def test_map_tasks_only():
@workflow
def wf1(a: int):
print(f"{a}")
with pytest.raises(ValueError):
@workflow
def wf2(a: typing.List[int]):
return map_task(wf1)(a=a)
lp = LaunchPlan.create("test", wf1)
with pytest.raises(ValueError):
@workflow
def wf3(a: typing.List[int]):
return map_task(lp)(a=a)
print(formatted_kickoff_time)
# %%
# Cron Expression
# ---------------
# Cron expression strings use the `AWS syntax <http://docs.aws.amazon.com/AmazonCloudWatch/latest/events/ScheduledEvents.html#CronExpressions>`_.
# These are validated at launch plan registration time.
from flytekit import CronSchedule, LaunchPlan
# creates a launch plan that runs at 10am UTC every day.
cron_lp = LaunchPlan.create(
"my_cron_scheduled_lp",
date_formatter_wf,
schedule=CronSchedule(
# Note that kickoff_time_input_arg matches the workflow input we defined above: kickoff_time
cron_expression="0 10 * * ? *",
kickoff_time_input_arg="kickoff_time",
),
)
# %%
# Fixed Rate
# ----------
# If you prefer to use an interval rather than the cron syntax to schedule your workflows, this is currently supported
# for Flyte deployments hosted on AWS.
# To run ``date_formatter_wf`` every 10 minutes read on below:
from datetime import timedelta
from flytekit import FixedRate, LaunchPlan
return str(a * 2)
@workflow
def int_doubler_wf(a: int) -> str:
doubled = double_int_and_print(a=a)
return doubled
# This launch plan triggers email notifications when the workflow execution it triggered reaches the phase `SUCCEEDED`.
int_doubler_wf_lp = LaunchPlan.create(
"int_doubler_wf",
int_doubler_wf,
default_inputs={"a": 4},
notifications=[
Email(
phases=[WorkflowExecutionPhase.SUCCEEDED],
recipients_email=["*****@*****.**"],
)
],
)
# %%
# Notifications shine when used for scheduled workflows to alert on failures:
from datetime import timedelta
from flytekit import FixedRate, PagerDuty
int_doubler_wf_scheduled_lp = LaunchPlan.create(
"int_doubler_wf_scheduled",
int_doubler_wf,
from datetime import datetime
from flytekit import LaunchPlan, task, workflow
from flytekit.models.common import AuthRole
@task
def print_hello_world() -> str:
print("Hello, World")
return "Hello"
@workflow
def hello_world(
styx_parameter: datetime,
styx_execution_id: str,
styx_trigger_id: str,
styx_trigger_type: str,
styx_workflow_id: str
) -> str:
hello = print_hello_world()
return hello
lp = LaunchPlan.create("morning_greeting", hello_world, auth_role=AuthRole(kubernetes_service_account="e2e-test-sa"))
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)
# %%
# Putting it all together
# #######################
#
# Default and fixed inputs can all be used in combination together to simplify individual executions