Sagemaker output from job name

awswrangler/__init__.py

@@ -17,12 +17,14 @@
 
 class DynamicInstantiate:
 
-    __default_session = Session()
+    __default_session = None
 
     def __init__(self, service):
         self._service = service
 
     def __getattr__(self, name):
+        if DynamicInstantiate.__default_session is None:
+            DynamicInstantiate.__default_session = Session()
         return getattr(getattr(DynamicInstantiate.__default_session, self._service), name)
 
 

awswrangler/exceptions.py

@@ -92,3 +92,7 @@ class InvalidTable(Exception):
 
 class InvalidParameters(Exception):
     pass
+
+
+class AWSCredentialsNotFound(Exception):
+    pass

awswrangler/sagemaker.py

@@ -1,7 +1,9 @@
 import pickle
 import tarfile
 import logging
+
 from typing import Any
+from awswrangler.exceptions import InvalidParameters
 
 logger = logging.getLogger(__name__)
 
@@ -10,18 +12,29 @@ class SageMaker:
     def __init__(self, session):
         self._session = session
         self._client_s3 = session.boto3_session.client(service_name="s3", use_ssl=True, config=session.botocore_config)
+        self._client_sagemaker = session.boto3_session.client(service_name="sagemaker")
 
     @staticmethod
     def _parse_path(path):
         path2 = path.replace("s3://", "")
         parts = path2.partition("/")
         return parts[0], parts[2]
 
-    def get_job_outputs(self, path: str) -> Any:
+    def get_job_outputs(self, job_name: str = None, path: str = None) -> Any:
+
+        if path and job_name:
+            raise InvalidParameters("Specify either path, job_arn or job_name")
+
+        if job_name:
+            path = self._client_sagemaker.describe_training_job(TrainingJobName=job_name)["ModelArtifacts"]["S3ModelArtifacts"]
+
+        if not self._session.s3.does_object_exists(path):
+            return None
 
         bucket, key = SageMaker._parse_path(path)
         if key.split("/")[-1] != "model.tar.gz":
             key = f"{key}/model.tar.gz"
+
         body = self._client_s3.get_object(Bucket=bucket, Key=key)["Body"].read()
         body = tarfile.io.BytesIO(body)  # type: ignore
         tar = tarfile.open(fileobj=body)

awswrangler/session.py

@@ -14,6 +14,7 @@
 from awswrangler.redshift import Redshift
 from awswrangler.emr import EMR
 from awswrangler.sagemaker import SageMaker
+from awswrangler.exceptions import AWSCredentialsNotFound
 
 PYSPARK_INSTALLED = False
 if importlib.util.find_spec("pyspark"):  # type: ignore
@@ -77,6 +78,7 @@ def __init__(self,
         :param athena_kms_key: For SSE-KMS and CSE-KMS , this is the KMS key ARN or ID.
         :param redshift_temp_s3_path: redshift_temp_s3_path: AWS S3 path to write temporary data (e.g. s3://...)
         """
+
         self._profile_name: Optional[str] = (boto3_session.profile_name if boto3_session else profile_name)
         self._aws_access_key_id: Optional[str] = (boto3_session.get_credentials().access_key
                                                   if boto3_session else aws_access_key_id)
@@ -130,8 +132,11 @@ def _load_new_boto3_session(self):
             args["aws_secret_access_key"] = self.aws_secret_access_key
         self._boto3_session = boto3.Session(**args)
         self._profile_name = self._boto3_session.profile_name
-        self._aws_access_key_id = self._boto3_session.get_credentials().access_key
-        self._aws_secret_access_key = self._boto3_session.get_credentials().secret_key
+        credentials = self._boto3_session.get_credentials()
+        if credentials is None:
+            raise AWSCredentialsNotFound("Please run aws configure: https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-configure.html")
+        self._aws_access_key_id = credentials.access_key
+        self._aws_secret_access_key = credentials.secret_key
         self._region_name = self._boto3_session.region_name
 
     def _load_new_primitives(self):

testing/test_awswrangler/test_sagemaker.py

@@ -38,9 +38,9 @@ def bucket(session, cloudformation_outputs):
     session.s3.delete_objects(path=f"s3://{bucket}/")
 
 
-def test_get_job_outputs(session, bucket):
-    model_path = "output"
-    s3 = boto3.resource("s3")
+@pytest.fixture(scope="module")
+def model(bucket):
+    model_path = "output/model.tar.gz"
 
     lr = LinearRegression()
     with open("model.pkl", "wb") as fp:
@@ -49,10 +49,23 @@ def test_get_job_outputs(session, bucket):
     with tarfile.open("model.tar.gz", "w:gz") as tar:
         tar.add("model.pkl")
 
-    s3.Bucket(bucket).upload_file("model.tar.gz", f"{model_path}/model.tar.gz")
-    outputs = session.sagemaker.get_job_outputs(f"{bucket}/{model_path}")
+    s3 = boto3.resource("s3")
+    s3.Bucket(bucket).upload_file("model.tar.gz", model_path)
+
+    yield f"s3://{bucket}/{model_path}"
 
     os.remove("model.pkl")
     os.remove("model.tar.gz")
 
+
+def test_get_job_outputs_by_path(session, model):
+    outputs = session.sagemaker.get_job_outputs(path=model)
     assert type(outputs[0]) == LinearRegression
+
+
+def test_get_job_outputs_by_job_id(session, bucket):
+    pass
+
+
+def test_get_job_outputs_empty(session, bucket):
+    pass