feat: add support for HTTPS URI pipeline templates (#1683)

First-party pipelines are not yet available in AR, meaning other than using a local file, the only way to access a first-party pipeline is using its GitHub URI. Since support was added for AR URIs, it is not much more effort to support general HTTPS URIs. - [x] Make sure to open an issue as a [bug/issue](https://github.com/googleapis/python-aiplatform/issues/new/choose) before writing your code! That way we can discuss the change, evaluate designs, and agree on the general idea - [x] Ensure the tests and linter pass - [x] Code coverage does not decrease (if any source code was changed) - [x] Appropriate docs were updated (if necessary) Fixes b/247878583 🦕
googleapis · Sep 26, 2022 · 926d0b6 · 926d0b6
1 parent 2a906c8
commit 926d0b6
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Showing 5 changed files with 166 additions and 42 deletions.
diff --git a/google/cloud/aiplatform/constants/pipeline.py b/google/cloud/aiplatform/constants/pipeline.py
@@ -33,10 +33,13 @@
 _PIPELINE_ERROR_STATES = set([gca_pipeline_state.PipelineState.PIPELINE_STATE_FAILED])
 
 # Pattern for valid names used as a Vertex resource name.
-_VALID_NAME_PATTERN = re.compile("^[a-z][-a-z0-9]{0,127}$")
+_VALID_NAME_PATTERN = re.compile("^[a-z][-a-z0-9]{0,127}$", re.IGNORECASE)
 
 # Pattern for an Artifact Registry URL.
-_VALID_AR_URL = re.compile(r"^https:\/\/([\w-]+)-kfp\.pkg\.dev\/.*")
+_VALID_AR_URL = re.compile(r"^https:\/\/([\w-]+)-kfp\.pkg\.dev\/.*", re.IGNORECASE)
+
+# Pattern for any JSON or YAML file over HTTPS.
+_VALID_HTTPS_URL = re.compile(r"^https:\/\/([\.\/\w-]+)\/.*(json|yaml|yml)$")
 
 # Fields to include in returned PipelineJob when enable_simple_view=True in PipelineJob.list()
 _READ_MASK_FIELDS = [

diff --git a/google/cloud/aiplatform/pipeline_jobs.py b/google/cloud/aiplatform/pipeline_jobs.py
@@ -57,6 +57,9 @@
 # Pattern for an Artifact Registry URL.
 _VALID_AR_URL = pipeline_constants._VALID_AR_URL
 
+# Pattern for any JSON or YAML file over HTTPS.
+_VALID_HTTPS_URL = pipeline_constants._VALID_HTTPS_URL
+
 _READ_MASK_FIELDS = pipeline_constants._READ_MASK_FIELDS
 
 
@@ -131,8 +134,8 @@ def __init__(
             template_path (str):
                 Required. The path of PipelineJob or PipelineSpec JSON or YAML file. It
                 can be a local path, a Google Cloud Storage URI (e.g. "gs://project.name"),
-                or an Artifact Registry URI (e.g.
-                "https://us-central1-kfp.pkg.dev/proj/repo/pack/latest").
+                an Artifact Registry URI (e.g.
+                "https://us-central1-kfp.pkg.dev/proj/repo/pack/latest"), or an HTTPS URI.
             job_id (str):
                 Optional. The unique ID of the job run.
                 If not specified, pipeline name + timestamp will be used.
@@ -277,7 +280,7 @@ def __init__(
             ),
         }
 
-        if _VALID_AR_URL.match(template_path):
+        if _VALID_AR_URL.match(template_path) or _VALID_HTTPS_URL.match(template_path):
             pipeline_job_args["template_uri"] = template_path
 
         self._gca_resource = gca_pipeline_job.PipelineJob(**pipeline_job_args)

diff --git a/google/cloud/aiplatform/utils/yaml_utils.py b/google/cloud/aiplatform/utils/yaml_utils.py
@@ -13,18 +13,21 @@
 # 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 re
+from types import ModuleType
 from typing import Any, Dict, Optional
 from urllib import request
 
 from google.auth import credentials as auth_credentials
 from google.auth import transport
 from google.cloud import storage
+from google.cloud.aiplatform.constants import pipeline as pipeline_constants
 
