# Cloud Dataproc API . projects . locations . autoscalingPolicies

## Instance Methods

Close httplib2 connections.

Creates new autoscaling policy.

Deletes an autoscaling policy. It is an error to delete an autoscaling policy that is in use by one or more clusters.

Retrieves autoscaling policy.

Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.

Lists autoscaling policies in the project.

Retrieves the next page of results.

Sets the access control policy on the specified resource. Replaces any existing policy.Can return NOT_FOUND, INVALID_ARGUMENT, and PERMISSION_DENIED errors.

Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a NOT_FOUND error.Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.

Updates (replaces) autoscaling policy.Disabled check for update_mask, because all updates will be full replacements.

### Method Details

`close()`

    Close httplib2 connections.

`create(parent, body=None, x__xgafv=None)`

    Creates new autoscaling policy.

    Args:
      parent: string, Required. The "resource name" of the region or location, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies.create, the resource name of the region has the following format: projects/{project_id}/regions/{region} For projects.locations.autoscalingPolicies.create, the resource name of the location has the following format: projects/{project_id}/locations/{location} (required)
      body: object, The request body.
        The object takes the form of:

    { # Describes an autoscaling policy for Dataproc cluster autoscaler.
      "basicAlgorithm": { # Basic algorithm for autoscaling.
        "cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
        "sparkStandaloneConfig": { # Basic autoscaling configurations for Spark Standalone. # Optional. Spark Standalone autoscaling configuration
          "gracefulDecommissionTimeout": "A String", # Required. Timeout for Spark graceful decommissioning of spark workers. Specifies the duration to wait for spark worker to complete spark decomissioning tasks before forcefully removing workers. Only applicable to downscaling operations.Bounds: 0s, 1d.
          "scaleDownFactor": 3.14, # Required. Fraction of required executors to remove from Spark Serverless clusters. A scale-down factor of 1.0 will result in scaling down so that there are no more executors for the Spark Job.(more aggressive scaling). A scale-down factor closer to 0 will result in a smaller magnitude of scaling donw (less aggressive scaling).Bounds: 0.0, 1.0.
          "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
          "scaleUpFactor": 3.14, # Required. Fraction of required workers to add to Spark Standalone clusters. A scale-up factor of 1.0 will result in scaling up so that there are no more required workers for the Spark Job (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling).Bounds: 0.0, 1.0.
          "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
        },
        "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
          "gracefulDecommissionTimeout": "A String", # Required. Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
          "scaleDownFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
          "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
          "scaleUpFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
          "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
        },
      },
      "id": "A String", # Required. The policy id.The id must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). Cannot begin or end with underscore or hyphen. Must consist of between 3 and 50 characters.
      "labels": { # Optional. The labels to associate with this autoscaling policy. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with an autoscaling policy.
        "a_key": "A String",
      },
      "name": "A String", # Output only. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
      "secondaryWorkerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Optional. Describes how the autoscaler will operate for secondary workers.
        "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
        "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
        "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
      },
      "workerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Required. Describes how the autoscaler will operate for primary workers.
        "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
        "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
        "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
      },
    }

      x__xgafv: string, V1 error format.
        Allowed values
          1 - v1 error format
          2 - v2 error format

    Returns:
      An object of the form:

