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SpecialistPoolServiceClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.aiplatform_v1.services.specialist_pool_service.transports.base.SpecialistPoolServiceTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
A service for creating and managing Customer SpecialistPools. When customers start Data Labeling jobs, they can reuse/create Specialist Pools to bring their own Specialists to label the data. Customers can add/remove Managers for the Specialist Pool on Cloud console, then Managers will get email notifications to manage Specialists and tasks on CrowdCompute console.
Inheritance
builtins.object > SpecialistPoolServiceClientProperties
transport
Returns the transport used by the client instance.
Type | Description |
SpecialistPoolServiceTransport | The transport used by the client instance. |
Methods
SpecialistPoolServiceClient
SpecialistPoolServiceClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.aiplatform_v1.services.specialist_pool_service.transports.base.SpecialistPoolServiceTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
Instantiates the specialist pool service client.
Name | Description |
credentials |
Optional[google.auth.credentials.Credentials]
The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment. |
transport |
Union[str, SpecialistPoolServiceTransport]
The transport to use. If set to None, a transport is chosen automatically. |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. It won't take effect if a |
client_info |
google.api_core.gapic_v1.client_info.ClientInfo
The client info used to send a user-agent string along with API requests. If |
Type | Description |
google.auth.exceptions.MutualTLSChannelError | If mutual TLS transport creation failed for any reason. |
__exit__
__exit__(type, value, traceback)
Releases underlying transport's resources.
common_billing_account_path
common_billing_account_path(billing_account: str)
Returns a fully-qualified billing_account string.
common_folder_path
common_folder_path(folder: str)
Returns a fully-qualified folder string.
common_location_path
common_location_path(project: str, location: str)
Returns a fully-qualified location string.
common_organization_path
common_organization_path(organization: str)
Returns a fully-qualified organization string.
common_project_path
common_project_path(project: str)
Returns a fully-qualified project string.
create_specialist_pool
create_specialist_pool(request: Optional[Union[google.cloud.aiplatform_v1.types.specialist_pool_service.CreateSpecialistPoolRequest, dict]] = None, *, parent: Optional[str] = None, specialist_pool: Optional[google.cloud.aiplatform_v1.types.specialist_pool.SpecialistPool] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates a SpecialistPool.
from google.cloud import aiplatform_v1
def sample_create_specialist_pool():
# Create a client
client = aiplatform_v1.SpecialistPoolServiceClient()
# Initialize request argument(s)
specialist_pool = aiplatform_v1.SpecialistPool()
specialist_pool.name = "name_value"
specialist_pool.display_name = "display_name_value"
request = aiplatform_v1.CreateSpecialistPoolRequest(
parent="parent_value",
specialist_pool=specialist_pool,
)
# Make the request
operation = client.create_specialist_pool(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.CreateSpecialistPoolRequest, dict]
The request object. Request message for SpecialistPoolService.CreateSpecialistPool. |
parent |
str
Required. The parent Project name for the new SpecialistPool. The form is |
specialist_pool |
google.cloud.aiplatform_v1.types.SpecialistPool
Required. The SpecialistPool to create. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.api_core.operation.Operation | An object representing a long-running operation. The result type for the operation will be SpecialistPool SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console. |
delete_specialist_pool
delete_specialist_pool(request: Optional[Union[google.cloud.aiplatform_v1.types.specialist_pool_service.DeleteSpecialistPoolRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Deletes a SpecialistPool as well as all Specialists in the pool.
from google.cloud import aiplatform_v1
def sample_delete_specialist_pool():
# Create a client
client = aiplatform_v1.SpecialistPoolServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.DeleteSpecialistPoolRequest(
name="name_value",
)
# Make the request
operation = client.delete_specialist_pool(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.DeleteSpecialistPoolRequest, dict]
The request object. Request message for SpecialistPoolService.DeleteSpecialistPool. |
name |
str
Required. The resource name of the SpecialistPool to delete. Format: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.api_core.operation.Operation | An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` 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); } The JSON representation for Empty is empty JSON object {}. |
from_service_account_file
from_service_account_file(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
SpecialistPoolServiceClient | The constructed client. |
from_service_account_info
from_service_account_info(info: dict, *args, **kwargs)
Creates an instance of this client using the provided credentials info.
Name | Description |
info |
dict
The service account private key info. |
Type | Description |
SpecialistPoolServiceClient | The constructed client. |
from_service_account_json
from_service_account_json(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
SpecialistPoolServiceClient | The constructed client. |
get_mtls_endpoint_and_cert_source
get_mtls_endpoint_and_cert_source(
client_options: Optional[google.api_core.client_options.ClientOptions] = None,
)
Return the API endpoint and client cert source for mutual TLS.
