def notebook_pipeline():
"""A pipeline to run a Jupyter notebook with elyra-ai/kfp-notebook and Papermill."""
from elyra.kfp.operator import ExecuteFileOp as NotebookOp
notebook_op = NotebookOp(name="${name}",
pipeline_name="${name}",
experiment_name="NOTEBOOK_RUNS",
notebook="${notebook}",
cos_endpoint="${cos_endpoint}",
cos_bucket="${cos_bucket}",
cos_directory="${cos_directory}",
cos_dependencies_archive="${cos_dependencies_archive}",
requirements_url="${requirements_url}",
image="${image}")
from kubernetes.client.models import V1EnvVar
notebook_op.container.add_env_variable(V1EnvVar(name='AWS_ACCESS_KEY_ID', value="${cos_username}"))
notebook_op.container.add_env_variable(V1EnvVar(name='AWS_SECRET_ACCESS_KEY', value="${cos_password}"))
from kfp import onprem
notebook_op.container.add_env_variable(V1EnvVar(name='DATA_DIR', value="${mount_path}"))
notebook_op.apply(onprem.mount_pvc(pvc_name='${dataset_pvc}',
volume_name='${dataset_pvc}',
volume_mount_path='${mount_path}'))
def test_construct_with_both_pipeline_inputs_and_outputs():
notebook_op = ExecuteFileOp(
name="test",
pipeline_name="test-pipeline",
experiment_name="experiment-name",
notebook="test_notebook.ipynb",
cos_endpoint="http://testserver:32525",
cos_bucket="test_bucket",
cos_directory="test_directory",
cos_dependencies_archive="test_archive.tgz",
pipeline_inputs=["test_input1.txt", "test_input2.txt"],
pipeline_outputs=["test_output1.txt", "test_output2.txt"],
image="test/image:dev",
)
assert notebook_op.pipeline_inputs == [
"test_input1.txt", "test_input2.txt"
]
assert notebook_op.pipeline_outputs == [
"test_output1.txt", "test_output2.txt"
]
assert '--inputs "test_input1.txt;test_input2.txt"' in notebook_op.container.args[
0]
assert '--outputs "test_output1.txt;test_output2.txt"' in notebook_op.container.args[
0]
def test_fail_without_notebook():
with pytest.raises(TypeError):
ExecuteFileOp(
name="test",
pipeline_name="test-pipeline",
experiment_name="experiment-name",
cos_endpoint="http://testserver:32525",
cos_bucket="test_bucket",
cos_directory="test_directory",
cos_dependencies_archive="test_archive.tgz",
image="test/image:dev",
)
def test_fail_without_runtime_image():
with pytest.raises(ValueError) as error_info:
ExecuteFileOp(
name="test",
pipeline_name="test-pipeline",
experiment_name="experiment-name",
notebook="test_notebook.ipynb",
cos_endpoint="http://testserver:32525",
cos_bucket="test_bucket",
cos_directory="test_directory",
cos_dependencies_archive="test_archive.tgz",
)
assert "You need to provide an image." == str(error_info.value)
def test_properly_set_python_script_name_when_in_subdirectory():
notebook_op = ExecuteFileOp(
name="test",
pipeline_name="test-pipeline",
experiment_name="experiment-name",
notebook="foo/test.py",
cos_endpoint="http://testserver:32525",
cos_bucket="test_bucket",
cos_directory="test_directory",
cos_dependencies_archive="test_archive.tgz",
image="test/image:dev",
)
assert "test.py" == notebook_op.notebook_name
def test_fail_with_empty_string_as_name():
with pytest.raises(ValueError):
ExecuteFileOp(
name="",
pipeline_name="test-pipeline",
experiment_name="experiment-name",
notebook="test_notebook.ipynb",
cos_endpoint="http://testserver:32525",
cos_bucket="test_bucket",
cos_directory="test_directory",
cos_dependencies_archive="test_archive.tgz",
image="test/image:dev",
)
def test_override_requirements_url():
notebook_op = ExecuteFileOp(
name="test",
pipeline_name="test-pipeline",
experiment_name="experiment-name",
requirements_url="https://test.server.com/requirements.py",
notebook="test_notebook.ipynb",
cos_endpoint="http://testserver:32525",
cos_bucket="test_bucket",
cos_directory="test_directory",
cos_dependencies_archive="test_archive.tgz",
image="test/image:dev",
)