        { # Describes an autoscaling policy for Dataproc cluster autoscaler.
      "basicAlgorithm": { # Basic algorithm for autoscaling.
        "cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
        "sparkStandaloneConfig": { # Basic autoscaling configurations for Spark Standalone. # Optional. Spark Standalone autoscaling configuration
          "gracefulDecommissionTimeout": "A String", # Required. Timeout for Spark graceful decommissioning of spark workers. Specifies the duration to wait for spark worker to complete spark decomissioning tasks before forcefully removing workers. Only applicable to downscaling operations.Bounds: 0s, 1d.
          "scaleDownFactor": 3.14, # Required. Fraction of required executors to remove from Spark Serverless clusters. A scale-down factor of 1.0 will result in scaling down so that there are no more executors for the Spark Job.(more aggressive scaling). A scale-down factor closer to 0 will result in a smaller magnitude of scaling donw (less aggressive scaling).Bounds: 0.0, 1.0.
          "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
          "scaleUpFactor": 3.14, # Required. Fraction of required workers to add to Spark Standalone clusters. A scale-up factor of 1.0 will result in scaling up so that there are no more required workers for the Spark Job (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling).Bounds: 0.0, 1.0.
          "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
        },
        "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
          "gracefulDecommissionTimeout": "A String", # Required. Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
          "scaleDownFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
          "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
          "scaleUpFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
          "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
        },
      },
      "id": "A String", # Required. The policy id.The id must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). Cannot begin or end with underscore or hyphen. Must consist of between 3 and 50 characters.
      "labels": { # Optional. The labels to associate with this autoscaling policy. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with an autoscaling policy.
        "a_key": "A String",
      },
      "name": "A String", # Output only. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
      "secondaryWorkerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Optional. Describes how the autoscaler will operate for secondary workers.
        "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
        "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
        "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
      },
      "workerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Required. Describes how the autoscaler will operate for primary workers.
        "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
        "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
        "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
      },
    }

`delete(name, x__xgafv=None)`

    Deletes an autoscaling policy. It is an error to delete an autoscaling policy that is in use by one or more clusters.

    Args:
      name: string, Required. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies.delete, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies.delete, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id} (required)
      x__xgafv: string, V1 error format.
        Allowed values
          1 - v1 error format
          2 - v2 error format

    Returns:
      An object of the form:

        { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
    }

`get(name, x__xgafv=None)`

    Retrieves autoscaling policy.

    Args:
      name: string, Required. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies.get, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies.get, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id} (required)
      x__xgafv: string, V1 error format.
        Allowed values
          1 - v1 error format
          2 - v2 error format

    Returns:
      An object of the form:

        { # Describes an autoscaling policy for Dataproc cluster autoscaler.
      "basicAlgorithm": { # Basic algorithm for autoscaling.
        "cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
        "sparkStandaloneConfig": { # Basic autoscaling configurations for Spark Standalone. # Optional. Spark Standalone autoscaling configuration
          "gracefulDecommissionTimeout": "A String", # Required. Timeout for Spark graceful decommissioning of spark workers. Specifies the duration to wait for spark worker to complete spark decomissioning tasks before forcefully removing workers. Only applicable to downscaling operations.Bounds: 0s, 1d.
          "scaleDownFactor": 3.14, # Required. Fraction of required executors to remove from Spark Serverless clusters. A scale-down factor of 1.0 will result in scaling down so that there are no more executors for the Spark Job.(more aggressive scaling). A scale-down factor closer to 0 will result in a smaller magnitude of scaling donw (less aggressive scaling).Bounds: 0.0, 1.0.
          "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
          "scaleUpFactor": 3.14, # Required. Fraction of required workers to add to Spark Standalone clusters. A scale-up factor of 1.0 will result in scaling up so that there are no more required workers for the Spark Job (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling).Bounds: 0.0, 1.0.
          "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
        },
        "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
          "gracefulDecommissionTimeout": "A String", # Required. Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
          "scaleDownFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
          "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
          "scaleUpFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
          "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
        },
      },
      "id": "A String", # Required. The policy id.The id must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). Cannot begin or end with underscore or hyphen. Must consist of between 3 and 50 characters.
      "labels": { # Optional. The labels to associate with this autoscaling policy. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with an autoscaling policy.
        "a_key": "A String",
      },
      "name": "A String", # Output only. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
      "secondaryWorkerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Optional. Describes how the autoscaler will operate for secondary workers.
        "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
        "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
        "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
      },
      "workerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Required. Describes how the autoscaler will operate for primary workers.
        "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
        "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
        "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
      },
    }

`getIamPolicy(resource, body=None, x__xgafv=None)`

    Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.

