def test_dynamic_pod_task():
dynamic_pod = Pod(pod_spec=get_pod_spec(), primary_container_name="a container")
@task
def t1(a: int) -> int:
return a + 10
@dynamic(
task_config=dynamic_pod, requests=Resources(cpu="10"), limits=Resources(gpu="2"), environment={"FOO": "bar"}
)
def dynamic_pod_task(a: int) -> List[int]:
s = []
for i in range(a):
s.append(t1(a=i))
return s
assert isinstance(dynamic_pod_task, PodFunctionTask)
default_img = Image(name="default", fqn="test", tag="tag")
custom = dynamic_pod_task.get_custom(
SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img, images=[default_img]),
)
)
assert len(custom["podSpec"]["containers"]) == 2
primary_container = custom["podSpec"]["containers"][0]
assert isinstance(dynamic_pod_task.task_config, Pod)
assert primary_container["resources"] == {
"requests": {"cpu": {"string": "10"}},
"limits": {"gpu": {"string": "2"}},
}
with context_manager.FlyteContext.current_context().new_serialization_settings(
serialization_settings=SerializationSettings(
project="test_proj",
domain="test_domain",
version="abc",
image_config=ImageConfig(Image(name="name", fqn="image", tag="name")),
env={},
)
) as ctx:
with ctx.new_execution_context(mode=ExecutionState.Mode.TASK_EXECUTION) as ctx:
dynamic_job_spec = dynamic_pod_task.compile_into_workflow(ctx, dynamic_pod_task._task_function, a=5)
assert len(dynamic_job_spec._nodes) == 5
def test_pod_task():
pod = Pod(pod_spec=get_pod_spec(), primary_container_name="a container")
@task(task_config=pod,
requests=Resources(cpu="10"),
limits=Resources(gpu="2"),
environment={"FOO": "bar"})
def simple_pod_task(i: int):
pass
assert isinstance(simple_pod_task, PodFunctionTask)
assert simple_pod_task.task_config == pod
default_img = Image(name="default", fqn="test", tag="tag")
custom = simple_pod_task.get_custom(
SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
))
assert custom["podSpec"]["restartPolicy"] == "OnFailure"
assert len(custom["podSpec"]["containers"]) == 2
primary_container = custom["podSpec"]["containers"][0]
assert primary_container["name"] == "a container"
assert primary_container["args"] == [
"pyflyte-execute",
"--task-module",
"pod.test_pod",
"--task-name",
"simple_pod_task",
"--inputs",
"{{.input}}",
"--output-prefix",
"{{.outputPrefix}}",
"--raw-output-data-prefix",
"{{.rawOutputDataPrefix}}",
]
assert primary_container["volumeMounts"] == [{
"mountPath": "some/where",
"name": "volume mount"
}]
assert primary_container["resources"] == {
"requests": {
"cpu": {
"string": "10"
}
},
"limits": {
"gpu": {
"string": "2"
}
},
}
assert primary_container["env"] == [{"name": "FOO", "value": "bar"}]
assert custom["podSpec"]["containers"][1]["name"] == "another container"
assert custom["primaryContainerName"] == "a container"
def test_pod_task_serialized():
pod = Pod(pod_spec=get_pod_spec(),
primary_container_name="an undefined container")
@task(task_config=pod,
requests=Resources(cpu="10"),
limits=Resources(gpu="2"),
environment={"FOO": "bar"})
def simple_pod_task(i: int):
pass
assert isinstance(simple_pod_task, PodFunctionTask)
assert simple_pod_task.task_config == pod
default_img = Image(name="default", fqn="test", tag="tag")
ssettings = SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
)
serialized = get_serializable(OrderedDict(), ssettings, simple_pod_task)
assert serialized.task_type_version == 1
assert serialized.config[
"primary_container_name"] == "an undefined container"
def test_query_no_inputs_or_outputs():
hive_task = HiveTask(
name="flytekit.demo.hive_task.hivequery1",
inputs={},
task_config=HiveConfig(cluster_label="flyte"),
query_template="""
insert into extant_table (1, 'two')
