aihub-dag/elyra/tests/pipeline/airflow/test_processor_airflow.py

#
# Copyright 2018-2022 Elyra Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import os
from pathlib import Path
import re
import string
import tempfile
from types import SimpleNamespace
from unittest import mock

from conftest import AIRFLOW_COMPONENT_CACHE_INSTANCE
import github
import pytest

from elyra.metadata.metadata import Metadata
from elyra.pipeline.airflow.processor_airflow import AirflowPipelineProcessor
from elyra.pipeline.parser import PipelineParser
from elyra.pipeline.pipeline import GenericOperation
from elyra.pipeline.runtime_type import RuntimeProcessorType
from elyra.tests.pipeline.test_pipeline_parser import _read_pipeline_resource
from elyra.util.github import GithubClient

PIPELINE_FILE_COMPLEX = "resources/sample_pipelines/pipeline_dependency_complex.json"
PIPELINE_FILE_CUSTOM_COMPONENTS = "resources/sample_pipelines/pipeline_with_airflow_components.json"


@pytest.fixture
def processor(setup_factory_data):
    processor = AirflowPipelineProcessor(os.getcwd())
    return processor


@pytest.fixture
def parsed_pipeline(request):
    pipeline_resource = _read_pipeline_resource(request.param)
    return PipelineParser().parse(pipeline_json=pipeline_resource)


@pytest.fixture
def sample_metadata():
    return {
        "name": "airflow_test",
        "display_name": "Apache Airflow Test Endpoint",
        "metadata": {
            "github_api_endpoint": "https://api.github.com",
            "github_repo": "test/test-repo",
            "github_repo_token": "",
            "github_branch": "test",
            "api_endpoint": "http://test.example.com:30000/",
            "cos_endpoint": "http://test.example.com:30001/",
            "cos_username": "test",
            "cos_password": "test-password",
            "cos_bucket": "test-bucket",
            "tags": [],
            "user_namespace": "default",
            "runtime_type": "APACHE_AIRFLOW",
        },
        "schema_name": "airflow",
        "resource": "/User/test_directory/airflow_test.json",
    }


@pytest.fixture
def sample_image_metadata():
    image_one = {"image_name": "tensorflow/tensorflow:2.0.0-py3", "pull_policy": "IfNotPresent", "tags": []}
    image_two = {"image_name": "elyra/examples:1.0.0-py3", "pull_policy": "Always", "tags": []}

    mocked_runtime_images = [
        Metadata(name="test-image-metadata", display_name="test-image", schema_name="airflow", metadata=image_one),
        Metadata(name="test-image-metadata", display_name="test-image", schema_name="airflow", metadata=image_two),
    ]

    return mocked_runtime_images


@pytest.fixture
def parsed_ordered_dict(monkeypatch, processor, parsed_pipeline, sample_metadata, sample_image_metadata):

    mocked_runtime = Metadata(
        name="test-metadata", display_name="test", schema_name="airflow", metadata=sample_metadata["metadata"]
    )

    mocked_func = mock.Mock(return_value="default", side_effect=[mocked_runtime, sample_image_metadata])

    monkeypatch.setattr(processor, "_get_metadata_configuration", mocked_func)
    monkeypatch.setattr(processor, "_upload_dependencies_to_object_store", lambda w, x, y, prefix: True)
    monkeypatch.setattr(processor, "_get_dependency_archive_name", lambda x: True)
    monkeypatch.setattr(processor, "_verify_cos_connectivity", lambda x: True)

    return processor._cc_pipeline(parsed_pipeline, pipeline_name="some-name", pipeline_instance_id="some-instance-id")


def read_key_pair(key_pair, sep="="):
    return {"key": key_pair.split(sep)[0].strip('" '), "value": key_pair.split(sep)[1].rstrip(",").strip('" ')}


def string_to_list(stringed_list):
    return stringed_list.replace(" ", "").replace('"', "").strip("[]").split(",")


def test_processor_type(processor):
    assert processor.type == RuntimeProcessorType.APACHE_AIRFLOW


def test_fail_processor_type(processor):
    with pytest.raises(Exception):
        assert processor.type == RuntimeProcessorType.KUBEFLOW_PIPELINES