assert notebook_op.requirements_url == "https://test.server.com/requirements.py"
def test_construct_with_bad_pipeline_outputs():
with pytest.raises(ValueError) as error_info:
ExecuteFileOp(
name="test",
pipeline_name="test-pipeline",
experiment_name="experiment-name",
notebook="test_notebook.ipynb",
cos_endpoint="http://testserver:32525",
cos_bucket="test_bucket",
cos_directory="test_directory",
cos_dependencies_archive="test_archive.tgz",
pipeline_outputs=["test_output1.txt", "test;output2.txt"],
image="test/image:dev",
)
assert "Illegal character (;) found in filename 'test;output2.txt'." == str(
error_info.value)
def test_user_crio_volume_creation():
notebook_op = ExecuteFileOp(
name="test",
pipeline_name="test-pipeline",
experiment_name="experiment-name",
notebook="test_notebook.ipynb",
cos_endpoint="http://testserver:32525",
cos_bucket="test_bucket",
cos_directory="test_directory",
cos_dependencies_archive="test_archive.tgz",
image="test/image:dev",
emptydir_volume_size="20Gi",
)
assert notebook_op.emptydir_volume_size == "20Gi"
assert notebook_op.container_work_dir_root_path == "/opt/app-root/src/"
assert notebook_op.container.volume_mounts.__len__() == 1
# Environment variables: PYTHONPATH, ELYRA_RUN_NAME
assert notebook_op.container.env.__len__() == 2, notebook_op.container.env
def test_construct_with_env_variables_tekton():
notebook_op = ExecuteFileOp(
name="test",
pipeline_name="test-pipeline",
experiment_name="experiment-name",
notebook="test_notebook.ipynb",
cos_endpoint="http://testserver:32525",
cos_bucket="test_bucket",
cos_directory="test_directory",
cos_dependencies_archive="test_archive.tgz",
pipeline_envs={
"ENV_VAR_ONE": "1",
"ENV_VAR_TWO": "2",
"ENV_VAR_THREE": "3"
},
image="test/image:dev",
workflow_engine="Tekton",
)
confirmation_names = [
"ENV_VAR_ONE", "ENV_VAR_TWO", "ENV_VAR_THREE", "ELYRA_RUN_NAME"
]
confirmation_values = ["1", "2", "3"]
field_path = "metadata.annotations['pipelines.kubeflow.org/run_name']"
for env_val in notebook_op.container.env:
assert env_val.name in confirmation_names
confirmation_names.remove(env_val.name)
if env_val.name == "ELYRA_RUN_NAME":
assert env_val.value_from.field_ref.field_path == field_path, env_val.value_from.field_ref
else:
assert env_val.value in confirmation_values
confirmation_values.remove(env_val.value)
# Verify confirmation values have been drained.
assert len(confirmation_names) == 0
assert len(confirmation_values) == 0
def _cc_pipeline(
self, pipeline, pipeline_name, pipeline_version="", experiment_name="", cos_directory=None, export=False
):
runtime_configuration = self._get_metadata_configuration(
schemaspace=Runtimes.RUNTIMES_SCHEMASPACE_ID, name=pipeline.runtime_config
)
cos_endpoint = runtime_configuration.metadata["cos_endpoint"]
cos_username = runtime_configuration.metadata.get("cos_username")
cos_password = runtime_configuration.metadata.get("cos_password")
cos_secret = runtime_configuration.metadata.get("cos_secret")
cos_bucket = runtime_configuration.metadata.get("cos_bucket")
if cos_directory is None:
cos_directory = pipeline_name
engine = runtime_configuration.metadata["engine"]
self.log_pipeline_info(
pipeline_name,
f"processing pipeline dependencies to: {cos_endpoint} " f"bucket: {cos_bucket} folder: {cos_directory}",
)
t0_all = time.time()
emptydir_volume_size = ""
container_runtime = bool(os.getenv("CRIO_RUNTIME", "False").lower() == "true")
# Create dictionary that maps component Id to its ContainerOp instance
target_ops = {}
# Sort operations based on dependency graph (topological order)
sorted_operations = PipelineProcessor._sort_operations(pipeline.operations)
# Determine whether access to cloud storage is required
for operation in sorted_operations:
if isinstance(operation, GenericOperation):
self._verify_cos_connectivity(runtime_configuration)
