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check credential before call spark.read.mltable() #3688

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check credential before call spark.read.mltable() #3688

check credential before call spark.read.mltable()
ec0e8a1
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GitHub Actions / Test Results for model-monitoring-ci failed Dec 17, 2024 in 0s

3 fail, 11 skipped, 112 pass in 2m 15s

126 tests   112 ✅  2m 15s ⏱️
  2 suites   11 💤
  2 files      3 ❌

Results for commit ec0e8a1.

Annotations

Check warning on line 0 in tests.unit.test_mdc_preprocessor.TestMDCPreprocessor

See this annotation in the file changed.

@github-actions github-actions / Test Results for model-monitoring-ci

test_uri_folder_to_spark_df_no_data[2023-11-03T15:00:00-2023-11-03T16:00:00] (tests.unit.test_mdc_preprocessor.TestMDCPreprocessor) failed 

results/group_3_junit3.xml [took 12s]
Raw output 
shared_utilities.momo_exceptions.InvalidInputError: Unsecure credential-less data is not supported. Please use either a secure or a credential url for the StoreUrl.
self = <test_mdc_preprocessor.TestMDCPreprocessor object at 0x7fe33938d2b0>
mdc_preprocessor_test_setup = None, window_start_time = '2023-11-03T15:00:00'
window_end_time = '2023-11-03T16:00:00'

    @pytest.mark.parametrize(
        "window_start_time, window_end_time",
        [
            ("2023-11-03T15:00:00", "2023-11-03T16:00:00"),  # no window folder
            ("2023-11-06T15:00:00", "2023-11-06T16:00:00"),  # has window folder, no file
            ("2023-11-06T17:00:00", "2023-11-06T18:00:00"),  # has window folder and file, but empty file
        ]
    )
    def test_uri_folder_to_spark_df_no_data(self, mdc_preprocessor_test_setup,
                                            window_start_time, window_end_time):
        """Test uri_folder_to_spark_df()."""
        def my_add_tags(tags: dict):
            print("my_add_tags:", tags)
        print("testing test_uri_folder_to_spark_df...")
        print("working dir:", os.getcwd())
    
        fs = fsspec.filesystem("file")
        tests_path = os.path.abspath(f"{os.path.dirname(__file__)}/../../tests")
        preprocessed_output = f"{tests_path}/unit/preprocessed_mdc_data"
        shutil.rmtree(f"{preprocessed_output}temp", True)
        root_folder = f"{tests_path}/unit/raw_mdc_data/"
    
        with pytest.raises(DataNotFoundError):
>           df = _raw_mdc_uri_folder_to_preprocessed_spark_df(
                window_start_time,
                window_end_time,
                root_folder,
                preprocessed_output,
                False,
                fs,
                my_add_tags
            )

/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/tests/unit/test_mdc_preprocessor.py:154: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/model_data_collector_preprocessor/run.py:278: in _raw_mdc_uri_folder_to_preprocessed_spark_df
    df = _convert_mltable_to_spark_df(table, preprocessed_input_data, fs, add_tags_func)
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/model_data_collector_preprocessor/run.py:156: in _convert_mltable_to_spark_df
    return try_read_mltable_in_spark_with_error(des_path, "preprocessed_data")
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:68: in try_read_mltable_in_spark_with_error
    return try_read_mltable_in_spark(mltable_path, input_name, NoDataApproach.ERROR)
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:126: in try_read_mltable_in_spark
    raise error
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:111: in try_read_mltable_in_spark
    df = read_mltable_in_spark(mltable_path)
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:150: in read_mltable_in_spark
    store_url.get_credential(True)  # will raise exception if not able to access
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/store_url.py:112: in get_credential
    return valid_aml_obo_credential()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    def valid_aml_obo_credential():
        """Validate AzureMLOnBehalfOfCredential can be used in the environment before returns it."""
        if not self._is_secure():
>           raise InvalidInputError(
                "Unsecure credential-less data is not supported. "
                "Please use either a secure or a credential url for the StoreUrl.")
E           shared_utilities.momo_exceptions.InvalidInputError: Unsecure credential-less data is not supported. Please use either a secure or a credential url for the StoreUrl.