""",
output_schema_type=None,
)
@workflow
def my_wf():
hive_task()
default_img = Image(name="default", fqn="test", tag="tag")
serialization_settings = SerializationSettings(
project="proj",
domain="dom",
version="123",
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
env={},
)
sdk_task = get_serializable(serialization_settings, hive_task)
assert len(sdk_task.interface.inputs) == 0
assert len(sdk_task.interface.outputs) == 0
get_serializable(serialization_settings, my_wf)
def test_tensorflow_task():
@task(
task_config=TfJob(num_workers=10,
per_replica_requests=Resources(cpu="1"),
num_ps_replicas=1,
num_chief_replicas=1),
cache=True,
cache_version="1",
)
def my_tensorflow_task(x: int, y: str) -> int:
return x
assert my_tensorflow_task(x=10, y="hello") == 10
assert my_tensorflow_task.task_config is not None
default_img = Image(name="default", fqn="test", tag="tag")
settings = SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
)
assert my_tensorflow_task.get_custom(settings) == {
"workers": 10,
"psReplicas": 1,
"chiefReplicas": 1
}
assert my_tensorflow_task.resources.limits == Resources()
assert my_tensorflow_task.resources.requests == Resources(cpu="1")
assert my_tensorflow_task.task_type == "tensorflow"
def test_spark_task():
@task(task_config=Spark(spark_conf={"spark": "1"}))
def my_spark(a: str) -> int:
session = flytekit.current_context().spark_session
assert session.sparkContext.appName == "FlyteSpark: ex:local:local:local"
return 10
assert my_spark.task_config is not None
assert my_spark.task_config.spark_conf == {"spark": "1"}
default_img = Image(name="default", fqn="test", tag="tag")
settings = SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
)
retrieved_settings = my_spark.get_custom(settings)
assert retrieved_settings["sparkConf"] == {"spark": "1"}
pb = ExecutionParameters.new_builder()
pb.working_dir = "/tmp"
pb.execution_id = "ex:local:local:local"
p = pb.build()
new_p = my_spark.pre_execute(p)
assert new_p is not None
assert new_p.has_attr("SPARK_SESSION")
assert my_spark.sess is not None
configs = my_spark.sess.sparkContext.getConf().getAll()
assert ("spark", "1") in configs
assert ("spark.app.name", "FlyteSpark: ex:local:local:local") in configs
def test_serialization():
athena_task = AthenaTask(
name="flytekit.demo.athena_task.query",
inputs=kwtypes(ds=str),
task_config=AthenaConfig(database="mnist",
catalog="my_catalog",
workgroup="my_wg"),
query_template="""
insert overwrite directory '{{ .rawOutputDataPrefix }}' stored as parquet
select *
from blah
where ds = '{{ .Inputs.ds }}'
""",
# the schema literal's backend uri will be equal to the value of .raw_output_data
output_schema_type=FlyteSchema,
)
@workflow
def my_wf(ds: str) -> FlyteSchema:
return athena_task(ds=ds)
default_img = Image(name="default", fqn="test", tag="tag")
serialization_settings = SerializationSettings(
project="proj",
domain="dom",
version="123",
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
env={},
)
task_spec = get_serializable(OrderedDict(), serialization_settings,
athena_task)
assert "{{ .rawOutputDataPrefix" in task_spec.template.custom["statement"]
assert "insert overwrite directory" in task_spec.template.custom[
"statement"]
assert "mnist" == task_spec.template.custom["schema"]
assert "my_catalog" == task_spec.template.custom["catalog"]
assert "my_wg" == task_spec.template.custom["routingGroup"]
assert len(task_spec.template.interface.inputs) == 1
assert len(task_spec.template.interface.outputs) == 1
admin_workflow_spec = get_serializable(OrderedDict(),
serialization_settings, my_wf)
assert admin_workflow_spec.template.interface.outputs[
"o0"].type.schema is not None