@pytest.mark.parametrize("parsed_pipeline", [PIPELINE_FILE_COMPLEX], indirect=True)
def test_pipeline_process(monkeypatch, processor, parsed_pipeline, sample_metadata):

    mocked_runtime = Metadata(
        name="test-metadata", display_name="test", schema_name="airflow", metadata=sample_metadata["metadata"]
    )
    mocked_path = "/some-placeholder"

    monkeypatch.setattr(processor, "_get_metadata_configuration", lambda schemaspace, name: mocked_runtime)
    monkeypatch.setattr(
        processor,
        "create_pipeline_file",
        lambda pipeline, pipeline_export_format, pipeline_export_path, pipeline_name, pipeline_instance_id: mocked_path,
    )

    monkeypatch.setattr(github.Github, "get_repo", lambda x, y: True)
    monkeypatch.setattr(GithubClient, "upload_dag", lambda x, y, z: True)

    response = processor.process(pipeline=parsed_pipeline)

    assert response.run_url == sample_metadata["metadata"]["api_endpoint"]
    assert response.object_storage_url == sample_metadata["metadata"]["cos_endpoint"]
    # Verifies that only this substring is in the storage path since a timestamp is injected into the name
    assert "/" + sample_metadata["metadata"]["cos_bucket"] + "/" + "untitled" in response.object_storage_path


@pytest.mark.parametrize("parsed_pipeline", [PIPELINE_FILE_COMPLEX], indirect=True)
def test_create_file(monkeypatch, processor, parsed_pipeline, parsed_ordered_dict, sample_metadata):
    pipeline_json = _read_pipeline_resource(PIPELINE_FILE_COMPLEX)

    export_pipeline_name = "some-name"
    export_file_type = "py"

    mocked_runtime = Metadata(
        name="test-metadata", display_name="test", schema_name="airflow", metadata=sample_metadata["metadata"]
    )

    monkeypatch.setattr(processor, "_get_metadata_configuration", lambda name=None, schemaspace=None: mocked_runtime)
    monkeypatch.setattr(processor, "_upload_dependencies_to_object_store", lambda w, x, y, prefix: True)
    monkeypatch.setattr(processor, "_cc_pipeline", lambda x, y, z: parsed_ordered_dict)

    with tempfile.TemporaryDirectory() as temp_dir:
        export_pipeline_output_path = os.path.join(temp_dir, f"{export_pipeline_name}.py")

        response = processor.create_pipeline_file(
            parsed_pipeline,
            pipeline_export_format=export_file_type,
            pipeline_export_path=export_pipeline_output_path,
            pipeline_name=export_pipeline_name,
            pipeline_instance_id=export_pipeline_name,
        )

        assert export_pipeline_output_path == response
        assert os.path.isfile(export_pipeline_output_path)

        file_as_lines = open(response).read().splitlines()

        assert "from airflow.contrib.operators.kubernetes_pod_operator import KubernetesPodOperator" in file_as_lines

        # Check DAG project name
        for i in range(len(file_as_lines)):
            if "args = {" == file_as_lines[i]:
                assert "project_id" == read_key_pair(file_as_lines[i + 1], sep=":")["key"]
                assert export_pipeline_name == read_key_pair(file_as_lines[i + 1], sep=":")["value"]

