialized entities
| Parameter | Type | Description |
|---|---|---|
cp_entity |
FlyteControlPlaneEntity |
The controlplane “serializable” version of a flyte entity. This is in the form that FlyteAdmin understands. |
settings |
SerializationSettings |
SerializationSettings to be used for registration - especially to identify the id |
version |
str |
Version to be registered |
create_default_launchplan |
bool |
boolean that indicates if a default launch plan should be created |
options |
Options |
Options to be used if registering a default launch plan |
og_entity |
FlyteLocalEntity |
Pass in the original workflow (flytekit type) if create_default_launchplan is true :return: Identifier of the created entity |
recent_executions()
def recent_executions(
project: typing.Optional[str],
domain: typing.Optional[str],
limit: typing.Optional[int],
filters: typing.Optional[typing.List[filter_models.Filter]],
) -> typing.List[FlyteWorkflowExecution]| Parameter | Type | Description |
|---|---|---|
project |
typing.Optional[str] |
|
domain |
typing.Optional[str] |
|
limit |
typing.Optional[int] |
|
filters |
typing.Optional[typing.List[filter_models.Filter]] |
register_launch_plan()
def register_launch_plan(
entity: LaunchPlan,
version: typing.Optional[str],
project: typing.Optional[str],
domain: typing.Optional[str],
options: typing.Optional[Options],
serialization_settings: typing.Optional[SerializationSettings],
) -> FlyteLaunchPlanRegister a given launchplan, possibly applying overrides from the provided options. If the underlying workflow is not already registered, it, along with any underlying entities, will also be registered. If the underlying workflow does exist (with the given project/domain/version), then only the launchplan will be registered.
| Parameter | Type | Description |
|---|---|---|
entity |
LaunchPlan |
Launchplan to be registered |
version |
typing.Optional[str] |
Version to be registered for the launch plan, and used to check (and register) underlying wf |
project |
typing.Optional[str] |
Optionally provide a project, if not already provided in flyteremote constructor or a separate one |
domain |
typing.Optional[str] |
Optionally provide a domain, if not already provided in FlyteRemote constructor or a separate one |
options |
typing.Optional[Options] |
|
serialization_settings |
typing.Optional[SerializationSettings] |
Optionally provide serialization settings, if not provided, will use the default |
register_script()
def register_script(
entity: typing.Union[WorkflowBase, PythonTask, LaunchPlan],
image_config: typing.Optional[ImageConfig],
version: typing.Optional[str],
project: typing.Optional[str],
domain: typing.Optional[str],
destination_dir: str,
copy_all: bool,
default_launch_plan: bool,
options: typing.Optional[Options],
source_path: typing.Optional[str],
module_name: typing.Optional[str],
envs: typing.Optional[typing.Dict[str, str]],
default_resources: typing.Optional[ResourceSpec],
fast_package_options: typing.Optional[FastPackageOptions],
) -> typing.Union[FlyteWorkflow, FlyteTask, FlyteLaunchPlan, ReferenceEntity]Use this method to register a workflow via script mode.
| Parameter | Type | Description |
|---|---|---|
entity |
typing.Union[WorkflowBase, PythonTask, LaunchPlan] |
The workflow to be registered or the task to be registered |
image_config |
typing.Optional[ImageConfig] |
The image config to use for the workflow. |
version |
typing.Optional[str] |
version for the entity to be registered as |
project |
typing.Optional[str] |
The project to register the workflow in. |
domain |
typing.Optional[str] |
The domain to register the workflow in. |
destination_dir |
str |
The destination directory where the workflow will be copied to. |
copy_all |
bool |
[deprecated] Please use the copy_style field in fast_package_options instead. |
default_launch_plan |
bool |
This should be true if a default launch plan should be created for the workflow |
options |
typing.Optional[Options] |
Additional execution options that can be configured for the default launchplan |
source_path |
typing.Optional[str] |
The root of the project path |
module_name |
typing.Optional[str] |
the name of the module |
envs |
typing.Optional[typing.Dict[str, str]] |
Environment variables to be passed to the serialization |
default_resources |
typing.Optional[ResourceSpec] |
Default resources to be passed to the serialization. These override the resource spec for any tasks that have no statically defined resource requests and limits. |
fast_package_options |
typing.Optional[FastPackageOptions] |
Options to customize copy_all behavior, ignored when copy_all is False. :return: |
register_task()
def register_task(
entity: PythonTask,
serialization_settings: typing.Optional[SerializationSettings],
version: typing.Optional[str],
) -> FlyteTaskRegister a qualified task (PythonTask) with Remote For any conflicting parameters method arguments are regarded as overrides
| Parameter | Type | Description |
|---|---|---|
entity |
PythonTask |
PythonTask can be either @task or a instance of a Task class |
serialization_settings |
typing.Optional[SerializationSettings] |
Settings that will be used to override various serialization parameters. |
version |
typing.Optional[str] |
version that will be used to register. If not specified will default to using the serialization settings default :return: |
register_workflow()
def register_workflow(
entity: WorkflowBase,
serialization_settings: typing.Optional[SerializationSettings],
version: typing.Optional[str],
default_launch_plan: typing.Optional[bool],
options: typing.Optional[Options],
) -> FlyteWorkflowUse this method to register a workflow.