    Args:
      resource: string, REQUIRED: The resource for which the policy is being requested. See the operation documentation for the appropriate value for this field. (required)
      body: object, The request body.
        The object takes the form of:

    { # Request message for GetIamPolicy method.
      "options": { # Encapsulates settings provided to GetIamPolicy. # OPTIONAL: A GetPolicyOptions object for specifying options to GetIamPolicy.
        "requestedPolicyVersion": 42, # Optional. The maximum policy version that will be used to format the policy.Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected.Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset.The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1.To learn which resources support conditions in their IAM policies, see the IAM documentation (https://cloud.google.com/iam/help/conditions/resource-policies).
      },
    }

      x__xgafv: string, V1 error format.
        Allowed values
          1 - v1 error format
          2 - v2 error format

    Returns:
      An object of the form:

        { # An Identity and Access Management (IAM) policy, which specifies access controls for Google Cloud resources.A Policy is a collection of bindings. A binding binds one or more members, or principals, to a single role. Principals can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions; each role can be an IAM predefined role or a user-created custom role.For some types of Google Cloud resources, a binding can also specify a condition, which is a logical expression that allows access to a resource only if the expression evaluates to true. A condition can add constraints based on attributes of the request, the resource, or both. To learn which resources support conditions in their IAM policies, see the IAM documentation (https://cloud.google.com/iam/help/conditions/resource-policies).JSON example: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": [ "user:eve@example.com" ], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01T00:00:00.000Z')", } } ], "etag": "BwWWja0YfJA=", "version": 3 } YAML example: bindings: - members: - user:mike@example.com - group:admins@example.com - domain:google.com - serviceAccount:my-project-id@appspot.gserviceaccount.com role: roles/resourcemanager.organizationAdmin - members: - user:eve@example.com role: roles/resourcemanager.organizationViewer condition: title: expirable access description: Does not grant access after Sep 2020 expression: request.time < timestamp('2020-10-01T00:00:00.000Z') etag: BwWWja0YfJA= version: 3 For a description of IAM and its features, see the IAM documentation (https://cloud.google.com/iam/docs/).
      "bindings": [ # Associates a list of members, or principals, with a role. Optionally, may specify a condition that determines how and when the bindings are applied. Each of the bindings must contain at least one principal.The bindings in a Policy can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the bindings grant 50 different roles to user:alice@example.com, and not to any other principal, then you can add another 1,450 principals to the bindings in the Policy.
        { # Associates members, or principals, with a role.
          "condition": { # Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec.Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information. # The condition that is associated with this binding.If the condition evaluates to true, then this binding applies to the current request.If the condition evaluates to false, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding.To learn which resources support conditions in their IAM policies, see the IAM documentation (https://cloud.google.com/iam/help/conditions/resource-policies).
            "description": "A String", # Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
            "expression": "A String", # Textual representation of an expression in Common Expression Language syntax.
            "location": "A String", # Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
            "title": "A String", # Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
          },
          "members": [ # Specifies the principals requesting access for a Cloud Platform resource. members can have the following values: allUsers: A special identifier that represents anyone who is on the internet; with or without a Google account. allAuthenticatedUsers: A special identifier that represents anyone who is authenticated with a Google account or a service account. user:{emailid}: An email address that represents a specific Google account. For example, alice@example.com . serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com. group:{emailid}: An email address that represents a Google group. For example, admins@example.com. deleted:user:{emailid}?uid={uniqueid}: An email address (plus unique identifier) representing a user that has been recently deleted. For example, alice@example.com?uid=123456789012345678901. If the user is recovered, this value reverts to user:{emailid} and the recovered user retains the role in the binding. deleted:serviceAccount:{emailid}?uid={uniqueid}: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901. If the service account is undeleted, this value reverts to serviceAccount:{emailid} and the undeleted service account retains the role in the binding. deleted:group:{emailid}?uid={uniqueid}: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, admins@example.com?uid=123456789012345678901. If the group is recovered, this value reverts to group:{emailid} and the recovered group retains the role in the binding. domain:{domain}: The G Suite domain (primary) that represents all the users of that domain. For example, google.com or example.com.
            "A String",
          ],
          "role": "A String", # Role that is assigned to the list of members, or principals. For example, roles/viewer, roles/editor, or roles/owner.
        },
      ],
      "etag": "A String", # etag is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the etag in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An etag is returned in the response to getIamPolicy, and systems are expected to put that etag in the request to setIamPolicy to ensure that their change will be applied to the same version of the policy.Important: If you use IAM Conditions, you must include the etag field whenever you call setIamPolicy. If you omit this field, then IAM allows you to overwrite a version 3 policy with a version 1 policy, and all of the conditions in the version 3 policy are lost.
      "version": 42, # Specifies the format of the policy.Valid values are 0, 1, and 3. Requests that specify an invalid value are rejected.Any operation that affects conditional role bindings must specify version 3. This requirement applies to the following operations: Getting a policy that includes a conditional role binding Adding a conditional role binding to a policy Changing a conditional role binding in a policy Removing any role binding, with or without a condition, from a policy that includes conditionsImportant: If you use IAM Conditions, you must include the etag field whenever you call setIamPolicy. If you omit this field, then IAM allows you to overwrite a version 3 policy with a version 1 policy, and all of the conditions in the version 3 policy are lost.If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset.To learn which resources support conditions in their IAM policies, see the IAM documentation (https://cloud.google.com/iam/help/conditions/resource-policies).
    }