        # For every node in the original pipeline json
        for node in pipeline_json["pipelines"][0]["nodes"]:
            component_parameters = node["app_data"]["component_parameters"]
            for i in range(len(file_as_lines)):
                # Matches a generic op with a node ID
                if f"op_{node['id'].replace('-', '_')} = KubernetesPodOperator(" in file_as_lines[i]:
                    sub_list_line_counter = 0
                    # Gets sub-list slice starting where the Notebook Op starts
                    init_line = i + 1
                    for line in file_as_lines[init_line:]:
                        if "namespace=" in line:
                            assert sample_metadata["metadata"]["user_namespace"] == read_key_pair(line)["value"]
                        elif "cos_endpoint=" in line:
                            assert sample_metadata["metadata"]["cos_endpoint"] == read_key_pair(line)["value"]
                        elif "cos_bucket=" in line:
                            assert sample_metadata["metadata"]["cos_bucket"] == read_key_pair(line)["value"]
                        elif "name=" in line:
                            assert node["app_data"]["ui_data"]["label"] == read_key_pair(line)["value"]
                        elif "notebook=" in line:
                            assert component_parameters["filename"] == read_key_pair(line)["value"]
                        elif "image=" in line:
                            assert component_parameters["runtime_image"] == read_key_pair(line)["value"]
                        elif "env_vars=" in line:
                            for env in component_parameters["env_vars"]:
                                var, value = env.split("=")
                                # Gets sub-list slice starting where the env vars starts
                                start_env = i + sub_list_line_counter + 2
                                for env_line in file_as_lines[start_env:]:
                                    if "AWS_ACCESS_KEY_ID" in env_line:
                                        assert (
                                            sample_metadata["metadata"]["cos_username"]
                                            == read_key_pair(env_line, sep=":")["value"]
                                        )
                                    elif "AWS_SECRET_ACCESS_KEY" in env_line:
                                        assert (
                                            sample_metadata["metadata"]["cos_password"]
                                            == read_key_pair(env_line, sep=":")["value"]
                                        )
                                    elif var in env_line:
                                        assert var == read_key_pair(env_line, sep=":")["key"]
                                        assert value == read_key_pair(env_line, sep=":")["value"]
                                    elif env_line.strip() == "},":  # end of env vars
                                        break
                        elif "pipeline_inputs=" in line and component_parameters.get("inputs"):
                            for input in component_parameters["inputs"]:
                                assert input in string_to_list(read_key_pair(line)["value"])
                        elif "pipeline_outputs=" in line and component_parameters.get("outputs"):
                            for output in component_parameters["outputs"]:
                                assert output in string_to_list(read_key_pair(line)["value"])
                        elif line == ")":  # End of this Notebook Op
                            break
                        sub_list_line_counter += 1


@pytest.mark.parametrize("parsed_pipeline", [PIPELINE_FILE_CUSTOM_COMPONENTS], indirect=True)
@pytest.mark.parametrize("catalog_instance", [AIRFLOW_COMPONENT_CACHE_INSTANCE], indirect=True)
def test_create_file_custom_components(
    monkeypatch, processor, catalog_instance, component_cache, parsed_pipeline, parsed_ordered_dict, sample_metadata
):
    pipeline_json = _read_pipeline_resource(PIPELINE_FILE_CUSTOM_COMPONENTS)

    export_pipeline_name = "some-name"
    export_file_type = "py"

    mocked_runtime = Metadata(
        name="test-metadata", display_name="test", schema_name="airflow", metadata=sample_metadata["metadata"]
    )

    monkeypatch.setattr(processor, "_get_metadata_configuration", lambda name=None, schemaspace=None: mocked_runtime)
    monkeypatch.setattr(processor, "_upload_dependencies_to_object_store", lambda w, x, y, prefix: True)
    monkeypatch.setattr(processor, "_cc_pipeline", lambda x, y, z: parsed_ordered_dict)

    with tempfile.TemporaryDirectory() as temp_dir:
        export_pipeline_output_path = os.path.join(temp_dir, f"{export_pipeline_name}.py")

        response = processor.create_pipeline_file(
            parsed_pipeline,
            pipeline_export_format=export_file_type,
            pipeline_export_path=export_pipeline_output_path,
            pipeline_name=export_pipeline_name,
            pipeline_instance_id=export_pipeline_name,
        )

        assert export_pipeline_output_path == response
        assert os.path.isfile(export_pipeline_output_path)

        file_as_lines = open(response).read().splitlines()

        pipeline_description = pipeline_json["pipelines"][0]["app_data"]["properties"]["description"]
        escaped_description = pipeline_description.replace('"""', '\\"\\"\\"')

        for i in range(len(file_as_lines)):
            if "args = {" == file_as_lines[i]:
                # Check DAG project name
                assert "project_id" == read_key_pair(file_as_lines[i + 1], sep=":")["key"]
                assert export_pipeline_name == read_key_pair(file_as_lines[i + 1], sep=":")["value"]
            elif 'description="""' in file_as_lines[i]:
                # Check that DAG contains the correct description
                line_no = i + 1
                description_as_lines = []
                while '"""' not in file_as_lines[line_no]:
                    description_as_lines.append(file_as_lines[line_no])
                    line_no += 1
                expected_description_lines = escaped_description.split("\n")
                assert description_as_lines == expected_description_lines

                # Nothing more to be done in file
                break

        # For every node in the original pipeline json
        for node in pipeline_json["pipelines"][0]["nodes"]:
            component_parameters = node["app_data"]["component_parameters"]
            for i in range(len(file_as_lines)):
                # Matches custom component operators
                if f"op_{node['id'].replace('-', '_')} = " in file_as_lines[i]:
                    for parameter in component_parameters:
                        # Find 'parameter=' clause in file_as_lines list
                        r = re.compile(rf"\s*{parameter}=.*")
                        parameter_clause = i + 1
                        assert len(list(filter(r.match, file_as_lines[parameter_clause:]))) > 0


