# 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 Dict, List

from google_cloud_pipeline_components import _image
from google_cloud_pipeline_components.types.artifact_types import BQMLModel
from kfp.dsl import Artifact
from kfp.dsl import ConcatPlaceholder
from kfp.dsl import container_component
from kfp.dsl import ContainerSpec
from kfp.dsl import Input
from kfp.dsl import Output
from kfp.dsl import OutputPath


@container_component
def bigquery_ml_arima_evaluate_job(
    project: str,
    model: Input[BQMLModel],
    arima_evaluation_metrics: Output[Artifact],
    gcp_resources: OutputPath(str),
    location: str = 'us-central1',
    show_all_candidate_models: bool = False,
    query_parameters: List[str] = [],
    job_configuration_query: Dict[str, str] = {},
    labels: Dict[str, str] = {},
    encryption_spec_key_name: str = '',
):
  # fmt: off
  """Launch a BigQuery ML.ARIMA_EVALUATE job and waits for it to finish.

  Args:
      project: Project to run BigQuery model evaluation job.
      location: Location to run the BigQuery model evaluation
        job. If not set, default to `US` multi-region. For more details, see
        https://cloud.google.com/bigquery/docs/locations#specifying_your_location
      model: BigQuery ML model for
        ML.ARIMA_EVALUATE. For more details, see
        https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-evaluate#model_name
      show_all_candidate_models: You can use
        show_all_candidate_models to show evaluation metrics or an error
        message for either all candidate models or for only the best model
        with the lowest AIC. The value is type BOOL and is part of the
        settings STRUCT. For more details, see
        https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-evaluate#show_all_candidate_models
      query_parameters: jobs.query parameters for
        standard SQL queries. If query_parameters are both specified in here
        and in job_configuration_query, the value in here will override the
        other one.
      job_configuration_query: A json formatted string
        describing the rest of the job configuration. For more details, see
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery
      labels: The labels associated with this job. You can
        use these to organize and group your jobs. Label keys and values can
        be no longer than 63 characters, can only containlowercase letters,
        numeric characters, underscores and dashes. International characters
        are allowed. Label values are optional. Label keys must start with a
        letter and each label in the list must have a different key.
        Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
      encryption_spec_key_name:
        Describes the Cloud
        KMS encryption key that will be used to protect destination
        BigQuery table. The BigQuery Service Account associated with your
        project requires access to this encryption key. If
        encryption_spec_key_name are both specified in here and in
        job_configuration_query, the value in here will override the other
        one.

  Returns:
      arima_evaluation_metrics: Describes arima metrics.
        For more details, see
        https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-evaluate#mlarima_evaluate_output
      gcp_resources: Serialized gcp_resources proto tracking the BigQuery job.
          For more details, see
          https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.
  """
  # fmt: on
  return ContainerSpec(
      image=_image.GCPC_IMAGE_TAG,
      command=[
          'python3',
          '-u',
          '-m',
          'google_cloud_pipeline_components.container.v1.bigquery.ml_arima_evaluate.launcher',
      ],
      args=[
          '--type',
          'BigqueryMLArimaEvaluateJob',
          '--project',
          project,
          '--location',
          location,
          '--model_name',
          ConcatPlaceholder([
              model.metadata['projectId'],
              '.',
              model.metadata['datasetId'],
              '.',
              model.metadata['modelId'],
          ]),
          '--show_all_candidate_models',
          show_all_candidate_models,
          '--payload',
          ConcatPlaceholder([
              '{',
              '"configuration": {',
              '"query": ',
              job_configuration_query,
              ', "labels": ',
              labels,
              '}',
              '}',
          ]),
          '--job_configuration_query_override',
          ConcatPlaceholder([
              '{',
              '"query_parameters": ',
              query_parameters,
              ', "destination_encryption_configuration": {',
              '"kmsKeyName": "',
              encryption_spec_key_name,
              '"}',
              '}',
          ]),
          '--gcp_resources',
          gcp_resources,
          '--executor_input',
          '{{$}}',
      ],
  )
