def get_registrable_entities(
ctx: flyte_context.FlyteContext,
options: typing.Optional[Options] = None
) -> typing.List[RegistrableEntity]:
"""
Returns all entities that can be serialized and should be sent over to Flyte backend. This will filter any entities
that are not known to Admin
"""
new_api_serializable_entities = OrderedDict()
# TODO: Clean up the copy() - it's here because we call get_default_launch_plan, which may create a LaunchPlan
# object, which gets added to the FlyteEntities.entities list, which we're iterating over.
for entity in flyte_context.FlyteEntities.entities.copy():
if isinstance(entity, PythonTask) or isinstance(
entity, WorkflowBase) or isinstance(entity, LaunchPlan):
get_serializable(new_api_serializable_entities,
ctx.serialization_settings,
entity,
options=options)
if isinstance(entity, WorkflowBase):
lp = LaunchPlan.get_default_launch_plan(ctx, entity)
get_serializable(new_api_serializable_entities,
ctx.serialization_settings, lp, options)
new_api_model_values = list(new_api_serializable_entities.values())
entities_to_be_serialized = list(
filter(_should_register_with_admin, new_api_model_values))
serializable_tasks: typing.List[task_models.TaskSpec] = [
entity for entity in entities_to_be_serialized
if isinstance(entity, task_models.TaskSpec)
]
# Detect if any of the tasks is duplicated. Duplicate tasks are defined as having the same
# metadata identifiers (see :py:class:`flytekit.common.core.identifier.Identifier`). Duplicate
# tasks are considered invalid at registration
# time and usually indicate user error, so we catch this common mistake at serialization time.
duplicate_tasks = _find_duplicate_tasks(serializable_tasks)
if len(duplicate_tasks) > 0:
duplicate_task_names = [
task.template.id.name for task in duplicate_tasks
]
raise FlyteValidationException(
f"Multiple definitions of the following tasks were found: {duplicate_task_names}"
)
return [v.to_flyte_idl() for v in entities_to_be_serialized]
y=alt.Y('new_cases_smoothed_per_million:Q', stack=None),
color=alt.Color('continent:N', scale=alt.Scale(scheme='set1')),
tooltip='continent:N').interactive().properties(width='container')
dp.Report(dp.Plot(plot), dp.DataTable(df)).save(path='report.html',open=True)
@task
def transform_data(url: str) -> pandas.DataFrame:
dataset = pd.read_csv(url)
df = dataset.groupby(
['continent',
'date'])['new_cases_smoothed_per_million'].mean().reset_index()
return df
@workflow
def datapane_workflow(url: str):
df = transform_data(url=url)
publish_report(df=df)
print(f"Report is published for {url}")
default_lp = LaunchPlan.get_default_launch_plan(
current_context(),
datapane_workflow)
if __name__ == "__main__":
print(default_lp(url="https://covid.ourworldindata.org/data/owid-covid-data.csv"))
from flytekit import task, LaunchPlan, workflow, current_context
@task
def square(val: int) -> int:
return val * val
@workflow
def my_wf(val: int) -> int:
result = square(val=val)
return result
default_lp = LaunchPlan.get_default_launch_plan(current_context(), my_wf)
square_3 = default_lp(val=3)
# %%
# The following shows how to specify a user-defined launch plan that defaults the value of 'val' to 4.
my_lp = LaunchPlan.create("default_4_lp", my_wf, default_inputs={"val": 4})
square_4 = my_lp()
square_5 = my_lp(val=5)
# %%
# In some cases you may want to **fix** launch plan inputs, such that they can't be overridden at execution call time.
my_fixed_lp = LaunchPlan.create("always_2_lp", my_wf, fixed_inputs={"val": 4})
square_2 = my_fixed_lp()
# error:
# square_1 = my_fixed_lp(val=1)