@pytest.mark.parametrize("parsed_pipeline", [PIPELINE_FILE_COMPLEX], indirect=True)
def test_export_overwrite(monkeypatch, processor, parsed_pipeline):
    with tempfile.TemporaryDirectory() as temp_dir:
        mocked_path = os.path.join(temp_dir, "some-name.py")
        Path(mocked_path).touch()
        assert os.path.isfile(mocked_path)

        monkeypatch.setattr(
            processor,
            "create_pipeline_file",
            lambda pipeline, pipeline_export_format, pipeline_export_path, pipeline_name, pipeline_instance_id: mocked_path,  # noqa: E501
        )

        returned_path = processor.export(parsed_pipeline, "py", mocked_path, True)
        assert returned_path == mocked_path


@pytest.mark.parametrize("parsed_pipeline", [PIPELINE_FILE_COMPLEX], indirect=True)
def test_fail_export_overwrite(processor, parsed_pipeline):
    with tempfile.TemporaryDirectory() as temp_dir:
        Path(f"{temp_dir}/test.py").touch()
        assert os.path.isfile(f"{temp_dir}/test.py")

        export_pipeline_output_path = os.path.join(temp_dir, "test.py")
        with pytest.raises(ValueError):
            processor.export(parsed_pipeline, "py", export_pipeline_output_path, False)


@pytest.mark.parametrize("parsed_pipeline", [PIPELINE_FILE_COMPLEX], indirect=True)
def test_pipeline_tree_creation(parsed_ordered_dict, sample_metadata, sample_image_metadata):
    pipeline_json = _read_pipeline_resource(PIPELINE_FILE_COMPLEX)

    ordered_dict = parsed_ordered_dict

    assert len(ordered_dict.keys()) == len(pipeline_json["pipelines"][0]["nodes"])

    # Verify tree structure is correct
    assert not ordered_dict["cded6818-e601-4fd8-b6b9-c9fdf1fd1fca"].get("parent_operation_ids")
    assert (
        ordered_dict["bb9606ca-29ec-4133-a36a-67bd2a1f6dc3"].get("parent_operation_ids").pop()
        == "cded6818-e601-4fd8-b6b9-c9fdf1fd1fca"
    )
    assert (
        ordered_dict["6f5c2ece-1977-48a1-847f-099b327c6ed1"].get("parent_operation_ids").pop()
        == "cded6818-e601-4fd8-b6b9-c9fdf1fd1fca"
    )
    assert (
        ordered_dict["4ef63a48-a27c-4d1e-a0ee-2fbbdbe3be74"].get("parent_operation_ids").pop()
        == "cded6818-e601-4fd8-b6b9-c9fdf1fd1fca"
    )
    assert (
        ordered_dict["4f7ae91b-682e-476c-8664-58412336b31f"].get("parent_operation_ids").pop()
        == "bb9606ca-29ec-4133-a36a-67bd2a1f6dc3"
    )
    assert (
        ordered_dict["f82c4699-b392-4a3e-92b0-45d9e11126fe"].get("parent_operation_ids").pop()
        == "bb9606ca-29ec-4133-a36a-67bd2a1f6dc3"
    )
    assert ordered_dict["137d3d2f-4224-42d9-b8c6-cbee9ff2872d"].get("parent_operation_ids") == [
        "4ef63a48-a27c-4d1e-a0ee-2fbbdbe3be74",
        "0a7eff92-fe2a-411c-92a6-73d6f3810516",
    ]
    assert not ordered_dict["779c2630-64bf-47ca-8a98-9ac8a60e85f7"].get("parent_operation_ids")
    assert (
        ordered_dict["0a7eff92-fe2a-411c-92a6-73d6f3810516"].get("parent_operation_ids").pop()
        == "779c2630-64bf-47ca-8a98-9ac8a60e85f7"
    )
    assert ordered_dict["92a7a247-1131-489c-8c3e-1e2389d4c673"].get("parent_operation_ids") == [
        "f82c4699-b392-4a3e-92b0-45d9e11126fe",
        "137d3d2f-4224-42d9-b8c6-cbee9ff2872d",
        "6f5c2ece-1977-48a1-847f-099b327c6ed1",
    ]

