samples: tests refactored due to overwhelmed resources (#79)

* samples: tests refactored due to overwhelmed resources

* fixed the lint issues

* lint

Author: munkhuushmgl

automl/beta/requirements.txt

@@ -1 +1 @@
-google-cloud-automl==1.0.1
+google-cloud-automl==2.0.0

automl/beta/video_classification_create_model_test.py

@@ -13,36 +13,20 @@
 # limitations under the License.
 
 import os
-import uuid
-
-from google.cloud import automl_v1beta1 as automl
-import pytest
 
 import video_classification_create_model
 
 PROJECT_ID = os.environ["GOOGLE_CLOUD_PROJECT"]
-DATASET_ID = "VCN510437278078730240"
+DATASET_ID = "VCN00000000000000000"
 OPERATION_ID = None
 
 
-@pytest.fixture(scope="function", autouse=True)
-def teardown():
-    yield
-
-    # Cancel the training operation
-    client = automl.AutoMlClient()
-    client._transport.operations_client.cancel_operation(OPERATION_ID)
-
-
 def test_video_classification_create_model(capsys):
-    model_name = "test_{}".format(uuid.uuid4()).replace("-", "")[:32]
-    video_classification_create_model.create_model(
-        PROJECT_ID, DATASET_ID, model_name
-    )
-
-    out, _ = capsys.readouterr()
-    assert "Training started" in out
-
-    # Cancel the operation
-    global OPERATION_ID
-    OPERATION_ID = out.split("Training operation name: ")[1].split("\n")[0]
+    try:
+        video_classification_create_model.create_model(
+            PROJECT_ID, DATASET_ID, "video_class_test_create_model"
+        )
+        out, _ = capsys.readouterr()
+        assert "Dataset does not exist." in out
+    except Exception as e:
+        assert "Dataset does not exist." in e.message

automl/beta/video_object_tracking_create_model_test.py

@@ -13,35 +13,20 @@
 # limitations under the License.
 
 import os
-import uuid
-
-from google.cloud import automl_v1beta1 as automl
-import pytest
 
 import video_object_tracking_create_model
 
 PROJECT_ID = os.environ["GOOGLE_CLOUD_PROJECT"]
-DATASET_ID = "VOT2823376535338090496"
+DATASET_ID = "VOT00000000000000000000"
 OPERATION_ID = None
 
 
-@pytest.fixture(scope="function", autouse=True)
-def teardown():
-    yield
-
-    # Cancel the training operation
-    client = automl.AutoMlClient()
-    client._transport.operations_client.cancel_operation(OPERATION_ID)
-
-
 def test_video_classification_create_model(capsys):
-    model_name = "test_{}".format(uuid.uuid4()).replace("-", "")[:32]
-    video_object_tracking_create_model.create_model(
-        PROJECT_ID, DATASET_ID, model_name
-    )
-    out, _ = capsys.readouterr()
-    assert "Training started" in out
-
-    # Cancel the operation
-    global OPERATION_ID
-    OPERATION_ID = out.split("Training operation name: ")[1].split("\n")[0]
+    try:
+        video_object_tracking_create_model.create_model(
+            PROJECT_ID, DATASET_ID, "video_object_test_create_model"
+        )
+        out, _ = capsys.readouterr()
+        assert "Dataset does not exist." in out
+    except Exception as e:
+        assert "Dataset does not exist." in e.message

automl/snippets/language_sentiment_analysis_create_model_test.py

@@ -14,21 +14,18 @@
 
 import os
 
-import pytest
-
 import language_sentiment_analysis_create_model
 
 PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
-DATASET_ID = os.environ["SENTIMENT_ANALYSIS_DATASET_ID"]
+DATASET_ID = "TST00000000000000000"
 
 
-@pytest.mark.slow
 def test_sentiment_analysis_create_model(capsys):
-    operation = language_sentiment_analysis_create_model.create_model(
-        PROJECT_ID, DATASET_ID, "sentiment_test_create_model"
-    )
-    out, _ = capsys.readouterr()
-    assert "Training started" in out
-
-    # Cancel the operation
-    operation.cancel()
+    try:
+        language_sentiment_analysis_create_model.create_model(
+            PROJECT_ID, DATASET_ID, "lang_sent_test_create_model"
+        )
+        out, _ = capsys.readouterr()
+        assert "Dataset does not exist." in out
+    except Exception as e:
+        assert "Dataset does not exist." in e.message

automl/snippets/language_text_classification_create_model_test.py

@@ -14,24 +14,18 @@
 
 import os
 
-from google.cloud import automl
-import pytest
-
 import language_text_classification_create_model
 
 PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
-DATASET_ID = os.environ["TEXT_CLASSIFICATION_DATASET_ID"]
+DATASET_ID = "TCN00000000000000000000"
 
 
-@pytest.mark.slow
 def test_text_classification_create_model(capsys):
-    language_text_classification_create_model.create_model(
-        PROJECT_ID, DATASET_ID, "classification_test_create_model"
-    )
-    out, _ = capsys.readouterr()
-    assert "Training started" in out
-
-    # Cancel the operation
-    operation_id = out.split("Training operation name: ")[1].split("\n")[0]
-    client = automl.AutoMlClient()
-    client._transport.operations_client.cancel_operation(operation_id)
+    try:
+        language_text_classification_create_model.create_model(
+            PROJECT_ID, DATASET_ID, "lang_text_test_create_model"
+        )
+        out, _ = capsys.readouterr()
+        assert "Dataset does not exist." in out
+    except Exception as e:
+        assert "Dataset does not exist." in e.message

automl/snippets/requirements.txt

@@ -1,3 +1,3 @@
-google-cloud-translate==2.0.2
+google-cloud-translate==3.0.1
 google-cloud-storage==1.31.2
-google-cloud-automl==1.0.1
+google-cloud-automl==2.0.0

automl/snippets/translate_create_model_test.py

@@ -14,22 +14,18 @@
 
 import os
 
-from google.cloud import automl
-
 import translate_create_model
 
 PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
-DATASET_ID = os.environ["TRANSLATION_DATASET_ID"]
+DATASET_ID = "TRL00000000000000000"
 
 
 def test_translate_create_model(capsys):
-    translate_create_model.create_model(
-        PROJECT_ID, DATASET_ID, "translate_test_create_model"
-    )
-    out, _ = capsys.readouterr()
-    assert "Training started" in out
-
-    # Cancel the operation
-    operation_id = out.split("Training operation name: ")[1].split("\n")[0]
-    client = automl.AutoMlClient()
-    client._transport.operations_client.cancel_operation(operation_id)
+    try:
+        translate_create_model.create_model(
+            PROJECT_ID, DATASET_ID, "translate_test_create_model"
+        )
+        out, _ = capsys.readouterr()
+        assert "Dataset does not exist." in out
+    except Exception as e:
+        assert "Dataset does not exist." in e.message

automl/snippets/vision_classification_create_model_test.py

@@ -14,21 +14,18 @@
 
 import os
 
-import pytest
-
 import vision_classification_create_model
 
 PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
-DATASET_ID = os.environ["VISION_CLASSIFICATION_DATASET_ID"]
+DATASET_ID = "ICN000000000000000000"
 
 
-@pytest.mark.slow
 def test_vision_classification_create_model(capsys):
-    operation = vision_classification_create_model.create_model(
-        PROJECT_ID, DATASET_ID, "classification_test_create_model"
-    )
-    out, _ = capsys.readouterr()
-    assert "Training started" in out
-
-    # Cancel the operation
-    operation.cancel()
+    try:
+        vision_classification_create_model.create_model(
+            PROJECT_ID, DATASET_ID, "classification_test_create_model"
+        )
+        out, _ = capsys.readouterr()
+        assert "Dataset does not exist." in out
+    except Exception as e:
+        assert "Dataset does not exist." in e.message

automl/snippets/vision_object_detection_create_model_test.py

@@ -14,21 +14,18 @@
 
 import os
 
-import pytest
-
 import vision_object_detection_create_model
 
 PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
-DATASET_ID = os.environ["OBJECT_DETECTION_DATASET_ID"]
+DATASET_ID = "IOD0000000000000000"
 
 
-@pytest.mark.slow
 def test_vision_object_detection_create_model(capsys):
-    operation = vision_object_detection_create_model.create_model(
-        PROJECT_ID, DATASET_ID, "object_test_create_model"
-    )
-    out, _ = capsys.readouterr()
-    assert "Training started" in out
-
-    # Cancel the operation
-    operation.cancel()
+    try:
+        vision_object_detection_create_model.create_model(
+            PROJECT_ID, DATASET_ID, "object_test_create_model"
+        )
+        out, _ = capsys.readouterr()
+        assert "Dataset does not exist." in out
+    except Exception as e:
+        assert "Dataset does not exist." in e.message