assert admin_workflow_spec.template.outputs[0].var == "o0"
assert admin_workflow_spec.template.outputs[
0].binding.promise.node_id == "n0"
assert admin_workflow_spec.template.outputs[
0].binding.promise.var == "results"
def test_serialization():
hive_task = HiveTask(
name="flytekit.demo.hive_task.hivequery1",
inputs=kwtypes(my_schema=FlyteSchema, ds=str),
config=HiveConfig(cluster_label="flyte"),
query_template="""
set engine=tez;
insert overwrite directory '{{ .rawOutputDataPrefix }}' stored as parquet -- will be unique per retry
select *
from blah
where ds = '{{ .Inputs.ds }}' and uri = '{{ .inputs.my_schema }}'
""",
# the schema literal's backend uri will be equal to the value of .raw_output_data
output_schema_type=FlyteSchema,
)
@workflow
def my_wf(in_schema: FlyteSchema, ds: str) -> FlyteSchema:
return hive_task(my_schema=in_schema, ds=ds)
default_img = Image(name="default", fqn="test", tag="tag")
serialization_settings = SerializationSettings(
project="proj",
domain="dom",
version="123",
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
env={},
)
task_spec = get_serializable(OrderedDict(), serialization_settings,
hive_task)
assert "{{ .rawOutputDataPrefix" in task_spec.template.custom["query"][
"query"]
assert "insert overwrite directory" in task_spec.template.custom["query"][
"query"]
assert len(task_spec.template.interface.inputs) == 2
assert len(task_spec.template.interface.outputs) == 1
admin_workflow_spec = get_serializable(OrderedDict(),
serialization_settings, my_wf)
assert admin_workflow_spec.template.interface.outputs[
"o0"].type.schema is not None
assert admin_workflow_spec.template.outputs[0].var == "o0"
assert admin_workflow_spec.template.outputs[
0].binding.promise.node_id == "n0"
assert admin_workflow_spec.template.outputs[
0].binding.promise.var == "results"
def test_fast_pod_task_serialization():
pod = Pod(
pod_spec=V1PodSpec(restart_policy="OnFailure",
containers=[V1Container(name="primary")]),
primary_container_name="primary",
)
@task(task_config=pod, environment={"FOO": "bar"})
def simple_pod_task(i: int):
pass
default_img = Image(name="default", fqn="test", tag="tag")
serialization_settings = SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
fast_serialization_settings=FastSerializationSettings(enabled=True),
)
serialized = get_serializable(OrderedDict(), serialization_settings,
simple_pod_task)
assert serialized.template.k8s_pod.pod_spec["containers"][0]["args"] == [
"pyflyte-fast-execute",
"--additional-distribution",
"{{ .remote_package_path }}",
"--dest-dir",
"{{ .dest_dir }}",
"--",
"pyflyte-execute",
"--inputs",
"{{.input}}",
"--output-prefix",
"{{.outputPrefix}}",
"--raw-output-data-prefix",
"{{.rawOutputDataPrefix}}",
"--resolver",
"flytekit.core.python_auto_container.default_task_resolver",
"--",
"task-module",
"plugins.tests.pod.test_pod",
"task-name",
"simple_pod_task",
]
def test_map_pod_task_serialization():
pod = Pod(
pod_spec=V1PodSpec(restart_policy="OnFailure",
containers=[V1Container(name="primary")]),
primary_container_name="primary",
)
@task(task_config=pod, environment={"FOO": "bar"})
def simple_pod_task(i: int):
pass
mapped_task = map_task(simple_pod_task, metadata=TaskMetadata(retries=1))
default_img = Image(name="default", fqn="test", tag="tag")
serialization_settings = SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
)
# Test that target is correctly serialized with an updated command
pod_spec = mapped_task.get_k8s_pod(serialization_settings).pod_spec
assert len(pod_spec["containers"]) == 1
assert pod_spec["containers"][0]["args"] == [
"pyflyte-map-execute",
"--inputs",
"{{.input}}",
"--output-prefix",