| Parameter | Type | Description |
|---|---|---|
entity |
WorkflowBase |
The workflow to be registered |
serialization_settings |
typing.Optional[SerializationSettings] |
The serialization settings to be used |
version |
typing.Optional[str] |
version for the entity to be registered as |
default_launch_plan |
typing.Optional[bool] |
This should be true if a default launch plan should be created for the workflow |
options |
typing.Optional[Options] |
Additional execution options that can be configured for the default launchplan :return: |
reject()
def reject(
signal_id: str,
execution_name: str,
project: str,
domain: str,
)| Parameter | Type | Description |
|---|---|---|
signal_id |
str |
The name of the signal, this is the key used in the approve() or wait_for_input() call. |
execution_name |
str |
The name of the execution. This is the tail-end of the URL when looking at the workflow execution. |
project |
str |
The execution project, will default to the Remote’s default project. |
domain |
str |
The execution domain, will default to the Remote’s default domain. |
remote_context()
def remote_context()Context manager with remote-specific configuration.
search_artifacts()
def search_artifacts(
project: typing.Optional[str],
domain: typing.Optional[str],
name: typing.Optional[str],
artifact_key: typing.Optional[art_id.ArtifactKey],
query: typing.Optional[ArtifactQuery],
partitions: typing.Optional[Union[Partitions, typing.Dict[str, str]]],
time_partition: typing.Optional[Union[datetime.datetime, TimePartition]],
group_by_key: bool,
limit: int,
) -> typing.List[Artifact]| Parameter | Type | Description |
|---|---|---|
project |
typing.Optional[str] |
|
domain |
typing.Optional[str] |
|
name |
typing.Optional[str] |
|
artifact_key |
typing.Optional[art_id.ArtifactKey] |
|
query |
typing.Optional[ArtifactQuery] |
|
partitions |
typing.Optional[Union[Partitions, typing.Dict[str, str]]] |
|
time_partition |
typing.Optional[Union[datetime.datetime, TimePartition]] |
|
group_by_key |
bool |
|
limit |
int |
set_input()
def set_input(
signal_id: str,
execution_name: str,
value: typing.Union[literal_models.Literal, typing.Any],
project,
domain,
python_type,
literal_type,
)| Parameter | Type | Description |
|---|---|---|
signal_id |
str |
The name of the signal, this is the key used in the approve() or wait_for_input() call. |
execution_name |
str |
The name of the execution. This is the tail-end of the URL when looking at the workflow execution. |
value |
typing.Union[literal_models.Literal, typing.Any] |
This is either a Literal or a Python value which FlyteRemote will invoke the TypeEngine to convert into a Literal. This argument is only value for wait_for_input type signals. |
project |
The execution project, will default to the Remote’s default project. | |
domain |
The execution domain, will default to the Remote’s default domain. | |
python_type |
Provide a python type to help with conversion if the value you provided is not a Literal. | |
literal_type |
Provide a Flyte literal type to help with conversion if the value you provided is not a Literal |
set_signal()
def set_signal(
signal_id: str,
execution_name: str,
value: typing.Union[literal_models.Literal, typing.Any],
project: typing.Optional[str],
domain: typing.Optional[str],
python_type: typing.Optional[typing.Type],
literal_type: typing.Optional[type_models.LiteralType],
)| Parameter | Type | Description |
|---|---|---|
signal_id |
str |
The name of the signal, this is the key used in the approve() or wait_for_input() call. |
execution_name |
str |
The name of the execution. This is the tail-end of the URL when looking at the workflow execution. |
value |
typing.Union[literal_models.Literal, typing.Any] |
This is either a Literal or a Python value which FlyteRemote will invoke the TypeEngine to convert into a Literal. This argument is only value for wait_for_input type signals. |
project |
typing.Optional[str] |
The execution project, will default to the Remote’s default project. |
domain |
typing.Optional[str] |
The execution domain, will default to the Remote’s default domain. |
python_type |
typing.Optional[typing.Type] |
Provide a python type to help with conversion if the value you provided is not a Literal. |
literal_type |
typing.Optional[type_models.LiteralType] |
Provide a Flyte literal type to help with conversion if the value you provided is not a Literal |
stop_app()
def stop_app(
name: str,
project: Optional[str],
domain: Optional[str],
)Stop an application.