`list(parent, pageSize=None, pageToken=None, x__xgafv=None)`

    Lists autoscaling policies in the project.

    Args:
      parent: string, Required. The "resource name" of the region or location, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies.list, the resource name of the region has the following format: projects/{project_id}/regions/{region} For projects.locations.autoscalingPolicies.list, the resource name of the location has the following format: projects/{project_id}/locations/{location} (required)
      pageSize: integer, Optional. The maximum number of results to return in each response. Must be less than or equal to 1000. Defaults to 100.
      pageToken: string, Optional. The page token, returned by a previous call, to request the next page of results.
      x__xgafv: string, V1 error format.
        Allowed values
          1 - v1 error format
          2 - v2 error format

    Returns:
      An object of the form:

        { # A response to a request to list autoscaling policies in a project.
      "nextPageToken": "A String", # Output only. This token is included in the response if there are more results to fetch.
      "policies": [ # Output only. Autoscaling policies list.
        { # Describes an autoscaling policy for Dataproc cluster autoscaler.
          "basicAlgorithm": { # Basic algorithm for autoscaling.
            "cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
            "sparkStandaloneConfig": { # Basic autoscaling configurations for Spark Standalone. # Optional. Spark Standalone autoscaling configuration
              "gracefulDecommissionTimeout": "A String", # Required. Timeout for Spark graceful decommissioning of spark workers. Specifies the duration to wait for spark worker to complete spark decomissioning tasks before forcefully removing workers. Only applicable to downscaling operations.Bounds: 0s, 1d.
              "scaleDownFactor": 3.14, # Required. Fraction of required executors to remove from Spark Serverless clusters. A scale-down factor of 1.0 will result in scaling down so that there are no more executors for the Spark Job.(more aggressive scaling). A scale-down factor closer to 0 will result in a smaller magnitude of scaling donw (less aggressive scaling).Bounds: 0.0, 1.0.
              "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
              "scaleUpFactor": 3.14, # Required. Fraction of required workers to add to Spark Standalone clusters. A scale-up factor of 1.0 will result in scaling up so that there are no more required workers for the Spark Job (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling).Bounds: 0.0, 1.0.
              "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
            },
            "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
              "gracefulDecommissionTimeout": "A String", # Required. Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
              "scaleDownFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
              "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
              "scaleUpFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
              "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
            },
          },
          "id": "A String", # Required. The policy id.The id must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). Cannot begin or end with underscore or hyphen. Must consist of between 3 and 50 characters.
          "labels": { # Optional. The labels to associate with this autoscaling policy. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with an autoscaling policy.
            "a_key": "A String",
          },
          "name": "A String", # Output only. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
          "secondaryWorkerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Optional. Describes how the autoscaler will operate for secondary workers.
            "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
            "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
            "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
          },
          "workerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Required. Describes how the autoscaler will operate for primary workers.
            "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
            "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
            "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
          },
        },
      ],
    }

`list_next(previous_request, previous_response)`

    Retrieves the next page of results.

