# Copyright 2023 The Kubeflow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


from typing import Optional

from google_cloud_pipeline_components import _image
from google_cloud_pipeline_components import utils
from google_cloud_pipeline_components.types.artifact_types import VertexDataset
from kfp import dsl
from kfp.dsl import Input
from kfp.dsl import Output


@utils.gcpc_output_name_converter('dataset')
@dsl.container_component
def image_dataset_import(
    project: str,
    dataset: Input[VertexDataset],
    output__dataset: Output[VertexDataset],
    location: Optional[str] = 'us-central1',
    data_item_labels: Optional[dict] = {},
    gcs_source: Optional[str] = None,
    import_schema_uri: Optional[str] = None,
):
  # fmt: off
  """Uploads data to an existing managed `Dataset <https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.datasets>`_.

  Args:
      project: Project to retrieve Dataset from.
      location: Optional location to retrieve Dataset from.
      dataset: The Dataset to be updated.
      gcs_source:
          Google Cloud Storage URI(-s) to the
          input file(s). May contain wildcards. For more
          information on wildcards, see
          https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames.
          For example, "gs://bucket/file.csv" or ["gs://bucket/file1.csv", "gs://bucket/file2.csv"].
      import_schema_uri: Points to a YAML file stored on Google Cloud
          Storage describing the import format. Validation will be
          done against the schema. The schema is defined as an
          `OpenAPI 3.0.2 Schema Object <https://tinyurl.com/y538mdwt>`_.
      data_item_labels: Labels that will be applied to newly imported DataItems. If
          an identical DataItem as one being imported already exists
          in the Dataset, then these labels will be appended to these
          of the already existing one, and if labels with identical
          key is imported before, the old label value will be
          overwritten. If two DataItems are identical in the same
          import data operation, the labels will be combined and if
          key collision happens in this case, one of the values will
          be picked randomly. Two DataItems are considered identical
          if their content bytes are identical (e.g. image bytes or
          pdf bytes). These labels will be overridden by Annotation
          labels specified inside index file refenced by
          ``import_schema_uri``, e.g. jsonl file.

  Returns:
      dataset: Instantiated representation of the managed Dataset resource.
  """
  # fmt: on

  return dsl.ContainerSpec(
      image=_image.GCPC_IMAGE_TAG,
      command=[
          'python3',
          '-m',
          'google_cloud_pipeline_components.container.v1.aiplatform.remote_runner',
          '--cls_name',
          'ImageDataset',
          '--method_name',
          'import_data',
      ],
      args=[
          '--init.project',
          project,
          '--init.location',
          location,
          '--init.dataset_name',
          dataset.metadata['resourceName'],
          '--method.data_item_labels',
          data_item_labels,
          dsl.IfPresentPlaceholder(
              input_name='gcs_source', then=['--method.gcs_source', gcs_source]
          ),
          dsl.IfPresentPlaceholder(
              input_name='import_schema_uri',
              then=['--method.import_schema_uri', import_schema_uri],
          ),
          '--executor_input',
          '{{$}}',
          '--resource_name_output_artifact_uri',
          output__dataset.uri,
      ],
  )
