[BUG] Fix StructuredDataset empty-str file_format in dc attr access

flytekit/types/structured/structured_dataset.py

@@ -739,10 +739,31 @@ async def async_to_literal(
             #       return StructuredDataset(uri=uri)
             if python_val.dataframe is None:
                 uri = python_val.uri
+                file_format = python_val.file_format
+
+                # Check the user-specified uri
                 if not uri:
                     raise ValueError(f"If dataframe is not specified, then the uri should be specified. {python_val}")
                 if not ctx.file_access.is_remote(uri):
                     uri = await ctx.file_access.async_put_raw_data(uri)
+
+                # Check the user-specified file_format
+                # When users specify file_format for a StructuredDataset, the file_format should be retained conditionally.
+                # For details, please refer to https://github.com/flyteorg/flyte/issues/6096.
+                # Following illustrates why we can't always copy the user-specified file_format over:
+                #
+                # @task
+                # def modify_format(sd: Annotated[StructuredDataset, {}, "task-format"]) -> StructuredDataset:
+                #     return sd
+                #
+                # sd = StructuredDataset(uri="s3://my-s3-bucket/df.parquet", file_format="user-format")
+                # sd2 = modify_format(sd=sd)
+                #
+                # In this case, we expect sd2.file_format to be task-format (as shown in Annotated), not user-format.
+                # If we directly copy the user-specified file_format over, the type hint information will be missing.
+                if sdt.format == GENERIC_FORMAT and file_format != GENERIC_FORMAT:
+                    sdt.format = file_format
+
                 sd_model = literals.StructuredDataset(
                     uri=uri,
                     metadata=StructuredDatasetMetadata(structured_dataset_type=sdt),

tests/flytekit/integration/remote/test_remote.py

@@ -16,6 +16,7 @@
 import uuid
 import pytest
 from unittest import mock
+from dataclasses import dataclass
 
 from flytekit import LaunchPlan, kwtypes, WorkflowExecutionPhase
 from flytekit.configuration import Config, ImageConfig, SerializationSettings
@@ -27,6 +28,7 @@
 from flytekit.remote.remote import FlyteRemote
 from flyteidl.service import dataproxy_pb2 as _data_proxy_pb2
 from flytekit.types.schema import FlyteSchema
+from flytekit.types.structured import StructuredDataset
 from flytekit.clients.friendly import SynchronousFlyteClient as _SynchronousFlyteClient
 from flytekit.configuration import PlatformConfig
 
@@ -877,6 +879,50 @@ def test_attr_access_sd():
     bucket, key = url.netloc, url.path.lstrip("/")
     file_transfer.delete_file(bucket=bucket, key=key)
 
+
+def test_sd_attr():
+    """Test correctness of StructuredDataset attributes.
+
+    This test considers only the following condition:
+    1. Check StructuredDataset (wrapped in a dataclass) file_format attribute
+
+    We'll make sure uri aligns with the user-specified one in the future.
+    """
+    from workflows.basic.sd_attr import wf
+
+    @dataclass
+    class DC:
+        sd: StructuredDataset
+
+    FILE_FORMAT = "parquet"
+
+    # Upload a file to minio s3 bucket
+    file_transfer = SimpleFileTransfer()
+    remote_file_path = file_transfer.upload_file(file_type=FILE_FORMAT)
+
+    # Create a dataclass as the workflow input because `pyflyte run`
+    # can't properly handle input arg `dc` as a json str so far
+    dc = DC(sd=StructuredDataset(uri=remote_file_path, file_format=FILE_FORMAT))
+
+    remote = FlyteRemote(Config.auto(config_file=CONFIG), PROJECT, DOMAIN, interactive_mode_enabled=True)
+    wf_exec = remote.execute(
+        wf,
+        inputs={"dc": dc, "file_format": FILE_FORMAT},
+        wait=True,
+        version=VERSION,
+        image_config=ImageConfig.from_images(IMAGE),
+    )
+    assert wf_exec.closure.phase == WorkflowExecutionPhase.SUCCEEDED, f"Execution failed with phase: {wf_exec.closure.phase}"
+    assert wf_exec.outputs["o0"].file_format == FILE_FORMAT, (
+        f"Workflow output StructuredDataset file_format should align with the user-specified file_format: {FILE_FORMAT}."
+    )
+
+    # Delete the remote file to free the space
+    url = urlparse(remote_file_path)
+    bucket, key = url.netloc, url.path.lstrip("/")
+    file_transfer.delete_file(bucket=bucket, key=key)
+
+
 def test_signal_approve_reject(register):
     from flytekit.models.types import LiteralType, SimpleType
     from time import sleep

tests/flytekit/integration/remote/workflows/basic/sd_attr.py

@@ -0,0 +1,68 @@
+from dataclasses import dataclass
+
+import pandas as pd
+from flytekit import task, workflow
+from flytekit.types.structured import StructuredDataset
+
+
+@dataclass
+class DC:
+    sd: StructuredDataset
+
+
+@task
+def create_dc(uri: str, file_format: str) -> DC:
+    """Create a dataclass with a StructuredDataset attribute.
+
+    Args:
+        uri: File URI.
+        file_format: File format, e.g., parquet, csv.
+
+    Returns:
+        dc: A dataclass with a StructuredDataset attribute.
+    """
+    dc = DC(sd=StructuredDataset(uri=uri, file_format=file_format))
+
+    return dc
+
+
+@task
+def check_file_format(sd: StructuredDataset, true_file_format: str) -> StructuredDataset:
+    """Check StructuredDataset file_format attribute.
+
+    StruturedDataset file_format should align with what users specify.
+
+    Args:
+        sd: Python native StructuredDataset.
+        true_file_format: User-specified file_format.
+    """
+    assert sd.file_format == true_file_format, (
+        f"StructuredDataset file_format should align with the user-specified file_format: {true_file_format}."
+    )
+    assert sd._literal_sd.metadata.structured_dataset_type.format == true_file_format, (
+        f"StructuredDatasetType format should align with the user-specified file_format: {true_file_format}."
+    )
+    print(f">>> SD <<<\n{sd}")
+    print(f">>> Literal SD <<<\n{sd._literal_sd}")
+    print(f">>> SDT <<<\n{sd._literal_sd.metadata.structured_dataset_type}")
+    print(f">>> DF <<<\n{sd.open(pd.DataFrame).all()}")
+
+    return sd
+
+
+@workflow
+def wf(dc: DC, file_format: str) -> StructuredDataset:
+    # Fail to use dc.sd.file_format as the input
+    sd = check_file_format(sd=dc.sd, true_file_format=file_format)
+
+    return sd
+
+
+if __name__ == "__main__":
+    # Define inputs
+    uri = "tests/flytekit/integration/remote/workflows/basic/data/df.parquet"
+    file_format = "parquet"
+
+    dc = create_dc(uri=uri, file_format=file_format)
+    sd = wf(dc=dc, file_format=file_format)
+    print(sd.file_format)