change: require framework_version, py_version for xgboost

src/sagemaker/xgboost/estimator.py

@@ -85,7 +85,7 @@ def __init__(
                 on SageMaker. For convenience, this accepts other types for keys and values, but
                 ``str()`` will be called to convert them before training.
             py_version (str): Python version you want to use for executing your model
-                training code (default: 'py3'). One of 'py2' or 'py3'.
+                training code (default: 'py3').
             image_name (str): If specified, the estimator will use this image for training and
                 hosting, instead of selecting the appropriate SageMaker official image
                 based on framework_version and py_version. It can be an ECR url or

src/sagemaker/xgboost/model.py

@@ -79,7 +79,7 @@ def __init__(
             image (str): A Docker image URI (default: None). If not specified, a default image for
                 XGBoos will be used.
             py_version (str): Python version you want to use for executing your model training code
-                (default: 'py2').
+                (default: 'py3').
             framework_version (str): XGBoost version you want to use for executing your model
                 training code.
             predictor_cls (callable[str, sagemaker.session.Session]): A function to call to create

tests/integ/__init__.py

@@ -23,7 +23,7 @@
 TUNING_DEFAULT_TIMEOUT_MINUTES = 20
 TRANSFORM_DEFAULT_TIMEOUT_MINUTES = 20
 AUTO_ML_DEFAULT_TIMEMOUT_MINUTES = 60
-PYTHON_VERSION = "py" + str(sys.version_info.major)
+PYTHON_VERSION = "py{}".format(sys.version_info.major)
 
 # these regions have some p2 and p3 instances, but not enough for continuous testing
 HOSTING_NO_P2_REGIONS = [

tests/integ/test_airflow_config.py

@@ -582,6 +582,7 @@ def test_tf_airflow_config_uploads_data_source_to_s3(sagemaker_session, cpu_inst
 
 
 @pytest.mark.canary_quick
+@pytest.mark.skipif(PYTHON_VERSION == "py2", reason="XGBoost container does not support Python 2.")
 def test_xgboost_airflow_config_uploads_data_source_to_s3(sagemaker_session, cpu_instance_type):
     with timeout(seconds=AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS):
         xgboost = XGBoost(

tox.ini

@@ -66,6 +66,10 @@ commands =
     {env:IGNORE_COVERAGE:} coverage report --fail-under=86
 extras = test
 
+[testenv:py27]
+setenv =
+    IGNORE_COVERAGE = true
+
 [testenv:flake8]
 basepython = python3
 skipdist = true