# ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------

from os import PathLike
from pathlib import Path
from typing import Any, Dict, Optional, Union

from azure.ai.ml.entities._job.resource_configuration import ResourceConfiguration
from azure.ai.ml._restclient.v2022_05_01.models import BatchDeploymentData
from azure.ai.ml._restclient.v2022_05_01.models import BatchDeploymentDetails as RestBatchDeployment
from azure.ai.ml._restclient.v2022_05_01.models import CodeConfiguration as RestCodeConfiguration
from azure.ai.ml._restclient.v2022_05_01.models import IdAssetReference
from azure.ai.ml._restclient.v2022_05_01.models import BatchOutputAction
from azure.ai.ml.constants._deployment import BatchDeploymentOutputAction
from azure.ai.ml.entities._assets import Environment, Model
from azure.ai.ml.entities import BatchDeployment, Deployment
from azure.ai.ml.exceptions import ErrorCategory, ErrorTarget, ValidationErrorType, ValidationException
from azure.ai.ml.constants._common import BASE_PATH_CONTEXT_KEY, PARAMS_OVERRIDE_KEY
from azure.ai.ml.entities._util import load_from_dict
from azure.ai.ml._utils._experimental import experimental
from azure.ai.ml._schema._deployment.batch.model_batch_deployment import ModelBatchDeploymentSchema
from .model_batch_deployment_settings import ModelBatchDeploymentSettings
from .code_configuration import CodeConfiguration


@experimental
class ModelBatchDeployment(Deployment):
    """Job Definition entity.

    :param type: Job definition type. Allowed value is: pipeline
    :type type: str
    :param name: Job name
    :type name: str
    :param job: Job definition
    :type job: Union[Job, str]
    :param component: Component definition
    :type component: Union[Component, str]
    :param settings: Job settings
    :type settings: Dict[str, Any]
    :param description: Job description.
    :type description: str
    :param tags: Job tags
    :type tags: Dict[str, Any]
    """

    def __init__(
        self,
        *,
        name: Optional[str],
        endpoint_name: Optional[str] = None,
        environment: Optional[Union[str, Environment]] = None,
        properties: Optional[Dict[str, str]] = None,
        model: Optional[Union[str, Model]] = None,
        description: Optional[str] = None,
        tags: Optional[Dict[str, Any]] = None,
        settings: Optional[ModelBatchDeploymentSettings] = None,
        resources: Optional[ResourceConfiguration] = None,
        compute: Optional[str] = None,
        code_configuration: Optional[CodeConfiguration] = None,
        code_path: Optional[Union[str, PathLike]] = None,  # promoted property from code_configuration.code
        scoring_script: Optional[
            Union[str, PathLike]
        ] = None,  # promoted property from code_configuration.scoring_script
        **kwargs,  # pylint: disable=unused-argument
    ):
        self._provisioning_state = kwargs.pop("provisioning_state", None)
        super().__init__(
            name=name,
            endpoint_name=endpoint_name,
            properties=properties,
            code_path=code_path,
            scoring_script=scoring_script,
            environment=environment,
            model=model,
            description=description,
            tags=tags,
            code_configuration=code_configuration,
            **kwargs,
        )
        self.compute = compute
        self.resources = resources
        self.model_deployment_settings = ModelBatchDeploymentSettings(
            mini_batch_size=settings.mini_batch_size,
            instance_count=settings.instance_count,
            max_concurrency_per_instance=settings.max_concurrency_per_instance,
            output_action=settings.output_action,
            output_file_name=settings.output_file_name,
            retry_settings=settings.retry_settings,
            environment_variables=settings.environment_variables,
            error_threshold=settings.error_threshold,
            logging_level=settings.logging_level,
        )

    def _to_rest_object(self, location: str) -> BatchDeploymentData:  # pylint: disable=arguments-differ
        self._validate()
        code_config = (
            RestCodeConfiguration(
                code_id=self.code_configuration.code,
                scoring_script=self.code_configuration.scoring_script,
            )
            if self.code_configuration
            else None
        )
        deployment_settings = self.model_deployment_settings
        model = IdAssetReference(asset_id=self.model) if self.model else None
        batch_deployment = RestBatchDeployment(
            description=self.description,
            environment_id=self.environment,
            model=model,
            code_configuration=code_config,
            output_file_name=deployment_settings.output_file_name,
            output_action=BatchDeployment._yaml_output_action_to_rest_output_action(  # pylint: disable=protected-access
                deployment_settings.output_action
            ),
            error_threshold=deployment_settings.error_threshold,
            resources=self.resources._to_rest_object() if self.resources else None,  # pylint: disable=protected-access
            retry_settings=deployment_settings.retry_settings._to_rest_object()  # pylint: disable=protected-access
            if deployment_settings.retry_settings
            else None,
            logging_level=deployment_settings.logging_level,
            mini_batch_size=deployment_settings.mini_batch_size,
            max_concurrency_per_instance=deployment_settings.max_concurrency_per_instance,
            environment_variables=deployment_settings.environment_variables,
            compute=self.compute,
        )
        return BatchDeploymentData(location=location, properties=batch_deployment, tags=self.tags)

    @classmethod
    def _load(
        cls,
        data: Optional[Dict] = None,
        yaml_path: Optional[Union[PathLike, str]] = None,
        params_override: Optional[list] = None,
        **kwargs,
    ) -> "ModelBatchDeployment":
        data = data or {}
        params_override = params_override or []
        cls._update_params(params_override)

        context = {
            BASE_PATH_CONTEXT_KEY: Path(yaml_path).parent if yaml_path else Path.cwd(),
            PARAMS_OVERRIDE_KEY: params_override,
        }
        return load_from_dict(ModelBatchDeploymentSchema, data, context, **kwargs)

    @classmethod
    def _update_params(cls, params_override) -> None:
        for param in params_override:
            endpoint_name = param.get("endpoint_name")
            if isinstance(endpoint_name, str):
                param["endpoint_name"] = endpoint_name.lower()

    @classmethod
    def _yaml_output_action_to_rest_output_action(cls, yaml_output_action: str) -> str:
        output_switcher = {
            BatchDeploymentOutputAction.APPEND_ROW: BatchOutputAction.APPEND_ROW,
            BatchDeploymentOutputAction.SUMMARY_ONLY: BatchOutputAction.SUMMARY_ONLY,
        }
        return output_switcher.get(yaml_output_action, yaml_output_action)

    @property
    def provisioning_state(self) -> Optional[str]:
        """Batch deployment provisioning state, readonly.

        :return: Batch deployment provisioning state.
        :rtype: Optional[str]
        """
        return self._provisioning_state

    def _validate(self) -> None:
        self._validate_output_action()

    def _validate_output_action(self) -> None:
        if (
            self.model_deployment_settings.output_action
            and self.model_deployment_settings.output_action == BatchDeploymentOutputAction.SUMMARY_ONLY
            and self.model_deployment_settings.output_file_name
        ):
            msg = "When output_action is set to {}, the output_file_name need not to be specified."
            msg = msg.format(BatchDeploymentOutputAction.SUMMARY_ONLY)
            raise ValidationException(
                message=msg,
                target=ErrorTarget.BATCH_DEPLOYMENT,
                no_personal_data_message=msg,
                error_category=ErrorCategory.USER_ERROR,
                error_type=ValidationErrorType.INVALID_VALUE,
            )

    def _to_dict(self) -> Dict:
        return ModelBatchDeploymentSchema(context={BASE_PATH_CONTEXT_KEY: "./"}).dump(self)  # pylint: disable=no-member
