def make_flow(obj,
token,
name,
tags,
namespace,
max_workers,
workflow_timeout,
is_project):
datastore = obj.datastore(obj.flow.name,
mode='w',
metadata=obj.metadata,
event_logger=obj.event_logger,
monitor=obj.monitor)
if datastore.TYPE != 's3':
raise MetaflowException("AWS Step Functions requires --datastore=s3.")
# Attach AWS Batch decorator to the flow
decorators._attach_decorators(obj.flow, [BatchDecorator.name])
decorators._init_step_decorators(
obj.flow, obj.graph, obj.environment, obj.datastore, obj.logger)
obj.package = MetaflowPackage(
obj.flow, obj.environment, obj.echo, obj.package_suffixes)
package_url = datastore.save_data(
obj.package.sha, TransformableObject(obj.package.blob))
return StepFunctions(name,
obj.graph,
obj.flow,
obj.package,
package_url,
token,
obj.metadata,
obj.datastore,
obj.environment,
obj.event_logger,
obj.monitor,
tags=tags,
namespace=namespace,
max_workers=max_workers,
username=get_username(),
workflow_timeout=workflow_timeout,
is_project=is_project)
def _save_package_once(cls, datastore, package):
if cls.package_url is None:
cls.package_url = datastore.save_data(
package.sha, TransformableObject(package.blob))
cls.package_sha = package.sha
