Creating an Airflow Operator#

Skyplane can be easily incorporated into an Airflow DAG using a SkyplaneOperator, which can be utilized in data transfer tasks, such as replacing the S3toGCSOperator. The following example demonstrates a data analytics workflow where data is transferred from S3 to GCS to build a BigQuery dataset and then used in a PySpark data analysis job.


In this tutorial, we extend Airflow’s BaseOperator object to create a custom Skyplane operator, called SkyplaneOperator. We first define the fields of the SkyplaneOperator:

import skyplane
from airflow.models import BaseOperator  # type: ignore

class SkyplaneOperator(BaseOperator):
    template_fields = (

    def __init__(
        *src_provider: str,
        src_bucket: str,
        src_region: str,
        dst_provider: str,
        dst_bucket: str,
        dst_region: str,
        aws_config: Optional[skyplane.AWSConfig] = None,
        gcp_config: Optional[skyplane.GCPConfig] = None,
        azure_config: Optional[skyplane.AzureConfig] = None,
    ) -> None:
        self.src_provider = src_provider
        self.src_bucket = src_bucket
        self.src_region = src_region
        self.dst_provider = dst_provider
        self.dst_bucket = dst_bucket
        self.dst_region = dst_region
        self.aws_config = aws_config
        self.gcp_config = gcp_config
        self.azure_config = azure_config

def execute(self, context):

Inside the execute function, we can instantiate a Skyplane client to create a dataplane and execute transfers:

def execute(self, context):
    client = SkyplaneClient(aws_config=self.aws_config, gcp_config=self.gcp_config, azure_config=self.azure_config)
    dp = client.dataplane(self.src_provider, self.src_region, self.dst_provider, self.dst_region, n_vms=1)
    with dp.auto_deprovision():
        dp.queue_copy(self.src_bucket, self.dst_bucket, recursive=True)
        tracker = dp.run_async()

We can also add reporting on the transfer:

    with dp.auto_deprovision():
        print("Waiting for transfer to complete...")
        while True:
            bytes_remaining = tracker.query_bytes_remaining()
            if bytes_remaining is None:
                print(f"{timestamp} Transfer not yet started")
            elif bytes_remaining > 0:
                print(f"{(bytes_remaining / (2 ** 30)):.2f}GB left")
        print("Transfer complete!")