 # Pattern for an Artifact Registry URL.
-_VALID_AR_URL = re.compile(r"^https:\/\/([\w-]+)-kfp\.pkg\.dev\/.*")
+_VALID_AR_URL = pipeline_constants._VALID_AR_URL
+
+# Pattern for any JSON or YAML file over HTTPS.
+_VALID_HTTPS_URL = pipeline_constants._VALID_HTTPS_URL
 
 
 def load_yaml(
@@ -36,8 +39,8 @@ def load_yaml(
 
     Args:
       path (str):
-          Required. The path of the YAML document in Google Cloud Storage or
-          local.
+          Required. The path of the YAML document. It can be a local path, a
+          Google Cloud Storage URI, an Artifact Registry URI, or an HTTPS URI.
       project (str):
           Optional. Project to initiate the Storage client with.
       credentials (auth_credentials.Credentials):
@@ -48,12 +51,31 @@ def load_yaml(
     """
     if path.startswith("gs://"):
         return _load_yaml_from_gs_uri(path, project, credentials)
-    elif _VALID_AR_URL.match(path):
-        return _load_yaml_from_ar_uri(path, credentials)
+    elif path.startswith("http://") or path.startswith("https://"):
+        if _VALID_AR_URL.match(path) or _VALID_HTTPS_URL.match(path):
+            return _load_yaml_from_https_uri(path, credentials)
+        else:
+            raise ValueError(
+                "Invalid HTTPS URI. If not using Artifact Registry, please "
+                "ensure the URI ends with .json, .yaml, or .yml."
+            )
     else:
         return _load_yaml_from_local_file(path)
 
 
+def _maybe_import_yaml() -> ModuleType:
+    """Tries to import the PyYAML module."""
+    try:
+        import yaml
+    except ImportError:
+        raise ImportError(
+            "PyYAML is not installed and is required to parse PipelineJob or "
+            'PipelineSpec files. Please install the SDK using "pip install '
+            'google-cloud-aiplatform[pipelines]"'
+        )
+    return yaml
+
+
 def _load_yaml_from_gs_uri(
     uri: str,
     project: Optional[str] = None,
@@ -72,13 +94,7 @@ def _load_yaml_from_gs_uri(
     Returns:
       A Dict object representing the YAML document.
     """
-    try:
-        import yaml
-    except ImportError:
-        raise ImportError(
-            "pyyaml is not installed and is required to parse PipelineJob or PipelineSpec files. "
-            'Please install the SDK using "pip install google-cloud-aiplatform[pipelines]"'
-        )
+    yaml = _maybe_import_yaml()
     storage_client = storage.Client(project=project, credentials=credentials)
     blob = storage.Blob.from_string(uri, storage_client)
     return yaml.safe_load(blob.download_as_bytes())
@@ -94,39 +110,27 @@ def _load_yaml_from_local_file(file_path: str) -> Dict[str, Any]:
     Returns:
       A Dict object representing the YAML document.
     """
-    try:
-        import yaml
-    except ImportError:
-        raise ImportError(
-            "pyyaml is not installed and is required to parse PipelineJob or PipelineSpec files. "
-            'Please install the SDK using "pip install google-cloud-aiplatform[pipelines]"'
-        )
+    yaml = _maybe_import_yaml()
     with open(file_path) as f:
         return yaml.safe_load(f)
 
 
-def _load_yaml_from_ar_uri(
+def _load_yaml_from_https_uri(
     uri: str,
     credentials: Optional[auth_credentials.Credentials] = None,
 ) -> Dict[str, Any]:
     """Loads data from a YAML document referenced by a Artifact Registry URI.
 
     Args:
-      path (str):
+      uri (str):
           Required. Artifact Registry URI for YAML document.
       credentials (auth_credentials.Credentials):
           Optional. Credentials to use with Artifact Registry.
 