/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/store_url.py:93: InvalidInputError

Check warning on line 0 in tests.unit.test_mdc_preprocessor.TestMDCPreprocessor

See this annotation in the file changed.

@github-actions github-actions / Test Results for model-monitoring-ci

test_uri_folder_to_spark_df_no_data[2023-11-06T17:00:00-2023-11-06T18:00:00] (tests.unit.test_mdc_preprocessor.TestMDCPreprocessor) failed 

results/group_3_junit3.xml [took 12s]
Raw output 
shared_utilities.momo_exceptions.InvalidInputError: Unsecure credential-less data is not supported. Please use either a secure or a credential url for the StoreUrl.
self = <test_mdc_preprocessor.TestMDCPreprocessor object at 0x7f90f4bd7550>
mdc_preprocessor_test_setup = None, window_start_time = '2023-11-06T17:00:00'
window_end_time = '2023-11-06T18:00:00'

    @pytest.mark.parametrize(
        "window_start_time, window_end_time",
        [
            ("2023-11-03T15:00:00", "2023-11-03T16:00:00"),  # no window folder
            ("2023-11-06T15:00:00", "2023-11-06T16:00:00"),  # has window folder, no file
            ("2023-11-06T17:00:00", "2023-11-06T18:00:00"),  # has window folder and file, but empty file
        ]
    )
    def test_uri_folder_to_spark_df_no_data(self, mdc_preprocessor_test_setup,
                                            window_start_time, window_end_time):
        """Test uri_folder_to_spark_df()."""
        def my_add_tags(tags: dict):
            print("my_add_tags:", tags)
        print("testing test_uri_folder_to_spark_df...")
        print("working dir:", os.getcwd())
    
        fs = fsspec.filesystem("file")
        tests_path = os.path.abspath(f"{os.path.dirname(__file__)}/../../tests")
        preprocessed_output = f"{tests_path}/unit/preprocessed_mdc_data"
        shutil.rmtree(f"{preprocessed_output}temp", True)
        root_folder = f"{tests_path}/unit/raw_mdc_data/"
    
        with pytest.raises(DataNotFoundError):
>           df = _raw_mdc_uri_folder_to_preprocessed_spark_df(
                window_start_time,
                window_end_time,
                root_folder,
                preprocessed_output,
                False,
                fs,
                my_add_tags
            )

/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/tests/unit/test_mdc_preprocessor.py:154: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/model_data_collector_preprocessor/run.py:278: in _raw_mdc_uri_folder_to_preprocessed_spark_df
    df = _convert_mltable_to_spark_df(table, preprocessed_input_data, fs, add_tags_func)
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/model_data_collector_preprocessor/run.py:156: in _convert_mltable_to_spark_df
    return try_read_mltable_in_spark_with_error(des_path, "preprocessed_data")
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:68: in try_read_mltable_in_spark_with_error
    return try_read_mltable_in_spark(mltable_path, input_name, NoDataApproach.ERROR)
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:126: in try_read_mltable_in_spark
    raise error
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:111: in try_read_mltable_in_spark
    df = read_mltable_in_spark(mltable_path)
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:150: in read_mltable_in_spark
    store_url.get_credential(True)  # will raise exception if not able to access
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/store_url.py:112: in get_credential
    return valid_aml_obo_credential()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    def valid_aml_obo_credential():
        """Validate AzureMLOnBehalfOfCredential can be used in the environment before returns it."""
        if not self._is_secure():
>           raise InvalidInputError(
                "Unsecure credential-less data is not supported. "
                "Please use either a secure or a credential url for the StoreUrl.")
E           shared_utilities.momo_exceptions.InvalidInputError: Unsecure credential-less data is not supported. Please use either a secure or a credential url for the StoreUrl.