| Parameter | Type | Description |
|---|---|---|
name |
str |
Name of application to stop. |
project |
Optional[str] |
Domain name. If None, uses default_domain. :return: The App IDL for the stopped application. |
domain |
Optional[str] |
stream_execution_events()
def stream_execution_events(
event_count: Optional[int],
include_workflow_executions: bool,
include_task_executions: bool,
include_node_executions: bool,
) -> AsyncGenerator[Union[CloudEventWorkflowExecution, CloudEventNodeExecution, CloudEventTaskExecution], None]Stream execution events from the given tenant. This is a generator that yields events as they are received.
Events are guaranteed to be delivered at least once, and clients must implement handling for potentially out-of-order event processing. Events will be retransmitted until acknowledged, with acknowledgment occurring automatically upon normal return from the caller. Note: if an exception is raised during event processing, the acknowledgment will not occur, and the event will be redelivered in a subsequent transmission.
| Parameter | Type | Description |
|---|---|---|
event_count |
Optional[int] |
Number of events to receive before closing the stream. If None, receive unlimited events. |
include_workflow_executions |
bool |
Whether to include workflow execution events |
include_task_executions |
bool |
Whether to include task execution events |
include_node_executions |
bool |
Whether to include node execution events |
sync()
def sync(
execution: FlyteWorkflowExecution,
entity_definition: typing.Union[FlyteWorkflow, FlyteTask],
sync_nodes: bool,
) -> FlyteWorkflowExecutionThis function was previously a singledispatchmethod. We’ve removed that but this function remains so that we don’t break people.
| Parameter | Type | Description |
|---|---|---|
execution |
FlyteWorkflowExecution |
|
entity_definition |
typing.Union[FlyteWorkflow, FlyteTask] |
|
sync_nodes |
bool |
By default sync will fetch data on all underlying node executions (recursively, so subworkflows and launch plans will also get picked up). Set this to False in order to prevent that (which will make this call faster). :return: Returns the same execution object, but with additional information pulled in. |
sync_execution()
def sync_execution(
execution: FlyteWorkflowExecution,
entity_definition: typing.Union[FlyteWorkflow, FlyteTask],
sync_nodes: bool,
) -> FlyteWorkflowExecutionSync a FlyteWorkflowExecution object with its corresponding remote state.
| Parameter | Type | Description |
|---|---|---|
execution |
FlyteWorkflowExecution |
|
entity_definition |
typing.Union[FlyteWorkflow, FlyteTask] |
|
sync_nodes |
bool |
sync_node_execution()
def sync_node_execution(
execution: FlyteNodeExecution,
node_mapping: typing.Dict[str, FlyteNode],
) -> FlyteNodeExecutionGet data backing a node execution. These FlyteNodeExecution objects should’ve come from Admin with the model fields already populated correctly. For purposes of the remote experience, we’d like to supplement the object with some additional fields:
- inputs/outputs
- task/workflow executions, and/or underlying node executions in the case of parent nodes
- TypedInterface (remote wrapper type)
A node can have several different types of executions behind it. That is, the node could’ve run (perhaps multiple times because of retries):
- A task
- A static subworkflow
- A dynamic subworkflow (which in turn may have run additional tasks, subwfs, and/or launch plans)
- A launch plan
The data model is complicated, so ascertaining which of these happened is a bit tricky. That logic is encapsulated in this function.