    for key in ordered_dict.keys():
        for node in pipeline_json["pipelines"][0]["nodes"]:
            if node["id"] == key:
                component_parameters = node["app_data"]["component_parameters"]
                assert ordered_dict[key]["runtime_image"] == component_parameters["runtime_image"]
                for image in sample_image_metadata:
                    if ordered_dict[key]["runtime_image"] == image.metadata["image_name"]:
                        assert ordered_dict[key]["image_pull_policy"] == image.metadata["pull_policy"]
                print(ordered_dict[key])
                for env in component_parameters["env_vars"]:
                    var, value = env.split("=")
                    assert ordered_dict[key]["pipeline_envs"][var] == value
                assert (
                    ordered_dict[key]["pipeline_envs"]["AWS_ACCESS_KEY_ID"]
                    == sample_metadata["metadata"]["cos_username"]
                )
                assert (
                    ordered_dict[key]["pipeline_envs"]["AWS_SECRET_ACCESS_KEY"]
                    == sample_metadata["metadata"]["cos_password"]
                )
                for arg in ["inputs", "outputs"]:
                    if node["app_data"].get(arg):
                        for file in node["app_data"][arg]:
                            assert file in ordered_dict[key]["pipeline_" + arg]


def test_collect_envs(processor):
    pipelines_test_file = "elyra/pipeline/tests/resources/archive/test.ipynb"

    # add system-owned envs with bogus values to ensure they get set to system-derived values,
    # and include some user-provided edge cases
    operation_envs = [
        'ELYRA_RUNTIME_ENV="bogus_runtime"',
        'ELYRA_ENABLE_PIPELINE_INFO="bogus_pipeline"',
        "ELYRA_WRITABLE_CONTAINER_DIR=",  # simulate operation reference in pipeline
        'AWS_ACCESS_KEY_ID="bogus_key"',
        'AWS_SECRET_ACCESS_KEY="bogus_secret"',
        "USER_EMPTY_VALUE=  ",
        "USER_TWO_EQUALS=KEY=value",
        "USER_NO_VALUE=",
    ]
    component_parameters = {
        "filename": pipelines_test_file,
        "env_vars": operation_envs,
        "runtime_image": "tensorflow/tensorflow:latest",
    }
    test_operation = GenericOperation(
        id="this-is-a-test-id",
        type="execution-node",
        classifier="execute-notebook-node",
        name="test",
        component_params=component_parameters,
    )

    envs = processor._collect_envs(test_operation, cos_secret=None, cos_username="Alice", cos_password="secret")

    assert envs["ELYRA_RUNTIME_ENV"] == "airflow"
    assert envs["AWS_ACCESS_KEY_ID"] == "Alice"
    assert envs["AWS_SECRET_ACCESS_KEY"] == "secret"
    assert envs["ELYRA_ENABLE_PIPELINE_INFO"] == "True"
    assert "ELYRA_WRITABLE_CONTAINER_DIR" not in envs
    assert "USER_EMPTY_VALUE" not in envs
    assert envs["USER_TWO_EQUALS"] == "KEY=value"
    assert "USER_NO_VALUE" not in envs

    # Repeat with non-None secret - ensure user and password envs are not present, but others are
    envs = processor._collect_envs(test_operation, cos_secret="secret", cos_username="Alice", cos_password="secret")

    assert envs["ELYRA_RUNTIME_ENV"] == "airflow"
    assert "AWS_ACCESS_KEY_ID" not in envs
    assert "AWS_SECRET_ACCESS_KEY" not in envs
    assert envs["ELYRA_ENABLE_PIPELINE_INFO"] == "True"
    assert "ELYRA_WRITABLE_CONTAINER_DIR" not in envs
    assert "USER_EMPTY_VALUE" not in envs
    assert envs["USER_TWO_EQUALS"] == "KEY=value"
    assert "USER_NO_VALUE" not in envs


def test_unique_operation_name_existent(processor):
    op1 = SimpleNamespace(name="sample_operation")
    op2 = SimpleNamespace(name="sample_operation_2")
    op3 = SimpleNamespace(name="sample_operation_3")
    op4 = SimpleNamespace(name="sample_operation")
    op5 = SimpleNamespace(name="sample_operation_2")
    op6 = SimpleNamespace(name="sample_operation_3")
    sample_operation_list = [op1, op2, op3, op4, op5, op6]

