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"""This module contains Amazon EKS operators."""
from datetime import datetime
from time import sleep
from typing import Dict, Iterable, List, Optional

from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.eks import (
    DEFAULT_CONTEXT_NAME,
    DEFAULT_POD_USERNAME,
    ClusterStates,
    EKSHook,
)
from airflow.providers.cncf.kubernetes.operators.kubernetes_pod import KubernetesPodOperator

CHECK_INTERVAL_SECONDS = 15
TIMEOUT_SECONDS = 25 * 60
DEFAULT_COMPUTE_TYPE = 'nodegroup'
DEFAULT_CONN_ID = "aws_default"
DEFAULT_NAMESPACE_NAME = 'default'
DEFAULT_NODEGROUP_NAME_SUFFIX = '-nodegroup'
DEFAULT_POD_NAME = 'pod'


class EKSCreateClusterOperator(BaseOperator):
    """
    Creates an Amazon EKS Cluster control plane.

    Optionally, can also create the supporting compute architecture:
    If argument 'compute' is provided with a value of 'nodegroup', will also attempt to create an Amazon
    EKS Managed Nodegroup for the cluster.  See EKSCreateNodegroupOperator documentation for requirements.

    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:EKSCreateClusterOperator`

    :param cluster_name: The unique name to give to your Amazon EKS Cluster. (templated)
    :type cluster_name: str
    :param cluster_role_arn: The Amazon Resource Name (ARN) of the IAM role that provides permissions for the
       Kubernetes control plane to make calls to AWS API operations on your behalf. (templated)
    :type cluster_role_arn: str
    :param resources_vpc_config: The VPC configuration used by the cluster control plane. (templated)
    :type resources_vpc_config: Dict
    :param compute: The type of compute architecture to generate along with the cluster. (templated)
        Defaults to 'nodegroup' to generate an EKS Managed Nodegroup.
    :type compute: str
    :param aws_conn_id: The Airflow connection used for AWS credentials. (templated)
         If this is None or empty then the default boto3 behaviour is used. If
         running Airflow in a distributed manner and aws_conn_id is None or
         empty, then the default boto3 configuration would be used (and must be
         maintained on each worker node).
    :type aws_conn_id: str
    :param region: Which AWS region the connection should use. (templated)
        If this is None or empty then the default boto3 behaviour is used.
    :type region: str

    If compute is assigned the value of ``nodegroup``, the following are required:

    :param nodegroup_name: The unique name to give your EKS Managed Nodegroup. (templated)
    :type nodegroup_name: str
    :param nodegroup_role_arn: The Amazon Resource Name (ARN) of the IAM role to associate
         with the EKS Managed Nodegroup. (templated)
    :type nodegroup_role_arn: str

    """

    template_fields: Iterable[str] = (
        "cluster_name",
        "cluster_role_arn",
        "resources_vpc_config",
        "nodegroup_name",
        "nodegroup_role_arn",
        "compute",
        "aws_conn_id",
        "region",
    )

    def __init__(
        self,
        cluster_name: str,
        cluster_role_arn: str,
        resources_vpc_config: Dict,
        nodegroup_name: Optional[str] = None,
        nodegroup_role_arn: Optional[str] = None,
        compute: Optional[str] = DEFAULT_COMPUTE_TYPE,
        aws_conn_id: str = DEFAULT_CONN_ID,
        region: Optional[str] = None,
        **kwargs,
    ) -> None:
        self.compute = compute
        if (self.compute == 'nodegroup') and not nodegroup_role_arn:
            raise ValueError("Creating an EKS Managed Nodegroup requires nodegroup_role_arn to be passed in.")
        self.cluster_name = cluster_name
        self.cluster_role_arn = cluster_role_arn
        self.resources_vpc_config = resources_vpc_config
        self.nodegroup_name = nodegroup_name or self.cluster_name + DEFAULT_NODEGROUP_NAME_SUFFIX
        self.nodegroup_role_arn = nodegroup_role_arn
        self.aws_conn_id = aws_conn_id
        self.region = region
        super().__init__(**kwargs)

    def execute(self, context):
        eks_hook = EKSHook(
            aws_conn_id=self.aws_conn_id,
            region_name=self.region,
        )

        eks_hook.create_cluster(
            name=self.cluster_name,
            roleArn=self.cluster_role_arn,
            resourcesVpcConfig=self.resources_vpc_config,
        )

        if not self.compute:
            return None

        self.log.info("Waiting for EKS Cluster to provision.  This will take some time.")