"{{.outputPrefix}}",
"--raw-output-data-prefix",
"{{.rawOutputDataPrefix}}",
"--resolver",
"flytekit.core.python_auto_container.default_task_resolver",
"--",
"task-module",
"plugins.tests.pod.test_pod",
"task-name",
"simple_pod_task",
]
assert {
"primary_container_name": "primary"
} == mapped_task.get_config(serialization_settings)
def test_pod_task_undefined_primary():
pod = Pod(pod_spec=get_pod_spec(),
primary_container_name="an undefined container")
@task(task_config=pod,
requests=Resources(cpu="10"),
limits=Resources(gpu="2"),
environment={"FOO": "bar"})
def simple_pod_task(i: int):
pass
assert isinstance(simple_pod_task, PodFunctionTask)
assert simple_pod_task.task_config == pod
default_img = Image(name="default", fqn="test", tag="tag")
custom = simple_pod_task.get_custom(
SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
))
assert len(custom["containers"]) == 3
primary_container = custom["containers"][2]
assert primary_container["name"] == "an undefined container"
config = simple_pod_task.get_config(
SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
))
assert config["primary_container_name"] == "an undefined container"
def test_spark_task():
@task(task_config=Spark(spark_conf={"spark": "1"}))
def my_spark(a: str) -> int:
session = flytekit.current_context().spark_session
assert session.sparkContext.appName == "FlyteSpark: ex:local:local:local"
return 10
assert my_spark.task_config is not None
assert my_spark.task_config.spark_conf == {"spark": "1"}
default_img = Image(name="default", fqn="test", tag="tag")
settings = SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
)
retrieved_settings = my_spark.get_custom(settings)
assert retrieved_settings["sparkConf"] == {"spark": "1"}
def test_pod_task_deserialization():
pod = Pod(pod_spec=get_pod_spec(), primary_container_name="a container")
@task(task_config=pod,
requests=Resources(cpu="10"),
limits=Resources(gpu="2"),
environment={"FOO": "bar"})
def simple_pod_task(i: int):
pass
assert isinstance(simple_pod_task, PodFunctionTask)
assert simple_pod_task.task_config == pod
default_img = Image(name="default", fqn="test", tag="tag")
custom = simple_pod_task.get_custom(
SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
))
# Test that custom is correctly serialized by deserializing it with the python API client
response = MagicMock()
response.data = json.dumps(custom)
deserialized_pod_spec = ApiClient().deserialize(response, V1PodSpec)
assert deserialized_pod_spec.restart_policy == "OnFailure"
assert len(deserialized_pod_spec.containers) == 2
primary_container = deserialized_pod_spec.containers[0]
assert primary_container.name == "a container"
assert primary_container.args == [
"pyflyte-execute",
"--inputs",
"{{.input}}",
"--output-prefix",
"{{.outputPrefix}}",
"--raw-output-data-prefix",
"{{.rawOutputDataPrefix}}",
"--resolver",
"flytekit.core.python_auto_container.default_task_resolver",
"--",
"task-module",
"plugins.tests.pod.test_pod",
"task-name",
"simple_pod_task",
]
assert primary_container.volume_mounts[0].mount_path == "some/where"
assert primary_container.volume_mounts[0].name == "volume mount"
assert primary_container.resources == V1ResourceRequirements(
limits={"gpu": "2"}, requests={"cpu": "10"})
assert primary_container.env == [V1EnvVar(name="FOO", value="bar")]
assert deserialized_pod_spec.containers[1].name == "another container"
config = simple_pod_task.get_config(
SerializationSettings(
project="project",
domain="domain",
version="version",
env={"FOO": "baz"},
image_config=ImageConfig(default_image=default_img,
images=[default_img]),
))
assert config["primary_container_name"] == "a container"
