Update data-factory.md

Author: msyyc

docs-ref-services/latest/data-factory.md

@@ -8,50 +8,50 @@ ms.topic: reference
 ms.devlang: python
 ms.service: datafactory
 ---
-# Azure Data Factory libraries for Python
-
-Compose data storage, movement, and processing services into automated data pipelines with [Azure Data Factory](/azure/data-factory/)
-
-[Learn more](/azure/data-factory/introduction) about Data Factory and get started with the [Create a data factory and pipeline using Python quickstart](/azure/data-factory/quickstart-create-data-factory-python). 
-
-## Management module
-
-Create and manage Data Factory instances in your subscription with the management module.
-
-### Installation
-
-Install the package with [pip](https://pip.pypa.io/en/stable/quickstart/):
-
-```bash
-pip install azure-mgmt-datafactory 
-```
-
-### Example 
-
-Create a Data Factory in your subscription on the East US region.
-
-```python
-from azure.common.credentials import ServicePrincipalCredentials
-from azure.mgmt.resource import ResourceManagementClient
-from azure.mgmt.datafactory import DataFactoryManagementClient
-from azure.mgmt.datafactory.models import *
-import time
-
-#Create a data factory
-subscription_id = '<Specify your Azure Subscription ID>'
-credentials = ServicePrincipalCredentials(client_id='<Active Directory application/client ID>', secret='<client secret>', tenant='<Active Directory tenant ID>')
-adf_client = DataFactoryManagementClient(credentials, subscription_id)
-
-rg_params = {'location':'eastus'}
-df_params = {'location':'eastus'}  
-
-df_resource = Factory(location='eastus')
-df = adf_client.factories.create_or_update(rg_name, df_name, df_resource)
-print_item(df)
-while df.provisioning_state != 'Succeeded':
-    df = adf_client.factories.get(rg_name, df_name)
-    time.sleep(1)
-```
-
-> [!div class="nextstepaction"]
-> [Explore the Management APIs](/python/api/overview/azure/datafactory/management)
+# Azure Data Factory libraries for Python
+
+Compose data storage, movement, and processing services into automated data pipelines with [Azure Data Factory](/azure/data-factory/)
+
+[Learn more](/azure/data-factory/introduction) about Data Factory and get started with the [Create a data factory and pipeline using Python quickstart](/azure/data-factory/quickstart-create-data-factory-python). 
+
+## Management module
+
+Create and manage Data Factory instances in your subscription with the management module.
+
+### Installation
+
+Install the package with [pip](https://pip.pypa.io/en/stable/quickstart/):
+
+```bash
+pip install azure-mgmt-datafactory 
+```
+
+### Example 
+
+Create a Data Factory in your subscription on the East US region.
+
+```python
+from azure.common.credentials import ServicePrincipalCredentials
+from azure.mgmt.resource import ResourceManagementClient
+from azure.mgmt.datafactory import DataFactoryManagementClient
+from azure.mgmt.datafactory.models import *
+import time
+
+#Create a data factory
+subscription_id = '<Specify your Azure Subscription ID>'
+credentials = ServicePrincipalCredentials(client_id='<Active Directory application/client ID>', secret='<client secret>', tenant='<Active Directory tenant ID>')
+adf_client = DataFactoryManagementClient(credentials, subscription_id)
+
+rg_params = {'location':'eastus'}
+df_params = {'location':'eastus'}  
+
+df_resource = Factory(location='eastus')
+df = adf_client.factories.create_or_update(rg_name, df_name, df_resource)
+print_item(df)
+while df.provisioning_state != 'Succeeded':
+    df = adf_client.factories.get(rg_name, df_name)
+    time.sleep(1)
+```
+
+> [!div class="nextstepaction"]
+> [Explore the Management APIs](/python/api/azure-mgmt-datafactory)