| Parameter | Type | Description |
|---|---|---|
execution |
FlyteNodeExecution |
|
node_mapping |
typing.Dict[str, FlyteNode] |
sync_task_execution()
def sync_task_execution(
execution: FlyteTaskExecution,
entity_interface: typing.Optional[TypedInterface],
get_task_exec_data: bool,
) -> FlyteTaskExecutionSync a FlyteTaskExecution object with its corresponding remote state.
| Parameter | Type | Description |
|---|---|---|
execution |
FlyteTaskExecution |
|
entity_interface |
typing.Optional[TypedInterface] |
|
get_task_exec_data |
bool |
terminate()
def terminate(
execution: FlyteWorkflowExecution,
cause: str,
)Terminate a workflow execution.
| Parameter | Type | Description |
|---|---|---|
execution |
FlyteWorkflowExecution |
workflow execution to terminate |
cause |
str |
reason for termination |
upload_file()
def upload_file(
to_upload: pathlib.Path,
project: typing.Optional[str],
domain: typing.Optional[str],
filename_root: typing.Optional[str],
) -> typing.Tuple[bytes, str]Function will use remote’s client to hash and then upload the file using Admin’s data proxy service.
| Parameter | Type | Description |
|---|---|---|
to_upload |
pathlib.Path |
Must be a single file |
project |
typing.Optional[str] |
Project to upload under, if not supplied will use the remote’s default |
domain |
typing.Optional[str] |
Domain to upload under, if not specified will use the remote’s default |
filename_root |
typing.Optional[str] |
If provided will be used as the root of the filename. If not, Admin will use a hash :return: The uploaded location. |
wait()
def wait(
execution: FlyteWorkflowExecution,
timeout: typing.Optional[typing.Union[timedelta, int]],
poll_interval: typing.Optional[typing.Union[timedelta, int]],
sync_nodes: bool,
) -> FlyteWorkflowExecutionWait for an execution to finish.
| Parameter | Type | Description |
|---|---|---|
execution |
FlyteWorkflowExecution |
execution object to wait on |
timeout |
typing.Optional[typing.Union[timedelta, int]] |
maximum amount of time to wait. It can be a timedelta or a duration in seconds as int. |
poll_interval |
typing.Optional[typing.Union[timedelta, int]] |
sync workflow execution at this interval. It can be a timedelta or a duration in seconds as int. |
sync_nodes |
bool |
passed along to the sync call for the workflow execution |
Properties
| Property | Type | Description |
|---|---|---|
apps_service_client |
||
artifacts_client |
||
authorizer_service_client |
||
client |
Return a SynchronousFlyteClient for additional operations. |
|
config |
Image config. |
|
context |
||
default_domain |
Default project to use when fetching or executing flyte entities. |
|
default_project |
Default project to use when fetching or executing flyte entities. |
|
file_access |
File access provider to use for offloading non-literal inputs/outputs. |
|
hooks_async_client |
||
hooks_sync_client |
||
images_client |
||
interactive_mode_enabled |
If set to True, the FlyteRemote will pickle the task/workflow. |
|
secret_client |
||
sync_channel |
Return channel from client. This channel already has the org passed in dynamically by the interceptor. |
|
user_service_client |
||
users_client |
union.remote.VLLMShardArgs
class VLLMShardArgs(
model: str,
tensor_parallel_size: int,
trust_remote_code: bool,
revision: str | None,
file_pattern: str | None,
max_file_size: int | None,
gpu_memory_utilization: float,
extra_args: dict[str, typing.Any],
)| Parameter | Type | Description |
|---|---|---|
model |
str |
|
tensor_parallel_size |
int |
|
trust_remote_code |
bool |
|
revision |
str | None |
|
file_pattern |
str | None |
|
max_file_size |
int | None |
|
gpu_memory_utilization |
float |
|
extra_args |
dict[str, typing.Any] |
Methods
| Method | Description |
|---|---|
get_vllm_args() |
get_vllm_args()
def get_vllm_args(
model_path: str,
)| Parameter | Type | Description |
|---|---|---|
model_path |
str |