        countdown = TIMEOUT_SECONDS
        while eks_hook.get_cluster_state(clusterName=self.cluster_name) != ClusterStates.ACTIVE:
            if countdown >= CHECK_INTERVAL_SECONDS:
                countdown -= CHECK_INTERVAL_SECONDS
                self.log.info(
                    "Waiting for cluster to start.  Checking again in %d seconds", CHECK_INTERVAL_SECONDS
                )
                sleep(CHECK_INTERVAL_SECONDS)
            else:
                message = (
                    "Cluster is still inactive after the allocated time limit.  "
                    "Failed cluster will be torn down."
                )
                self.log.error(message)
                # If there is something preventing the cluster for activating, tear it down and abort.
                eks_hook.delete_cluster(name=self.cluster_name)
                raise RuntimeError(message)

        if self.compute == 'nodegroup':
            eks_hook.create_nodegroup(
                clusterName=self.cluster_name,
                nodegroupName=self.nodegroup_name,
                subnets=self.resources_vpc_config.get('subnetIds'),
                nodeRole=self.nodegroup_role_arn,
            )


class EKSCreateNodegroupOperator(BaseOperator):
    """
    Creates am Amazon EKS Managed Nodegroup for an existing Amazon EKS Cluster.

    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:EKSCreateNodegroupOperator`

    :param cluster_name: The name of the Amazon EKS Cluster to create the managed nodegroup in. (templated)
    :type cluster_name: str
    :param nodegroup_name: The unique name to give your managed nodegroup. (templated)
    :type nodegroup_name: str
    :param nodegroup_subnets:
        The subnets to use for the Auto Scaling group that is created for the managed nodegroup. (templated)
    :type nodegroup_subnets: List[str]
    :param nodegroup_role_arn:
        The Amazon Resource Name (ARN) of the IAM role to associate with the managed nodegroup. (templated)
    :type nodegroup_role_arn: str
    :param aws_conn_id: The Airflow connection used for AWS credentials. (templated)
         If this is None or empty then the default boto3 behaviour is used. If
         running Airflow in a distributed manner and aws_conn_id is None or
         empty, then the default boto3 configuration would be used (and must be
         maintained on each worker node).
    :type aws_conn_id: str
        :param region: Which AWS region the connection should use. (templated)
        If this is None or empty then the default boto3 behaviour is used.
    :type region: str

    """

    template_fields: Iterable[str] = (
        "cluster_name",
        "nodegroup_subnets",
        "nodegroup_role_arn",
        "nodegroup_name",
        "aws_conn_id",
        "region",
    )

    def __init__(
        self,
        cluster_name: str,
        nodegroup_subnets: List[str],
        nodegroup_role_arn: str,
        nodegroup_name: Optional[str] = None,
        aws_conn_id: str = DEFAULT_CONN_ID,
        region: Optional[str] = None,
        **kwargs,
    ) -> None:
        self.cluster_name = cluster_name
        self.nodegroup_subnets = nodegroup_subnets
        self.nodegroup_role_arn = nodegroup_role_arn
        self.nodegroup_name = nodegroup_name or cluster_name + datetime.now().strftime("%Y%m%d_%H%M%S")
        self.aws_conn_id = aws_conn_id
        self.region = region
        super().__init__(**kwargs)

    def execute(self, context):
        eks_hook = EKSHook(
            aws_conn_id=self.aws_conn_id,
            region_name=self.region,
        )

        eks_hook.create_nodegroup(
            clusterName=self.cluster_name,
            nodegroupName=self.nodegroup_name,
            subnets=self.nodegroup_subnets,
            nodeRole=self.nodegroup_role_arn,
        )


class EKSDeleteClusterOperator(BaseOperator):
    """
    Deletes the Amazon EKS Cluster control plane and all nodegroups attached to it.