     Returns:
       A Dict object representing the YAML document.
     """
-    try:
-        import yaml
-    except ImportError:
-        raise ImportError(
-            "pyyaml is not installed and is required to parse PipelineJob or PipelineSpec files. "
-            'Please install the SDK using "pip install google-cloud-aiplatform[pipelines]"'
-        )
+    yaml = _maybe_import_yaml()
     req = request.Request(uri)
 
     if credentials:

diff --git a/tests/unit/aiplatform/test_pipeline_jobs.py b/tests/unit/aiplatform/test_pipeline_jobs.py
@@ -60,6 +60,7 @@
 
 _TEST_TEMPLATE_PATH = f"gs://{_TEST_GCS_BUCKET_NAME}/job_spec.json"
 _TEST_AR_TEMPLATE_PATH = "https://us-central1-kfp.pkg.dev/proj/repo/pack/latest"
+_TEST_HTTPS_TEMPLATE_PATH = "https://raw.githubusercontent.com/repo/pipeline.json"
 _TEST_PARENT = f"projects/{_TEST_PROJECT}/locations/{_TEST_LOCATION}"
 _TEST_NETWORK = f"projects/{_TEST_PROJECT}/global/networks/{_TEST_PIPELINE_JOB_ID}"
 
@@ -627,6 +628,88 @@ def test_run_call_pipeline_service_create_artifact_registry(
             gca_pipeline_state.PipelineState.PIPELINE_STATE_SUCCEEDED
         )
 
+    @pytest.mark.parametrize(
+        "job_spec",
+        [_TEST_PIPELINE_SPEC_JSON, _TEST_PIPELINE_SPEC_YAML, _TEST_PIPELINE_JOB],
+    )
+    @pytest.mark.parametrize("sync", [True, False])
+    def test_run_call_pipeline_service_create_https(
+        self,
+        mock_pipeline_service_create,
+        mock_pipeline_service_get,
+        mock_pipeline_bucket_exists,
+        mock_request_urlopen,
+        job_spec,
+        mock_load_yaml_and_json,
+        sync,
+    ):
+        import yaml
+
+        aiplatform.init(
+            project=_TEST_PROJECT,
+            staging_bucket=_TEST_GCS_BUCKET_NAME,
+            location=_TEST_LOCATION,
+            credentials=_TEST_CREDENTIALS,
+        )
+
+        job = pipeline_jobs.PipelineJob(
+            display_name=_TEST_PIPELINE_JOB_DISPLAY_NAME,
+            template_path=_TEST_HTTPS_TEMPLATE_PATH,
+            job_id=_TEST_PIPELINE_JOB_ID,
+            parameter_values=_TEST_PIPELINE_PARAMETER_VALUES,
+            enable_caching=True,
+        )
+
+        job.run(
+            service_account=_TEST_SERVICE_ACCOUNT,
+            network=_TEST_NETWORK,
+            sync=sync,
+            create_request_timeout=None,
+        )
+
+        if not sync:
+            job.wait()
+
+        expected_runtime_config_dict = {
+            "gcsOutputDirectory": _TEST_GCS_BUCKET_NAME,
+            "parameterValues": _TEST_PIPELINE_PARAMETER_VALUES,
+        }
+        runtime_config = gca_pipeline_job.PipelineJob.RuntimeConfig()._pb
+        json_format.ParseDict(expected_runtime_config_dict, runtime_config)
+
+        job_spec = yaml.safe_load(job_spec)
+        pipeline_spec = job_spec.get("pipelineSpec") or job_spec
+
+        # Construct expected request
+        expected_gapic_pipeline_job = gca_pipeline_job.PipelineJob(
+            display_name=_TEST_PIPELINE_JOB_DISPLAY_NAME,
+            pipeline_spec={
+                "components": {},
+                "pipelineInfo": pipeline_spec["pipelineInfo"],
+                "root": pipeline_spec["root"],
+                "schemaVersion": "2.1.0",
+            },
+            runtime_config=runtime_config,
+            service_account=_TEST_SERVICE_ACCOUNT,
+            network=_TEST_NETWORK,
+            template_uri=_TEST_HTTPS_TEMPLATE_PATH,
+        )
+
+        mock_pipeline_service_create.assert_called_once_with(
+            parent=_TEST_PARENT,
+            pipeline_job=expected_gapic_pipeline_job,
+            pipeline_job_id=_TEST_PIPELINE_JOB_ID,
+            timeout=None,
+        )
+
+        mock_pipeline_service_get.assert_called_with(
+            name=_TEST_PIPELINE_JOB_NAME, retry=base._DEFAULT_RETRY
+        )
+
+        assert job._gca_resource == make_pipeline_job(
+            gca_pipeline_state.PipelineState.PIPELINE_STATE_SUCCEEDED
+        )
+
     @pytest.mark.parametrize(
         "job_spec",
         [