    Args:
      previous_request: The request for the previous page. (required)
      previous_response: The response from the request for the previous page. (required)

    Returns:
      A request object that you can call 'execute()' on to request the next
      page. Returns None if there are no more items in the collection.

`setIamPolicy(resource, body=None, x__xgafv=None)`

    Sets the access control policy on the specified resource. Replaces any existing policy.Can return NOT_FOUND, INVALID_ARGUMENT, and PERMISSION_DENIED errors.

    Args:
      resource: string, REQUIRED: The resource for which the policy is being specified. See the operation documentation for the appropriate value for this field. (required)
      body: object, The request body.
        The object takes the form of:

    { # Request message for SetIamPolicy method.
      "policy": { # An Identity and Access Management (IAM) policy, which specifies access controls for Google Cloud resources.A Policy is a collection of bindings. A binding binds one or more members, or principals, to a single role. Principals can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions; each role can be an IAM predefined role or a user-created custom role.For some types of Google Cloud resources, a binding can also specify a condition, which is a logical expression that allows access to a resource only if the expression evaluates to true. A condition can add constraints based on attributes of the request, the resource, or both. To learn which resources support conditions in their IAM policies, see the IAM documentation (https://cloud.google.com/iam/help/conditions/resource-policies).JSON example: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": [ "user:eve@example.com" ], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01T00:00:00.000Z')", } } ], "etag": "BwWWja0YfJA=", "version": 3 } YAML example: bindings: - members: - user:mike@example.com - group:admins@example.com - domain:google.com - serviceAccount:my-project-id@appspot.gserviceaccount.com role: roles/resourcemanager.organizationAdmin - members: - user:eve@example.com role: roles/resourcemanager.organizationViewer condition: title: expirable access description: Does not grant access after Sep 2020 expression: request.time < timestamp('2020-10-01T00:00:00.000Z') etag: BwWWja0YfJA= version: 3 For a description of IAM and its features, see the IAM documentation (https://cloud.google.com/iam/docs/). # REQUIRED: The complete policy to be applied to the resource. The size of the policy is limited to a few 10s of KB. An empty policy is a valid policy but certain Cloud Platform services (such as Projects) might reject them.
        "bindings": [ # Associates a list of members, or principals, with a role. Optionally, may specify a condition that determines how and when the bindings are applied. Each of the bindings must contain at least one principal.The bindings in a Policy can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the bindings grant 50 different roles to user:alice@example.com, and not to any other principal, then you can add another 1,450 principals to the bindings in the Policy.
          { # Associates members, or principals, with a role.
            "condition": { # Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec.Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information. # The condition that is associated with this binding.If the condition evaluates to true, then this binding applies to the current request.If the condition evaluates to false, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding.To learn which resources support conditions in their IAM policies, see the IAM documentation (https://cloud.google.com/iam/help/conditions/resource-policies).
              "description": "A String", # Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
              "expression": "A String", # Textual representation of an expression in Common Expression Language syntax.
              "location": "A String", # Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
              "title": "A String", # Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
            },
            "members": [ # Specifies the principals requesting access for a Cloud Platform resource. members can have the following values: allUsers: A special identifier that represents anyone who is on the internet; with or without a Google account. allAuthenticatedUsers: A special identifier that represents anyone who is authenticated with a Google account or a service account. user:{emailid}: An email address that represents a specific Google account. For example, alice@example.com . serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com. group:{emailid}: An email address that represents a Google group. For example, admins@example.com. deleted:user:{emailid}?uid={uniqueid}: An email address (plus unique identifier) representing a user that has been recently deleted. For example, alice@example.com?uid=123456789012345678901. If the user is recovered, this value reverts to user:{emailid} and the recovered user retains the role in the binding. deleted:serviceAccount:{emailid}?uid={uniqueid}: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901. If the service account is undeleted, this value reverts to serviceAccount:{emailid} and the undeleted service account retains the role in the binding. deleted:group:{emailid}?uid={uniqueid}: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, admins@example.com?uid=123456789012345678901. If the group is recovered, this value reverts to group:{emailid} and the recovered group retains the role in the binding. domain:{domain}: The G Suite domain (primary) that represents all the users of that domain. For example, google.com or example.com.
              "A String",
            ],
            "role": "A String", # Role that is assigned to the list of members, or principals. For example, roles/viewer, roles/editor, or roles/owner.
          },
        ],
        "etag": "A String", # etag is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the etag in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An etag is returned in the response to getIamPolicy, and systems are expected to put that etag in the request to setIamPolicy to ensure that their change will be applied to the same version of the policy.Important: If you use IAM Conditions, you must include the etag field whenever you call setIamPolicy. If you omit this field, then IAM allows you to overwrite a version 3 policy with a version 1 policy, and all of the conditions in the version 3 policy are lost.
        "version": 42, # Specifies the format of the policy.Valid values are 0, 1, and 3. Requests that specify an invalid value are rejected.Any operation that affects conditional role bindings must specify version 3. This requirement applies to the following operations: Getting a policy that includes a conditional role binding Adding a conditional role binding to a policy Changing a conditional role binding in a policy Removing any role binding, with or without a condition, from a policy that includes conditionsImportant: If you use IAM Conditions, you must include the etag field whenever you call setIamPolicy. If you omit this field, then IAM allows you to overwrite a version 3 policy with a version 1 policy, and all of the conditions in the version 3 policy are lost.If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset.To learn which resources support conditions in their IAM policies, see the IAM documentation (https://cloud.google.com/iam/help/conditions/resource-policies).
      },
    }