break
# All previous operation outputs should be propagated throughout the pipeline.
# In order to process this recursively, the current operation's inputs should be combined
# from its parent's inputs (which, themselves are derived from the outputs of their parent)
# and its parent's outputs.
PipelineProcessor._propagate_operation_inputs_outputs(pipeline, sorted_operations)
for operation in sorted_operations:
if container_runtime:
# Volume size to create when using CRI-o, NOTE: IBM Cloud minimum is 20Gi
emptydir_volume_size = "20Gi"
sanitized_operation_name = self._sanitize_operation_name(operation.name)
# Create pipeline operation
# If operation is one of the "generic" set of NBs or scripts, construct custom ExecuteFileOp
if isinstance(operation, GenericOperation):
# Collect env variables
pipeline_envs = self._collect_envs(
operation, cos_secret=cos_secret, cos_username=cos_username, cos_password=cos_password
)
operation_artifact_archive = self._get_dependency_archive_name(operation)
self.log.debug(f"Creating pipeline component:\n {operation} archive : {operation_artifact_archive}")
target_ops[operation.id] = ExecuteFileOp(
name=sanitized_operation_name,
pipeline_name=pipeline_name,
experiment_name=experiment_name,
notebook=operation.filename,
cos_endpoint=cos_endpoint,
cos_bucket=cos_bucket,
cos_directory=cos_directory,
cos_dependencies_archive=operation_artifact_archive,
pipeline_version=pipeline_version,
pipeline_source=pipeline.source,
pipeline_inputs=operation.inputs,
pipeline_outputs=operation.outputs,
pipeline_envs=pipeline_envs,
emptydir_volume_size=emptydir_volume_size,
cpu_request=operation.cpu,
mem_request=operation.memory,
gpu_limit=operation.gpu,
workflow_engine=engine,
image=operation.runtime_image,
file_outputs={
"mlpipeline-metrics": f"{pipeline_envs['ELYRA_WRITABLE_CONTAINER_DIR']}/mlpipeline-metrics.json", # noqa
"mlpipeline-ui-metadata": f"{pipeline_envs['ELYRA_WRITABLE_CONTAINER_DIR']}/mlpipeline-ui-metadata.json", # noqa
},
)
if operation.doc:
target_ops[operation.id].add_pod_annotation("elyra/node-user-doc", operation.doc)
# TODO Can we move all of this to apply to non-standard components as well? Test when servers are up
if cos_secret and not export:
target_ops[operation.id].apply(use_aws_secret(cos_secret))
image_namespace = self._get_metadata_configuration(RuntimeImages.RUNTIME_IMAGES_SCHEMASPACE_ID)
for image_instance in image_namespace:
if image_instance.metadata["image_name"] == operation.runtime_image and image_instance.metadata.get(
"pull_policy"
):
target_ops[operation.id].container.set_image_pull_policy(image_instance.metadata["pull_policy"])
self.log_pipeline_info(
pipeline_name,
f"processing operation dependencies for id: {operation.id}",
operation_name=operation.name,
)
self._upload_dependencies_to_object_store(runtime_configuration, cos_directory, operation)
# If operation is a "non-standard" component, load it's spec and create operation with factory function
else:
# Retrieve component from cache
component = ComponentCache.instance().get_component(self._type, operation.classifier)
# Convert the user-entered value of certain properties according to their type
for component_property in component.properties:
# Get corresponding property's value from parsed pipeline
property_value = operation.component_params.get(component_property.ref)
self.log.debug(
f"Processing component parameter '{component_property.name}' "
f"of type '{component_property.data_type}'"
)
if component_property.data_type == "inputpath":
output_node_id = property_value["value"]
output_node_parameter_key = property_value["option"].replace("elyra_output_", "")
operation.component_params[component_property.ref] = target_ops[output_node_id].outputs[
output_node_parameter_key
]
elif component_property.data_type == "inputvalue":
active_property = property_value["activeControl"]
active_property_value = property_value.get(active_property, None)
# If the value is not found, assign it the default value assigned in parser
if active_property_value is None:
active_property_value = component_property.value
if isinstance(active_property_value, dict) and set(active_property_value.keys()) == {
"value",
"option",
}:
output_node_id = active_property_value["value"]
output_node_parameter_key = active_property_value["option"].replace("elyra_output_", "")
operation.component_params[component_property.ref] = target_ops[output_node_id].outputs[
output_node_parameter_key
]
elif component_property.default_data_type == "dictionary":
processed_value = self._process_dictionary_value(active_property_value)
operation.component_params[component_property.ref] = processed_value
elif component_property.default_data_type == "list":
processed_value = self._process_list_value(active_property_value)
operation.component_params[component_property.ref] = processed_value
else:
operation.component_params[component_property.ref] = active_property_value
# Build component task factory
try:
factory_function = components.load_component_from_text(component.definition)
except Exception as e:
# TODO Fix error messaging and break exceptions down into categories
self.log.error(f"Error loading component spec for {operation.name}: {str(e)}")
raise RuntimeError(f"Error loading component spec for {operation.name}.")