    correct_name_list = [
        "sample_operation",
        "sample_operation_2",
        "sample_operation_3",
        "sample_operation_1",
        "sample_operation_2_1",
        "sample_operation_3_1",
    ]

    renamed_op_list = processor._create_unique_node_names(sample_operation_list)
    name_list = [op.name for op in renamed_op_list]

    assert name_list == correct_name_list


def test_unique_operation_name_non_existent(processor):
    operation_name = "sample_operation_foo_bar"

    op1 = SimpleNamespace(name="sample_operation")
    op2 = SimpleNamespace(name="sample_operation_2")
    op3 = SimpleNamespace(name="sample_operation_3")
    sample_operation_list = [op1, op2, op3]

    correct_name_list = ["sample_operation", "sample_operation_2", "sample_operation_3"]

    renamed_op_list = processor._create_unique_node_names(sample_operation_list)
    name_list = [op.name for op in renamed_op_list]

    assert name_list == correct_name_list
    assert operation_name not in name_list


def test_unique_operation_custom(processor):
    op1 = SimpleNamespace(name="this bash")
    op2 = SimpleNamespace(name="this@bash")
    op3 = SimpleNamespace(name="this!bash")
    op4 = SimpleNamespace(name="that^bash")
    op5 = SimpleNamespace(name="that bash")
    op6 = SimpleNamespace(name="that_bash_2")
    op7 = SimpleNamespace(name="that_bash_1")
    op8 = SimpleNamespace(name="that_bash_0")
    sample_operation_list = [op1, op2, op3, op4, op5, op6, op7, op8]

    correct_name_list = [
        "this_bash",
        "this_bash_1",
        "this_bash_2",
        "that_bash",
        "that_bash_1",
        "that_bash_2",
        "that_bash_1_1",
        "that_bash_0",
    ]

    scrubbed_list = processor._scrub_invalid_characters_from_list(sample_operation_list)
    renamed_op_list = processor._create_unique_node_names(scrubbed_list)
    name_list = [op.name for op in renamed_op_list]

    assert name_list == correct_name_list


def test_process_list_value_function(processor):
    # Test values that will be successfully converted to list
    assert processor._process_list_value("") == []
    assert processor._process_list_value(None) == []
    assert processor._process_list_value("[]") == []
    assert processor._process_list_value("None") == []
    assert processor._process_list_value("['elem1']") == ["elem1"]
    assert processor._process_list_value("['elem1', 'elem2', 'elem3']") == ["elem1", "elem2", "elem3"]
    assert processor._process_list_value("  ['elem1',   'elem2' , 'elem3']  ") == ["elem1", "elem2", "elem3"]
    assert processor._process_list_value("[1, 2]") == [1, 2]
    assert processor._process_list_value("[True, False, True]") == [True, False, True]
    assert processor._process_list_value("[{'obj': 'val', 'obj2': 'val2'}, {}]") == [{"obj": "val", "obj2": "val2"}, {}]

    # Test values that will not be successfully converted to list
    # Surrounding quotes are added to string values for correct DAG render
    assert processor._process_list_value("[[]") == '"[[]"'
    assert processor._process_list_value("[elem1, elem2]") == '"[elem1, elem2]"'
    assert processor._process_list_value("elem1, elem2") == '"elem1, elem2"'
    assert processor._process_list_value("  elem1, elem2  ") == '"elem1, elem2"'
    assert processor._process_list_value("'elem1', 'elem2'") == "\"'elem1', 'elem2'\""


def test_process_dictionary_value_function(processor):
    # Test values that will be successfully converted to dictionary
    assert processor._process_dictionary_value("") == {}
    assert processor._process_dictionary_value(None) == {}
    assert processor._process_dictionary_value("{}") == {}
    assert processor._process_dictionary_value("None") == {}
    assert processor._process_dictionary_value("{'key': 'value'}") == {"key": "value"}

    dict_as_str = "{'key1': 'value', 'key2': 'value'}"
    assert processor._process_dictionary_value(dict_as_str) == {"key1": "value", "key2": "value"}

    dict_as_str = "  {  'key1': 'value'  , 'key2'  : 'value'}  "
    assert processor._process_dictionary_value(dict_as_str) == {"key1": "value", "key2": "value"}

    dict_as_str = "{'key1': [1, 2, 3], 'key2': ['elem1', 'elem2']}"
    assert processor._process_dictionary_value(dict_as_str) == {"key1": [1, 2, 3], "key2": ["elem1", "elem2"]}