    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:EKSDeleteClusterOperator`

    :param cluster_name: The name of the Amazon EKS Cluster to delete. (templated)
    :type cluster_name: str
    :param force_delete_compute: If True, will delete any attached resources. (templated)
         Defaults to False.
    :type force_delete_compute: bool
    :param aws_conn_id: The Airflow connection used for AWS credentials. (templated)
         If this is None or empty then the default boto3 behaviour is used. If
         running Airflow in a distributed manner and aws_conn_id is None or
         empty, then the default boto3 configuration would be used (and must be
         maintained on each worker node).
    :type aws_conn_id: str
    :param region: Which AWS region the connection should use. (templated)
        If this is None or empty then the default boto3 behaviour is used.
    :type region: str

    """

    template_fields: Iterable[str] = (
        "cluster_name",
        "force_delete_compute",
        "aws_conn_id",
        "region",
    )

    def __init__(
        self,
        cluster_name: str,
        force_delete_compute: bool = False,
        aws_conn_id: str = DEFAULT_CONN_ID,
        region: Optional[str] = None,
        **kwargs,
    ) -> None:
        self.cluster_name = cluster_name
        self.force_delete_compute = force_delete_compute
        self.aws_conn_id = aws_conn_id
        self.region = region
        super().__init__(**kwargs)

    def execute(self, context):
        eks_hook = EKSHook(
            aws_conn_id=self.aws_conn_id,
            region_name=self.region,
        )

        if self.force_delete_compute:
            nodegroups = eks_hook.list_nodegroups(clusterName=self.cluster_name)
            nodegroup_count = len(nodegroups)
            if nodegroup_count:
                self.log.info(
                    "A cluster can not be deleted with attached nodegroups.  Deleting %d nodegroups.",
                    nodegroup_count,
                )
                for group in nodegroups:
                    eks_hook.delete_nodegroup(clusterName=self.cluster_name, nodegroupName=group)

                # Scaling up the timeout based on the number of nodegroups that are being processed.
                additional_seconds = 5 * 60
                countdown = TIMEOUT_SECONDS + (nodegroup_count * additional_seconds)
                while eks_hook.list_nodegroups(clusterName=self.cluster_name):
                    if countdown >= CHECK_INTERVAL_SECONDS:
                        countdown -= CHECK_INTERVAL_SECONDS
                        sleep(CHECK_INTERVAL_SECONDS)
                        self.log.info(
                            "Waiting for the remaining %s nodegroups to delete.  "
                            "Checking again in %d seconds.",
                            nodegroup_count,
                            CHECK_INTERVAL_SECONDS,
                        )
                    else:
                        raise RuntimeError(
                            "Nodegroups are still inactive after the allocated time limit.  Aborting."
                        )
            self.log.info("No nodegroups remain, deleting cluster.")

        eks_hook.delete_cluster(name=self.cluster_name)


class EKSDeleteNodegroupOperator(BaseOperator):
    """
    Deletes an Amazon EKS Nodegroup from an Amazon EKS Cluster.

    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:EKSDeleteNodegroupOperator`

    :param cluster_name: The name of the Amazon EKS Cluster associated with your nodegroup. (templated)
    :type cluster_name: str
    :param nodegroup_name: The name of the nodegroup to delete. (templated)
    :type nodegroup_name: str
    :param aws_conn_id: The Airflow connection used for AWS credentials. (templated)
         If this is None or empty then the default boto3 behaviour is used.  If
         running Airflow in a distributed manner and aws_conn_id is None or
         empty, then the default boto3 configuration would be used (and must be
         maintained on each worker node).
    :type aws_conn_id: str
    :param region: Which AWS region the connection should use. (templated)
        If this is None or empty then the default boto3 behaviour is used.
    :type region: str