# Add factory function, which returns a ContainerOp task instance, to pipeline operation dict
try:
comp_spec_inputs = [
inputs.name.lower().replace(" ", "_") for inputs in factory_function.component_spec.inputs
]
# Remove inputs and outputs from params dict
# TODO: need to have way to retrieve only required params
parameter_removal_list = ["inputs", "outputs"]
for component_param in operation.component_params_as_dict.keys():
if component_param not in comp_spec_inputs:
parameter_removal_list.append(component_param)
for parameter in parameter_removal_list:
operation.component_params_as_dict.pop(parameter, None)
# Create ContainerOp instance and assign appropriate user-provided name
sanitized_component_params = {
self._sanitize_param_name(name): value
for name, value in operation.component_params_as_dict.items()
}
container_op = factory_function(**sanitized_component_params)
container_op.set_display_name(operation.name)
if operation.doc:
container_op.add_pod_annotation("elyra/node-user-doc", operation.doc)
target_ops[operation.id] = container_op
except Exception as e:
# TODO Fix error messaging and break exceptions down into categories
self.log.error(f"Error constructing component {operation.name}: {str(e)}")
raise RuntimeError(f"Error constructing component {operation.name}.")
# Process dependencies after all the operations have been created
for operation in pipeline.operations.values():
op = target_ops[operation.id]
for parent_operation_id in operation.parent_operation_ids:
parent_op = target_ops[parent_operation_id] # Parent Operation
op.after(parent_op)
self.log_pipeline_info(pipeline_name, "pipeline dependencies processed", duration=(time.time() - t0_all))
return target_ops
def test_normalize_label_value():
valid_middle_chars = "-_."
# test min length
assert ExecuteFileOp._normalize_label_value(None) == ""
assert ExecuteFileOp._normalize_label_value("") == ""
# test max length (63)
assert ExecuteFileOp._normalize_label_value("a" * 63) == "a" * 63
assert ExecuteFileOp._normalize_label_value("a" *
64) == "a" * 63 # truncated
# test first and last char
assert ExecuteFileOp._normalize_label_value("1") == "1"
assert ExecuteFileOp._normalize_label_value("22") == "22"
assert ExecuteFileOp._normalize_label_value("3_3") == "3_3"
assert ExecuteFileOp._normalize_label_value("4u4") == "4u4"
assert ExecuteFileOp._normalize_label_value("5$5") == "5_5"
# test first char
for c in string.printable:
if c in string.ascii_letters + string.digits:
# first char is valid
# no length violation
assert ExecuteFileOp._normalize_label_value(c) == c
assert ExecuteFileOp._normalize_label_value(c + "B") == c + "B"
# max length
assert ExecuteFileOp._normalize_label_value(c +
"B" * 62) == (c +
"B" * 62)
# max length exceeded
assert ExecuteFileOp._normalize_label_value(c + "B" * 63) == (
c + "B" * 62) # truncated
else:
# first char is invalid, e.g. '#a', and becomes the
# second char, which might require replacement
rv = c
if c not in valid_middle_chars:
rv = "_"
# no length violation
assert ExecuteFileOp._normalize_label_value(c) == "a" + rv + "a"
assert ExecuteFileOp._normalize_label_value(c +
"B") == "a" + rv + "B"
# max length
assert ExecuteFileOp._normalize_label_value(c + "B" * 62) == (
"a" + rv + "B" * 61) # truncated
# max length exceeded
assert ExecuteFileOp._normalize_label_value(c + "B" * 63) == (
"a" + rv + "B" * 61) # truncated
# test last char
for c in string.printable:
if c in string.ascii_letters + string.digits:
# no length violation
assert ExecuteFileOp._normalize_label_value("b" + c) == "b" + c
# max length
assert ExecuteFileOp._normalize_label_value("b" * 62 +
c) == ("b" * 62 + c)
# max length exceeded
assert ExecuteFileOp._normalize_label_value("b" * 63 + c) == ("b" *
63)
else:
# last char is invalid, e.g. 'a#', and requires
# patching
rv = c
if c not in valid_middle_chars:
rv = "_"
# no length violation (char is appended)
assert ExecuteFileOp._normalize_label_value("b" +
c) == "b" + rv + "a"
# max length (char is replaced)
assert ExecuteFileOp._normalize_label_value("b" * 62 +
