lint: formatted the code with black

Author: praneet22

aml_service/00-WorkSpace.py

@@ -45,7 +45,7 @@
         name=workspace_name,
         subscription_id=subscription_id,
         resource_group=resource_group,
-        auth=cli_auth
+        auth=cli_auth,
     )
 
 except:
@@ -57,8 +57,7 @@
         resource_group=resource_group,
         # create_resource_group=True,
         location=location,
-        auth=cli_auth
-
+        auth=cli_auth,
     )
 
 # print Workspace details

aml_service/01-Experiment.py

@@ -27,8 +27,10 @@
 from azureml.core import Experiment
 from azureml.core import Workspace
 from azureml.core.authentication import AzureCliAuthentication
+
 cli_auth = AzureCliAuthentication()
 
+
 def getExperiment():
     ws = Workspace.from_config(auth=cli_auth)
     script_folder = "."

aml_service/02-AttachTrainingVM.py

@@ -34,6 +34,7 @@
 from azureml.core.compute import DsvmCompute
 from azureml.core.compute_target import ComputeTargetException
 from azureml.core.authentication import AzureCliAuthentication
+
 cli_auth = AzureCliAuthentication()
 
 # Get workspace

aml_service/03-AttachAmlCluster.py

@@ -38,28 +38,29 @@
 with open("aml_config/security_config.json") as f:
     config = json.load(f)
 
-aml_cluster_name = config['aml_cluster_name']
+aml_cluster_name = config["aml_cluster_name"]
 
-# un-comment the below lines if you want to put AML Compute under Vnet. Also update /aml_config/security_config.json 
+# un-comment the below lines if you want to put AML Compute under Vnet. Also update /aml_config/security_config.json
 # vnet_resourcegroup_name = config['vnet_resourcegroup_name']
 # vnet_name = config['vnet_name']
 # subnet_name = config['subnet_name']
 
 # Verify that cluster does not exist already
 try:
     cpu_cluster = ComputeTarget(workspace=ws, name=aml_cluster_name)
-    print('Found existing cluster, use it.')
+    print("Found existing cluster, use it.")
 except ComputeTargetException:
-    compute_config = AmlCompute.provisioning_configuration(vm_size='STANDARD_D2_V2',
-                                                           vm_priority='dedicated',
-                                                           min_nodes=1,
-                                                           max_nodes=3,
-                                                           idle_seconds_before_scaledown='300',
-                                                        #    #Uncomment the below lines for VNet support                                                        
-                                                        #    vnet_resourcegroup_name=vnet_resourcegroup_name,
-                                                        #    vnet_name=vnet_name,
-                                                        #    subnet_name=subnet_name
-                                                           )
+    compute_config = AmlCompute.provisioning_configuration(
+        vm_size="STANDARD_D2_V2",
+        vm_priority="dedicated",
+        min_nodes=1,
+        max_nodes=3,
+        idle_seconds_before_scaledown="300",
+        #    #Uncomment the below lines for VNet support
+        #    vnet_resourcegroup_name=vnet_resourcegroup_name,
+        #    vnet_name=vnet_name,
+        #    subnet_name=subnet_name
+    )
     cpu_cluster = ComputeTarget.create(ws, aml_cluster_name, compute_config)
 
-cpu_cluster.wait_for_completion(show_output=True)
+cpu_cluster.wait_for_completion(show_output=True)

aml_service/10-TrainOnLocal.py

@@ -30,6 +30,7 @@
 from azureml.core import ScriptRunConfig
 import json
 from azureml.core.authentication import AzureCliAuthentication
+
 cli_auth = AzureCliAuthentication()
 
 # Get workspace

aml_service/11-TrainOnLocalEnv.py

@@ -33,6 +33,7 @@
 from azureml.core import ScriptRunConfig
 
 from azureml.core.authentication import AzureCliAuthentication
+
 cli_auth = AzureCliAuthentication()
 
 # Get workspace

aml_service/15-EvaluateModel.py

@@ -30,6 +30,7 @@
 import azureml.core
 from azureml.core import Run
 from azureml.core.authentication import AzureCliAuthentication
+
 cli_auth = AzureCliAuthentication()
 
 # Get workspace

aml_service/20-RegisterModel.py

@@ -31,6 +31,7 @@
 
 from azureml.core.runconfig import RunConfiguration
 from azureml.core.authentication import AzureCliAuthentication
+
 cli_auth = AzureCliAuthentication()
 
 # Get workspace

aml_service/50-deployOnAci.py

@@ -34,7 +34,7 @@
 
 cli_auth = AzureCliAuthentication()
 # Get workspace
-ws = Workspace.from_config(auth=cli_auth)# Get the Image to deploy details
+ws = Workspace.from_config(auth=cli_auth)  # Get the Image to deploy details
 try:
     with open("aml_config/image.json") as f:
         config = json.load(f)

tests/unit/data_test.py

@@ -33,8 +33,10 @@
 def get_absPath(filename):
     """Returns the path of the notebooks folder"""
     path = os.path.abspath(
-        os.path.join(os.path.dirname(__file__), os.path.pardir, 
-                     os.path.pardir, "data", filename))
+        os.path.join(
+            os.path.dirname(__file__), os.path.pardir, os.path.pardir, "data", filename
+        )
+    )
     return path
 
 
@@ -81,42 +83,42 @@ def get_absPath(filename):
 def test_check_schema():
     datafile = get_absPath("diabetes.csv")
     # check that file exists
-    assert(os.path.exists(datafile))
+    assert os.path.exists(datafile)
     dataset = pd.read_csv(datafile)
     header = dataset[dataset.columns[:-1]]
     actual_columns = header.shape[1]
     # check header has expected number of columns
-    assert(actual_columns == expected_columns)
+    assert actual_columns == expected_columns
 
 
 def test_check_bad_schema():
     datafile = get_absPath("diabetes_bad_schema.csv")
     # check that file exists
-    assert(os.path.exists(datafile))
+    assert os.path.exists(datafile)
     dataset = pd.read_csv(datafile)
     header = dataset[dataset.columns[:-1]]
     actual_columns = header.shape[1]
     # check header has expected number of columns
-    assert(actual_columns != expected_columns)
+    assert actual_columns != expected_columns
 
 
 def test_check_missing_values():
     datafile = get_absPath("diabetes_missing_values.csv")
     # check that file exists
-    assert(os.path.exists(datafile))
+    assert os.path.exists(datafile)
     dataset = pd.read_csv(datafile)
     n_nan = np.sum(np.isnan(dataset.values))
-    assert(n_nan > 0)
+    assert n_nan > 0
 
 
 def test_check_distribution():
     datafile = get_absPath("diabetes_bad_dist.csv")
     # check that file exists
-    assert(os.path.exists(datafile))
+    assert os.path.exists(datafile)
     dataset = pd.read_csv(datafile)
     mean = np.mean(dataset.values, axis=0)
     std = np.mean(dataset.values, axis=0)
-    assert(np.sum(abs(mean - historical_mean) > shift_tolerance *
-                  abs(historical_mean)) or
-           np.sum(abs(std - historical_std) > shift_tolerance * 
-                  abs(historical_std)) > 0)
+    assert (
+        np.sum(abs(mean - historical_mean) > shift_tolerance * abs(historical_mean))
+        or np.sum(abs(std - historical_std) > shift_tolerance * abs(historical_std)) > 0
+    )