/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/store_url.py:93: InvalidInputError

Check warning on line 0 in tests.unit.test_mdc_preprocessor.TestMDCPreprocessor

See this annotation in the file changed.

@github-actions github-actions / Test Results for model-monitoring-ci

test_uri_folder_to_spark_df_no_data[2023-11-06T15:00:00-2023-11-06T16:00:00] (tests.unit.test_mdc_preprocessor.TestMDCPreprocessor) failed 

results/group_3_junit3.xml [took 8s]
Raw output 
shared_utilities.momo_exceptions.InvalidInputError: Unsecure credential-less data is not supported. Please use either a secure or a credential url for the StoreUrl.
self = <test_mdc_preprocessor.TestMDCPreprocessor object at 0x7fe33938d190>
mdc_preprocessor_test_setup = None, window_start_time = '2023-11-06T15:00:00'
window_end_time = '2023-11-06T16:00:00'

    @pytest.mark.parametrize(
        "window_start_time, window_end_time",
        [
            ("2023-11-03T15:00:00", "2023-11-03T16:00:00"),  # no window folder
            ("2023-11-06T15:00:00", "2023-11-06T16:00:00"),  # has window folder, no file
            ("2023-11-06T17:00:00", "2023-11-06T18:00:00"),  # has window folder and file, but empty file
        ]
    )
    def test_uri_folder_to_spark_df_no_data(self, mdc_preprocessor_test_setup,
                                            window_start_time, window_end_time):
        """Test uri_folder_to_spark_df()."""
        def my_add_tags(tags: dict):
            print("my_add_tags:", tags)
        print("testing test_uri_folder_to_spark_df...")
        print("working dir:", os.getcwd())
    
        fs = fsspec.filesystem("file")
        tests_path = os.path.abspath(f"{os.path.dirname(__file__)}/../../tests")
        preprocessed_output = f"{tests_path}/unit/preprocessed_mdc_data"
        shutil.rmtree(f"{preprocessed_output}temp", True)
        root_folder = f"{tests_path}/unit/raw_mdc_data/"
    
        with pytest.raises(DataNotFoundError):
>           df = _raw_mdc_uri_folder_to_preprocessed_spark_df(
                window_start_time,
                window_end_time,
                root_folder,
                preprocessed_output,
                False,
                fs,
                my_add_tags
            )

/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/tests/unit/test_mdc_preprocessor.py:154: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/model_data_collector_preprocessor/run.py:278: in _raw_mdc_uri_folder_to_preprocessed_spark_df
    df = _convert_mltable_to_spark_df(table, preprocessed_input_data, fs, add_tags_func)
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/model_data_collector_preprocessor/run.py:156: in _convert_mltable_to_spark_df
    return try_read_mltable_in_spark_with_error(des_path, "preprocessed_data")
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:68: in try_read_mltable_in_spark_with_error
    return try_read_mltable_in_spark(mltable_path, input_name, NoDataApproach.ERROR)
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:126: in try_read_mltable_in_spark
    raise error
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:111: in try_read_mltable_in_spark
    df = read_mltable_in_spark(mltable_path)
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/io_utils.py:150: in read_mltable_in_spark
    store_url.get_credential(True)  # will raise exception if not able to access
/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/store_url.py:112: in get_credential
    return valid_aml_obo_credential()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    def valid_aml_obo_credential():
        """Validate AzureMLOnBehalfOfCredential can be used in the environment before returns it."""
        if not self._is_secure():
>           raise InvalidInputError(
                "Unsecure credential-less data is not supported. "
                "Please use either a secure or a credential url for the StoreUrl.")
E           shared_utilities.momo_exceptions.InvalidInputError: Unsecure credential-less data is not supported. Please use either a secure or a credential url for the StoreUrl.

/home/runner/work/azureml-assets/azureml-assets/assets/model_monitoring/components/src/shared_utilities/store_url.py:93: InvalidInputError
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