diff --git a/tests/unit/aiplatform/test_utils.py b/tests/unit/aiplatform/test_utils.py
@@ -24,7 +24,7 @@
 from typing import Callable, Dict, Optional
 from unittest import mock
 from unittest.mock import patch
-from urllib import request
+from urllib import request as urllib_request
 
 import pytest
 import yaml
@@ -751,15 +751,15 @@ def json_file(tmp_path):
 
 
 @pytest.fixture(scope="function")
-def mock_request_urlopen():
+def mock_request_urlopen(request: str) -> str:
     data = {"key": "val", "list": ["1", 2, 3.0]}
-    with mock.patch.object(request, "urlopen") as mock_urlopen:
+    with mock.patch.object(urllib_request, "urlopen") as mock_urlopen:
         mock_read_response = mock.MagicMock()
         mock_decode_response = mock.MagicMock()
         mock_decode_response.return_value = json.dumps(data)
         mock_read_response.return_value.decode = mock_decode_response
         mock_urlopen.return_value.read = mock_read_response
-        yield "https://us-central1-kfp.pkg.dev/proj/repo/pack/latest"
+        yield request.param
 
 
 class TestYamlUtils:
@@ -773,11 +773,42 @@ def test_load_yaml_from_local_file__with_json(self, json_file):
         expected = {"key": "val", "list": ["1", 2, 3.0]}
         assert actual == expected
 
+    @pytest.mark.parametrize(
+        "mock_request_urlopen",
+        ["https://us-central1-kfp.pkg.dev/proj/repo/pack/latest"],
+        indirect=True,
+    )
     def test_load_yaml_from_ar_uri(self, mock_request_urlopen):
         actual = yaml_utils.load_yaml(mock_request_urlopen)
         expected = {"key": "val", "list": ["1", 2, 3.0]}
         assert actual == expected
 
-    def test_load_yaml_from_invalid_uri(self):
-        with pytest.raises(FileNotFoundError):
-            yaml_utils.load_yaml("https://us-docker.pkg.dev/v2/proj/repo/img/tags/list")
+    @pytest.mark.parametrize(
+        "mock_request_urlopen",
+        [
+            "https://raw.githubusercontent.com/repo/pipeline.json",
+            "https://raw.githubusercontent.com/repo/pipeline.yaml",
+            "https://raw.githubusercontent.com/repo/pipeline.yml",
+        ],
+        indirect=True,
+    )
+    def test_load_yaml_from_https_uri(self, mock_request_urlopen):
+        actual = yaml_utils.load_yaml(mock_request_urlopen)
+        expected = {"key": "val", "list": ["1", 2, 3.0]}
+        assert actual == expected
+
+    @pytest.mark.parametrize(
+        "uri",
+        [
+            "https://us-docker.pkg.dev/v2/proj/repo/img/tags/list",
+            "https://example.com/pipeline.exe",
+            "http://example.com/pipeline.yaml",
+        ],
+    )
+    def test_load_yaml_from_invalid_uri(self, uri: str):
+        message = (
+            "Invalid HTTPS URI. If not using Artifact Registry, please "
+            "ensure the URI ends with .json, .yaml, or .yml."
+        )
+        with pytest.raises(ValueError, match=message):
+            yaml_utils.load_yaml(uri)