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@elegant-house-93198 flagging for you

@gentle-translator-17986 you’re correct, this is a snippet of the code that’s causing the issue.

for obj in self._client.list_objects_v2(
                Bucket=self._s3_bucket, Prefix="great_expectations.yml"
            ).get("Contents"):
                if obj.get("Key") == "great_expectations.yml":

What does your current file structure in S3 look like?

@elegant-house-93198 got it got it that's what i thought.. so we don't really have

great_expectations.yml

in our S3 bucket bc that's not really a requirement and we send our data context "on the fly" whenever we do our GE validations using an Airflow Operator. So essentially something like:

from great_expectations.data_context import BaseDataContext

context = BaseDataContext(project_config={
    'datasources': {
        'my_datasource_name': {
            'module_name': 'great_expectations.datasource',
            'class_name': 'Datasource',
            'execution_engine': {
                'module_name': 'great_expectations.execution_engine',
                'class_name': 'PandasExecutionEngine',
            },
            'data_connectors': {
                'my_dataconnector_name': {
                    'module_name': 'great_expectations.datasource.data_connector',
                    'class_name': 'InferredAssetS3DataConnector',
                    'bucket': 'some_bucket',
                    'prefix': 'some_prefix',
                     'default_regex': {
                         "pattern": "(.*)",
                         "group_names": ["data_asset_name"],  # This name is important, not a placeholder
                     }
                },
            },
        }
    },
    ...
})

but i was wondering what do you extract from the

great_expectations.yml

? because i can just put a dummy one in there to avoid the fail integration