"""
All or portions of this file Copyright (c) Amazon.com, Inc. or its affiliates or
its licensors.

For complete copyright and license terms please see the LICENSE at the root of this
distribution (the "License"). All use of this software is governed by the License,
or, if provided, by the license below or the license accompanying this file. Do not
remove or modify any license notices. This file is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
"""

from aws_cdk import (
    core
)

from .real_time_data_processing import RealTimeDataProcessing
from .data_ingestion import DataIngestion
from .batch_processing import BatchProcessing
from .batch_analytics import BatchAnalytics
from .data_lake_integration import DataLakeIntegration
from .dashboard import Dashboard


class AWSMetricsStack(core.Stack):
    """
    Create the feature stack for the AWSMetrics Gem.

    Please reference the CloudFormation template provided by the Game Analytics Pipeline for the
    full production ready solution. This CDK application deploys a simplified version of this pipeline as an example.
    https://docs.aws.amazon.com/solutions/latest/game-analytics-pipeline/template.html
    """

    def __init__(self,
                 scope: core.Construct,
                 id_: str,
                 application_name: str,
                 optional_features: dict,
                 **kwargs) -> None:
        super().__init__(scope, id_, **kwargs)

        self._data_ingestion = DataIngestion(self, application_name)

        self._real_time_data_processing = RealTimeDataProcessing(
            self,
            input_stream_arn=self._data_ingestion.input_stream_arn,
            application_name=application_name
        )

        batch_processing_enabled = optional_features.get('batch_processing', False)
        self._data_lake_integration = DataLakeIntegration(
            self,
            application_name=application_name
        ) if batch_processing_enabled else None

        self._batch_processing = BatchProcessing(
            self,
            input_stream_arn=self._data_ingestion.input_stream_arn,
            analytics_bucket_arn=self._data_lake_integration.analytics_bucket_arn,
            events_database_name=self._data_lake_integration.events_database_name,
            events_table_name=self._data_lake_integration.events_table_name
        ) if batch_processing_enabled else None

        self._batch_analytics = BatchAnalytics(
            self,
            analytics_bucket_name=self._data_lake_integration.analytics_bucket_name,
            events_database_name=self._data_lake_integration.events_database_name,
            events_table_name=self._data_lake_integration.events_table_name
        ) if batch_processing_enabled else None

        self._dashboard = Dashboard(
            self,
            input_stream_name=self._data_ingestion.input_stream_name,
            application_name=application_name,
            analytics_processing_lambda_name=self._real_time_data_processing.analytics_processing_lambda_name,
            delivery_stream_name=self._batch_processing.delivery_stream_name if batch_processing_enabled else '',
            events_processing_lambda_name=self._batch_processing.events_processing_lambda_name if batch_processing_enabled else ''
        )

    @property
    def data_ingestion_component(self):
        return self._data_ingestion

    @property
    def real_time_data_processing_component(self):
        return self._real_time_data_processing

    @property
    def dashboard_component(self):
        return self._dashboard

    @property
    def data_lake_integration_component(self):
        return self._data_lake_integration

    @property
    def batch_processing_component(self):
        return self._batch_processing

    @property
    def batch_analytics_component(self):
        return self._batch_analytics