      x__xgafv: string, V1 error format.
        Allowed values
          1 - v1 error format
          2 - v2 error format

    Returns:
      An object of the form:

        { # An Identity and Access Management (IAM) policy, which specifies access controls for Google Cloud resources.A Policy is a collection of bindings. A binding binds one or more members, or principals, to a single role. Principals can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions; each role can be an IAM predefined role or a user-created custom role.For some types of Google Cloud resources, a binding can also specify a condition, which is a logical expression that allows access to a resource only if the expression evaluates to true. A condition can add constraints based on attributes of the request, the resource, or both. To learn which resources support conditions in their IAM policies, see the IAM documentation (https://cloud.google.com/iam/help/conditions/resource-policies).JSON example: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": [ "user:eve@example.com" ], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01T00:00:00.000Z')", } } ], "etag": "BwWWja0YfJA=", "version": 3 } YAML example: bindings: - members: - user:mike@example.com - group:admins@example.com - domain:google.com - serviceAccount:my-project-id@appspot.gserviceaccount.com role: roles/resourcemanager.organizationAdmin - members: - user:eve@example.com role: roles/resourcemanager.organizationViewer condition: title: expirable access description: Does not grant access after Sep 2020 expression: request.time < timestamp('2020-10-01T00:00:00.000Z') etag: BwWWja0YfJA= version: 3 For a description of IAM and its features, see the IAM documentation (https://cloud.google.com/iam/docs/).
      "bindings": [ # Associates a list of members, or principals, with a role. Optionally, may specify a condition that determines how and when the bindings are applied. Each of the bindings must contain at least one principal.The bindings in a Policy can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the bindings grant 50 different roles to user:alice@example.com, and not to any other principal, then you can add another 1,450 principals to the bindings in the Policy.
        { # Associates members, or principals, with a role.
          "condition": { # Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec.Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information. # The condition that is associated with this binding.If the condition evaluates to true, then this binding applies to the current request.If the condition evaluates to false, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding.To learn which resources support conditions in their IAM policies, see the IAM documentation (https://cloud.google.com/iam/help/conditions/resource-policies).
            "description": "A String", # Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
            "expression": "A String", # Textual representation of an expression in Common Expression Language syntax.
            "location": "A String", # Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
            "title": "A String", # Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
          },
          "members": [ # Specifies the principals requesting access for a Cloud Platform resource. members can have the following values: allUsers: A special identifier that represents anyone who is on the internet; with or without a Google account. allAuthenticatedUsers: A special identifier that represents anyone who is authenticated with a Google account or a service account. user:{emailid}: An email address that represents a specific Google account. For example, alice@example.com . serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com. group:{emailid}: An email address that represents a Google group. For example, admins@example.com. deleted:user:{emailid}?uid={uniqueid}: An email address (plus unique identifier) representing a user that