    """

    template_fields: Iterable[str] = (
        "cluster_name",
        "nodegroup_name",
        "aws_conn_id",
        "region",
    )

    def __init__(
        self,
        cluster_name: str,
        nodegroup_name: str,
        aws_conn_id: str = DEFAULT_CONN_ID,
        region: Optional[str] = None,
        **kwargs,
    ) -> None:
        self.cluster_name = cluster_name
        self.nodegroup_name = nodegroup_name
        self.aws_conn_id = aws_conn_id
        self.region = region
        super().__init__(**kwargs)

    def execute(self, context):
        eks_hook = EKSHook(
            aws_conn_id=self.aws_conn_id,
            region_name=self.region,
        )

        eks_hook.delete_nodegroup(clusterName=self.cluster_name, nodegroupName=self.nodegroup_name)


class EKSPodOperator(KubernetesPodOperator):
    """
    Executes a task in a Kubernetes pod on the specified Amazon EKS Cluster.

    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:EKSPodOperator`

    :param cluster_name: The name of the Amazon EKS Cluster to execute the task on. (templated)
    :type cluster_name: str
    :param cluster_role_arn: The Amazon Resource Name (ARN) of the IAM role that provides permissions
       for the Kubernetes control plane to make calls to AWS API operations on your behalf. (templated)
    :type cluster_role_arn: str
    :param in_cluster: If True, look for config inside the cluster; if False look for a local file path.
    :type in_cluster: bool
    :param namespace: The namespace in which to execute the pod. (templated)
    :type namespace: str
    :param pod_context: The security context to use while executing the pod. (templated)
    :type pod_context: str
    :param pod_name: The unique name to give the pod. (templated)
    :type pod_name: str
    :param pod_username: The username to use while executing the pod. (templated)
    :type pod_username: str
    :param aws_profile: The named profile containing the credentials for the AWS CLI tool to use.
    :param aws_profile: str
    :param region: Which AWS region the connection should use. (templated)
        If this is None or empty then the default boto3 behaviour is used.
    :type region: str
    :param aws_conn_id: The Airflow connection used for AWS credentials. (templated)
         If this is None or empty then the default boto3 behaviour is used. If
         running Airflow in a distributed manner and aws_conn_id is None or
         empty, then the default boto3 configuration would be used (and must be
         maintained on each worker node).
    :type aws_conn_id: str
    """

    template_fields: Iterable[str] = {
        "cluster_name",
        "in_cluster",
        "namespace",
        "pod_context",
        "pod_name",
        "pod_username",
        "aws_conn_id",
        "region",
    } | set(KubernetesPodOperator.template_fields)

    def __init__(
        self,
        cluster_name: str,
        # Setting in_cluster to False tells the pod that the config
        # file is stored locally in the worker and not in the cluster.
        in_cluster: bool = False,
        namespace: str = DEFAULT_NAMESPACE_NAME,
        pod_context: str = DEFAULT_CONTEXT_NAME,
        pod_name: str = DEFAULT_POD_NAME,
        pod_username: str = DEFAULT_POD_USERNAME,
        aws_conn_id: str = DEFAULT_CONN_ID,
        region: Optional[str] = None,
        **kwargs,
    ) -> None:
        self.cluster_name = cluster_name
        self.in_cluster = in_cluster
        self.namespace = namespace
        self.pod_context = pod_context
        self.pod_name = pod_name
        self.pod_username = pod_username
        self.aws_conn_id = aws_conn_id
        self.region = region
        super().__init__(
            in_cluster=self.in_cluster,
            namespace=self.namespace,
            name=self.pod_name,
            **kwargs,
        )

    def execute(self, context):
        eks_hook = EKSHook(
            aws_conn_id=self.aws_conn_id,
            region_name=self.region,
        )

        with eks_hook.generate_config_file(
            eks_cluster_name=self.cluster_name,
            pod_namespace=self.namespace,
            pod_username=self.pod_username,
            pod_context=self.pod_context,
        ) as self.config_file:
            return super().execute(context)

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