c) == ("b" * 62 + "a")
# max length exceeded (no action required)
assert ExecuteFileOp._normalize_label_value("b" * 63 + c) == ("b" *
63)
# test first and last char
for c in string.printable:
if c in string.ascii_letters + string.digits:
# no length violation
assert ExecuteFileOp._normalize_label_value(
c + "b" + c) == c + "b" + c # nothing is modified
# max length
assert ExecuteFileOp._normalize_label_value(c + "b" * 61 + c) == (
c + "b" * 61 + c) # nothing is modified
# max length exceeded
assert ExecuteFileOp._normalize_label_value(
c + "b" * 62 + c) == c + "b" * 62 # truncate only
else:
# first and last characters are invalid, e.g. '#a#'
rv = c
if c not in valid_middle_chars:
rv = "_"
# no length violation
assert ExecuteFileOp._normalize_label_value(
c + "b" + c) == "a" + rv + "b" + rv + "a"
# max length
assert ExecuteFileOp._normalize_label_value(c + "b" * 59 +
c) == ("a" + rv +
"b" * 59 + rv +
"a")
# max length exceeded after processing, scenario 1
# resolved by adding char before first, replace last
assert ExecuteFileOp._normalize_label_value(c + "b" * 60 +
c) == ("a" + rv +
"b" * 60 + "a")
# max length exceeded after processing, scenario 2
# resolved by adding char before first, appending after last
assert ExecuteFileOp._normalize_label_value(c + "b" * 59 +
c) == ("a" + rv +
"b" * 59 + rv +
"a")
# max length exceeded before processing, scenario 1
# resolved by adding char before first, truncating last
assert ExecuteFileOp._normalize_label_value(c + "b" * 62 +
c) == ("a" + rv +
"b" * 61)
# max length exceeded before processing, scenario 2
# resolved by adding char before first, replacing last
assert ExecuteFileOp._normalize_label_value(c + "b" * 60 +
c * 3) == ("a" + rv +
"b" * 60 +
"a")
# test char in a position other than first and last
# if invalid, the char is replaced with '_'
for c in string.printable:
if c in string.ascii_letters + string.digits + "-_.":
assert ExecuteFileOp._normalize_label_value("A" + c +
"Z") == "A" + c + "Z"
else:
assert ExecuteFileOp._normalize_label_value("A" + c + "Z") == "A_Z"
# encore
assert ExecuteFileOp._normalize_label_value(r"¯\_(ツ)_/¯") == "a_________a"
def test_construct_with_env_variables_argo():
notebook_op = ExecuteFileOp(
name="test",
pipeline_name="test-pipeline",
experiment_name="experiment-name",
notebook="test_notebook.ipynb",
cos_endpoint="http://testserver:32525",
cos_bucket="test_bucket",
cos_directory="test_directory",
cos_dependencies_archive="test_archive.tgz",
pipeline_envs={
"ENV_VAR_ONE": "1",
"ENV_VAR_TWO": "2",
"ENV_VAR_THREE": "3"
},
image="test/image:dev",
)
confirmation_names = [
"ENV_VAR_ONE", "ENV_VAR_TWO", "ENV_VAR_THREE", "ELYRA_RUN_NAME"
]
confirmation_values = ["1", "2", "3", RUN_ID_PLACEHOLDER]
for env_val in notebook_op.container.env:
assert env_val.name in confirmation_names
assert env_val.value in confirmation_values
confirmation_names.remove(env_val.name)
confirmation_values.remove(env_val.value)
# Verify confirmation values have been drained.
assert len(confirmation_names) == 0
assert len(confirmation_values) == 0
# same as before but explicitly specify the workflow engine type
# as Argo
notebook_op = ExecuteFileOp(
name="test",
pipeline_name="test-pipeline",
experiment_name="experiment-name",
notebook="test_notebook.ipynb",
cos_endpoint="http://testserver:32525",
cos_bucket="test_bucket",
cos_directory="test_directory",
cos_dependencies_archive="test_archive.tgz",
pipeline_envs={
"ENV_VAR_ONE": "1",
"ENV_VAR_TWO": "2",
"ENV_VAR_THREE": "3"
},
image="test/image:dev",
workflow_engine="Argo",
)
confirmation_names = [
"ENV_VAR_ONE", "ENV_VAR_TWO", "ENV_VAR_THREE", "ELYRA_RUN_NAME"
]
confirmation_values = ["1", "2", "3", RUN_ID_PLACEHOLDER]
for env_val in notebook_op.container.env:
assert env_val.name in confirmation_names
assert env_val.value in confirmation_values
confirmation_names.remove(env_val.name)
confirmation_values.remove(env_val.value)
# Verify confirmation values have been drained.
assert len(confirmation_names) == 0
assert len(confirmation_values) == 0