has been recently deleted. For example, alice@example.com?uid=123456789012345678901. If the user is recovered, this value reverts to user:{emailid} and the recovered user retains the role in the binding. deleted:serviceAccount:{emailid}?uid={uniqueid}: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901. If the service account is undeleted, this value reverts to serviceAccount:{emailid} and the undeleted service account retains the role in the binding. deleted:group:{emailid}?uid={uniqueid}: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, admins@example.com?uid=123456789012345678901. If the group is recovered, this value reverts to group:{emailid} and the recovered group retains the role in the binding. domain:{domain}: The G Suite domain (primary) that represents all the users of that domain. For example, google.com or example.com.
            "A String",
          ],
          "role": "A String", # Role that is assigned to the list of members, or principals. For example, roles/viewer, roles/editor, or roles/owner.
        },
      ],
      "etag": "A String", # etag is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the etag in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An etag is returned in the response to getIamPolicy, and systems are expected to put that etag in the request to setIamPolicy to ensure that their change will be applied to the same version of the policy.Important: If you use IAM Conditions, you must include the etag field whenever you call setIamPolicy. If you omit this field, then IAM allows you to overwrite a version 3 policy with a version 1 policy, and all of the conditions in the version 3 policy are lost.
      "version": 42, # Specifies the format of the policy.Valid values are 0, 1, and 3. Requests that specify an invalid value are rejected.Any operation that affects conditional role bindings must specify version 3. This requirement applies to the following operations: Getting a policy that includes a conditional role binding Adding a conditional role binding to a policy Changing a conditional role binding in a policy Removing any role binding, with or without a condition, from a policy that includes conditionsImportant: If you use IAM Conditions, you must include the etag field whenever you call setIamPolicy. If you omit this field, then IAM allows you to overwrite a version 3 policy with a version 1 policy, and all of the conditions in the version 3 policy are lost.If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset.To learn which resources support conditions in their IAM policies, see the IAM documentation (https://cloud.google.com/iam/help/conditions/resource-policies).
    }

`testIamPermissions(resource, body=None, x__xgafv=None)`

    Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a NOT_FOUND error.Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.

    Args:
      resource: string, REQUIRED: The resource for which the policy detail is being requested. See the operation documentation for the appropriate value for this field. (required)
      body: object, The request body.
        The object takes the form of:

    { # Request message for TestIamPermissions method.
      "permissions": [ # The set of permissions to check for the resource. Permissions with wildcards (such as '*' or 'storage.*') are not allowed. For more information see IAM Overview (https://cloud.google.com/iam/docs/overview#permissions).
        "A String",
      ],
    }

      x__xgafv: string, V1 error format.
        Allowed values
          1 - v1 error format
          2 - v2 error format

    Returns:
      An object of the form:

        { # Response message for TestIamPermissions method.
      "permissions": [ # A subset of TestPermissionsRequest.permissions that the caller is allowed.
        "A String",
      ],
    }

`update(name, body=None, x__xgafv=None)`

    Updates (replaces) autoscaling policy.Disabled check for update_mask, because all updates will be full replacements.

