feature: separating sagemaker dependencies into more use case specific installable components.

doc/overview.rst

@@ -661,6 +661,12 @@ For example, the ``dataframe`` method gets a pandas dataframe summarizing the as
     # Look at summary of associated training jobs
     my_dataframe = my_tuner_analytics.dataframe()
 
+You can install all necessary for this feature dependencies using pip:
+
+::
+
+    pip install 'sagemaker[analytics]' --upgrade
+
 For more detailed examples of running hyperparameter tuning jobs, see:
 
 - `Using the TensorFlow estimator with hyperparameter tuning <https://github.com/awslabs/amazon-sagemaker-examples/blob/master/hyperparameter_tuning/tensorflow_mnist/hpo_tensorflow_mnist.ipynb>`__
@@ -718,6 +724,12 @@ The SageMaker Python SDK supports local mode, which allows you to create estimat
 This is a great way to test your deep learning scripts before running them in SageMaker's managed training or hosting environments.
 Local Mode is supported for frameworks images (TensorFlow, MXNet, Chainer, PyTorch, and Scikit-Learn) and images you supply yourself.
 
+You can install all necessary for this feature dependencies using pip:
+
+::
+
+    pip install 'sagemaker[local]' --upgrade
+
 We can take the example in  `Using Estimators <#using-estimators>`__ , and use either ``local`` or ``local_gpu`` as the instance type.
 
 .. code:: python

setup.py

@@ -38,12 +38,40 @@ def read_version():
     "numpy>=1.9.0",
     "protobuf>=3.1",
     "scipy>=0.19.0",
-    "urllib3>=1.21, <1.25",
+    "urllib3>=1.21, <1.25",  # local mode dependencies -> remove in the next release
     "protobuf3-to-dict>=0.1.5",
     "requests>=2.20.0, <2.21",
-    "fabric>=2.0",
+    "docker-compose>=1.23.0",  # local mode dependencies -> remove in the next release
 ]
 
+# Specific use case dependencies
+extras = {
+    "analytics": ["pandas"],
+    "local": ["urllib3>=1.21, <1.25", "docker-compose>=1.23.0"],
+    "tensorflow": ["tensorflow>=1.3.0"],
+}
+# Meta dependency groups
+extras["all"] = [item for group in extras.values() for item in group]
+# Tests specific dependencies (do not need to be included in 'all')
+extras["test"] = (
+    [
+        extras["all"],
+        "tox==3.13.1",
+        "flake8",
+        "pytest==4.4.1",
+        "pytest-cov",
+        "pytest-rerunfailures",
+        "pytest-xdist",
+        "mock",
+        "contextlib2",
+        "awslogs",
+        "black==19.3b0 ; python_version >= '3.6'",
+        "stopit==1.1.2",
+        "apache-airflow==1.10.5",
+        "fabric>=2.0",
+    ],
+)
+
 # enum is introduced in Python 3.4. Installing enum back port
 if sys.version_info < (3, 4):
     required_packages.append("enum34>=1.1.6")
@@ -70,24 +98,6 @@ def read_version():
         "Programming Language :: Python :: 3.6",
     ],
     install_requires=required_packages,
-    extras_require={
-        "test": [
-            "tox==3.13.1",
-            "flake8",
-            "pytest==4.4.1",
-            "pytest-cov",
-            "pytest-rerunfailures",
-            "pytest-xdist",
-            "mock",
-            "tensorflow>=1.3.0",
-            "contextlib2",
-            "awslogs",
-            "pandas",
-            "black==19.3b0 ; python_version >= '3.6'",
-            "stopit==1.1.2",
-            "apache-airflow==1.10.5",
-            "docker-compose>=1.23.0",
-        ]
-    },
+    extras_require=extras,
     entry_points={"console_scripts": ["sagemaker=sagemaker.cli.main:main"]},
 )

src/sagemaker/local/entities.py

@@ -19,12 +19,19 @@
 import os
 import tempfile
 import time
-import urllib3
 
 import sagemaker.local.data
 from sagemaker.local.image import _SageMakerContainer
 from sagemaker.local.utils import copy_directory_structure, move_to_destination
-from sagemaker.utils import get_config_value
+from sagemaker.utils import DeferredError, get_config_value
+
+try:
+    import urllib3
+except ImportError as e:
+    logging.warning("urllib3 failed to import. Local mode features will be impaired or broken.")
+    # Any subsequent attempt to use urllib3 will raise the ImportError
+    urllib3 = DeferredError(e)
+
 
 logger = logging.getLogger(__name__)
 

src/sagemaker/local/local_session.py

@@ -17,7 +17,6 @@
 import platform
 
 import boto3
-import urllib3
 from botocore.exceptions import ClientError
 
 from sagemaker.local.image import _SageMakerContainer
@@ -29,7 +28,14 @@
     _LocalTransformJob,
 )
 from sagemaker.session import Session
-from sagemaker.utils import get_config_value
+from sagemaker.utils import DeferredError, get_config_value
+
+try:
+    import urllib3
+except ImportError as e:
+    logging.warning("urllib3 failed to import. Local mode features will be impaired or broken.")
+    # Any subsequent attempt to use urllib3 will raise the ImportError
+    urllib3 = DeferredError(e)
 
 logger = logging.getLogger(__name__)