    dict_as_str = "{'key1': 2, 'key2': 'value', 'key3': True, 'key4': None, 'key5': [1, 2, 3]}"
    expected_value = {"key1": 2, "key2": "value", "key3": True, "key4": None, "key5": [1, 2, 3]}
    assert processor._process_dictionary_value(dict_as_str) == expected_value

    dict_as_str = "{'key1': {'key2': 2, 'key3': 3, 'key4': 4}, 'key5': {}}"
    expected_value = {
        "key1": {
            "key2": 2,
            "key3": 3,
            "key4": 4,
        },
        "key5": {},
    }
    assert processor._process_dictionary_value(dict_as_str) == expected_value

    # Test values that will not be successfully converted to dictionary
    # Surrounding quotes are added to string values for correct DAG render
    assert processor._process_dictionary_value("{{}") == '"{{}"'
    assert processor._process_dictionary_value("{key1: value, key2: value}") == '"{key1: value, key2: value}"'
    assert processor._process_dictionary_value("  { key1: value, key2: value }  ") == '"{ key1: value, key2: value }"'
    assert processor._process_dictionary_value("key1: value, key2: value") == '"key1: value, key2: value"'
    assert processor._process_dictionary_value("{'key1': true}") == "\"{'key1': true}\""
    assert processor._process_dictionary_value("{'key': null}") == "\"{'key': null}\""

    dict_as_str = "{'key1': [elem1, elem2, elem3], 'key2': ['elem1', 'elem2']}"
    assert processor._process_dictionary_value(dict_as_str) == f'"{dict_as_str}"'

    dict_as_str = "{'key1': {key2: 2}, 'key3': ['elem1', 'elem2']}"
    assert processor._process_dictionary_value(dict_as_str) == f'"{dict_as_str}"'

    dict_as_str = "{'key1': {key2: 2}, 'key3': ['elem1', 'elem2']}"
    assert processor._process_dictionary_value(dict_as_str) == f'"{dict_as_str}"'


@pytest.mark.parametrize(
    "parsed_pipeline", ["resources/validation_pipelines/aa_operator_same_name.json"], indirect=True
)
@pytest.mark.parametrize("catalog_instance", [AIRFLOW_COMPONENT_CACHE_INSTANCE], indirect=True)
def test_same_name_operator_in_pipeline(monkeypatch, processor, catalog_instance, parsed_pipeline, sample_metadata):
    task_id = "e3922a29-f4c0-43d9-8d8b-4509aab80032"
    upstream_task_id = "0eb57369-99d1-4cd0-a205-8d8d96af3ad4"

    mocked_runtime = Metadata(
        name="test-metadata", display_name="test", schema_name="airflow", metadata=sample_metadata["metadata"]
    )

    monkeypatch.setattr(processor, "_get_metadata_configuration", lambda name=None, schemaspace=None: mocked_runtime)
    monkeypatch.setattr(processor, "_upload_dependencies_to_object_store", lambda w, x, y, prefix: True)

    pipeline_def_operation = parsed_pipeline.operations[task_id]
    pipeline_def_operation_parameters = pipeline_def_operation.component_params_as_dict
    pipeline_def_operation_bash_param = pipeline_def_operation_parameters["bash_command"]

    assert pipeline_def_operation_bash_param["activeControl"] == "NestedEnumControl"
    assert set(pipeline_def_operation_bash_param["NestedEnumControl"].keys()) == {"value", "option"}
    assert pipeline_def_operation_bash_param["NestedEnumControl"]["value"] == upstream_task_id

    ordered_operations = processor._cc_pipeline(
        parsed_pipeline, pipeline_name="some-name", pipeline_instance_id="some-instance-name"
    )
    operation_parameters = ordered_operations[task_id]["component_params"]
    operation_parameter_bash_command = operation_parameters["bash_command"]

    assert operation_parameter_bash_command == "\"{{ ti.xcom_pull(task_ids='BashOperator_1') }}\""


def test_scrub_invalid_characters(processor):
    invalid_character_list_string = "[-!@#$%^&*(){};:,/<>?|`~=+ ]"
    valid_character_list_string = list(string.ascii_lowercase + string.ascii_uppercase + string.digits)
    for character in invalid_character_list_string:
        assert processor._scrub_invalid_characters(character) == "_"

    for character in valid_character_list_string:
        assert processor._scrub_invalid_characters(character) == character