    Args:
      name: string, Output only. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id} (required)
      body: object, The request body.
        The object takes the form of:

    { # Describes an autoscaling policy for Dataproc cluster autoscaler.
      "basicAlgorithm": { # Basic algorithm for autoscaling.
        "cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
        "sparkStandaloneConfig": { # Basic autoscaling configurations for Spark Standalone. # Optional. Spark Standalone autoscaling configuration
          "gracefulDecommissionTimeout": "A String", # Required. Timeout for Spark graceful decommissioning of spark workers. Specifies the duration to wait for spark worker to complete spark decomissioning tasks before forcefully removing workers. Only applicable to downscaling operations.Bounds: 0s, 1d.
          "scaleDownFactor": 3.14, # Required. Fraction of required executors to remove from Spark Serverless clusters. A scale-down factor of 1.0 will result in scaling down so that there are no more executors for the Spark Job.(more aggressive scaling). A scale-down factor closer to 0 will result in a smaller magnitude of scaling donw (less aggressive scaling).Bounds: 0.0, 1.0.
          "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
          "scaleUpFactor": 3.14, # Required. Fraction of required workers to add to Spark Standalone clusters. A scale-up factor of 1.0 will result in scaling up so that there are no more required workers for the Spark Job (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling).Bounds: 0.0, 1.0.
          "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
        },
        "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
          "gracefulDecommissionTimeout": "A String", # Required. Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
          "scaleDownFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
          "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
          "scaleUpFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
          "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
        },
      },
      "id": "A String", # Required. The policy id.The id must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). Cannot begin or end with underscore or hyphen. Must consist of between 3 and 50 characters.
      "labels": { # Optional. The labels to associate with this autoscaling policy. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with an autoscaling policy.
        "a_key": "A String",
      },
      "name": "A String", # Output only. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
      "secondaryWorkerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Optional. Describes how the autoscaler will operate for secondary workers.
        "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
        "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
        "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
      },
      "workerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Required. Describes how the autoscaler will operate for primary workers.
        "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
        "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
        "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
      },
    }

      x__xgafv: string, V1 error format.
        Allowed values
          1 - v1 error format
          2 - v2 error format

    Returns:
      An object of the form:

        { # Describes an autoscaling policy for Dataproc cluster autoscaler.
      "basicAlgorithm": { # Basic algorithm for autoscaling.
        "cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
        "sparkStandaloneConfig": { # Basic autoscaling configurations for Spark Standalone. # Optional. Spark Standalone autoscaling configuration
          "gracefulDecommissionTimeout": "A String", # Required. Timeout for Spark graceful decommissioning of spark workers. Specifies the duration to wait for spark worker to complete spark decomissioning tasks before forcefully removing workers. Only applicable to downscaling operations.Bounds: 0s, 1d.
          "scaleDownFactor": 3.14, # Required. Fraction of required executors to remove from Spark Serverless clusters. A scale-down factor of 1.0 will result in scaling down so that there are no more executors for the Spark Job.(more aggressive scaling). A scale-down factor closer to 0 will result in a smaller magnitude of scaling donw (less aggressive scaling).Bounds: 0.0, 1.0.
          "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
          "scaleUpFactor": 3.14, # Required. Fraction of required workers to add to Spark Standalone clusters. A scale-up factor of 1.0 will result in scaling up so that there are no more required workers for the Spark Job (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling).Bounds: 0.0, 1.0.
          "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
        },
        "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
          "gracefulDecommissionTimeout": "A String", # Required. Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
          "scaleDownFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
          "scaleDownMinWorkerFraction": 3.14, # Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
          "scaleUpFactor": 3.14, # Required. Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.
          "scaleUpMinWorkerFraction": 3.14, # Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
        },
      },
      "id": "A String", # Required. The policy id.The id must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). Cannot begin or end with underscore or hyphen. Must consist of between 3 and 50 characters.
      "labels": { # Optional. The labels to associate with this autoscaling policy. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with an autoscaling policy.
        "a_key": "A String",
      },
      "name": "A String", # Output only. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
      "secondaryWorkerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Optional. Describes how the autoscaler will operate for secondary workers.
        "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
        "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
        "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
      },
      "workerConfig": { # Configuration for the size bounds of an instance group, including its proportional size to other groups. # Required. Describes how the autoscaler will operate for primary workers.
        "maxInstances": 42, # Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
        "minInstances": 42, # Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
        "weight": 42, # Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
      },
    }