Generated ADF pipelibe using Python

Question

Hello,

I am working on the dynamic data pipeline framework were i can generate Azure data pipeline programatically. till now, i have done for creating copy activiyt and dataflow. the final step is, need to link between this two by creating another pipeline. for ex: dataflow(reads config info from database) and copy activity perform based on the config.

Kindly help, how to create new pipeline by attaching dataflow and copyactivity

Answer 1

You'll first need to have the azure-mgmt-datafactory package installed. Install it using pip if you haven't:

     pip install azure-mgmt-datafactory

Then you will need to authenticate against the Azure subscription where your Data Factory resides.

   from azure.identity import DefaultAzureCredential
   from azure.mgmt.datafactory import DataFactoryManagementClient
   resource_group_name = "your-resource-group-name"
   data_factory_name = "your-data-factory-name"
   location = "your-location"
   subscription_id = "your-subscription-id"
   # Authenticate
   credential = DefaultAzureCredential()
   adf_client = DataFactoryManagementClient(credential, subscription_id)

After initializing, you can start defining the pipeline with linked Dataflow and Copy Activity.

   from azure.mgmt.datafactory.models import PipelineResource, CopyActivity, DataFlow
   # Define the Dataflow (replace with your actual Dataflow details)
   dataflow = DataFlow(
       name="your-dataflow-name",
       description="Your Dataflow description",
       folder="Path/to/your/Dataflow"
       # Add other necessary configurations
   )
   # Define the Copy Activity (replace with your actual Copy Activity details)
   copy_activity = CopyActivity(
       name="your-copy-activity-name",
       description="Your Copy Activity description",
       # Add other necessary configurations
   )
   # Create the Pipeline with the above Dataflow and Copy Activity linked
   pipeline = PipelineResource(
       activities=[dataflow, copy_activity],
       description="Your pipeline description"
   )
   # Create the pipeline in Azure Data Factory
   adf_client.pipelines.create_or_update(resource_group_name, data_factory_name, "your-pipeline-name", pipeline)

Try to update the code to adjust it to your needs.