The client cert source is determined in the following order:
(1) if GOOGLE_API_USE_CLIENT_CERTIFICATE
environment variable is not "true", the
client cert source is None.
(2) if client_options.client_cert_source
is provided, use the provided one; if the
default client cert source exists, use the default one; otherwise the client cert
source is None.
The API endpoint is determined in the following order:
(1) if client_options.api_endpoint
if provided, use the provided one.
(2) if GOOGLE_API_USE_CLIENT_CERTIFICATE
environment variable is "always", use the
default mTLS endpoint; if the environment variabel is "never", use the default API
endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
use the default API endpoint.
More details can be found at https://google.aip.dev/auth/4114.
Name | Description |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. Only the |
Type | Description |
google.auth.exceptions.MutualTLSChannelError | If any errors happen. |
Type | Description |
Tuple[str, Callable[[], Tuple[bytes, bytes]]] | returns the API endpoint and the client cert source to use. |
get_specialist_pool
get_specialist_pool(request: Optional[Union[google.cloud.aiplatform_v1.types.specialist_pool_service.GetSpecialistPoolRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a SpecialistPool.
from google.cloud import aiplatform_v1
def sample_get_specialist_pool():
# Create a client
client = aiplatform_v1.SpecialistPoolServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.GetSpecialistPoolRequest(
name="name_value",
)
# Make the request
response = client.get_specialist_pool(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.GetSpecialistPoolRequest, dict]
The request object. Request message for SpecialistPoolService.GetSpecialistPool. |
name |
str
Required. The name of the SpecialistPool resource. The form is |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.cloud.aiplatform_v1.types.SpecialistPool | SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console. |
list_specialist_pools
list_specialist_pools(request: Optional[Union[google.cloud.aiplatform_v1.types.specialist_pool_service.ListSpecialistPoolsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists SpecialistPools in a Location.
from google.cloud import aiplatform_v1
def sample_list_specialist_pools():
# Create a client
client = aiplatform_v1.SpecialistPoolServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.ListSpecialistPoolsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_specialist_pools(request=request)
# Handle the response
for response in page_result:
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.ListSpecialistPoolsRequest, dict]
The request object. Request message for SpecialistPoolService.ListSpecialistPools. |
parent |
str
Required. The name of the SpecialistPool's parent resource. Format: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.cloud.aiplatform_v1.services.specialist_pool_service.pagers.ListSpecialistPoolsPager | Response message for SpecialistPoolService.ListSpecialistPools. Iterating over this object will yield results and resolve additional pages automatically. |
parse_common_billing_account_path
parse_common_billing_account_path(path: str)
Parse a billing_account path into its component segments.
parse_common_folder_path
parse_common_folder_path(path: str)
Parse a folder path into its component segments.
parse_common_location_path
parse_common_location_path(path: str)
Parse a location path into its component segments.
parse_common_organization_path
parse_common_organization_path(path: str)
Parse a organization path into its component segments.
parse_common_project_path
parse_common_project_path(path: str)
Parse a project path into its component segments.
parse_specialist_pool_path
parse_specialist_pool_path(path: str)
Parses a specialist_pool path into its component segments.
specialist_pool_path
specialist_pool_path(project: str, location: str, specialist_pool: str)
Returns a fully-qualified specialist_pool string.
update_specialist_pool
update_specialist_pool(request: Optional[Union[google.cloud.aiplatform_v1.types.specialist_pool_service.UpdateSpecialistPoolRequest, dict]] = None, *, specialist_pool: Optional[google.cloud.aiplatform_v1.types.specialist_pool.SpecialistPool] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Updates a SpecialistPool.
from google.cloud import aiplatform_v1
def sample_update_specialist_pool():
# Create a client
client = aiplatform_v1.SpecialistPoolServiceClient()
# Initialize request argument(s)
specialist_pool = aiplatform_v1.SpecialistPool()
specialist_pool.name = "name_value"
specialist_pool.display_name = "display_name_value"
request = aiplatform_v1.UpdateSpecialistPoolRequest(
specialist_pool=specialist_pool,
)
# Make the request
operation = client.update_specialist_pool(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.UpdateSpecialistPoolRequest, dict]
The request object. Request message for SpecialistPoolService.UpdateSpecialistPool. |
specialist_pool |
google.cloud.aiplatform_v1.types.SpecialistPool
Required. The SpecialistPool which replaces the resource on the server. This corresponds to the |
update_mask |
google.protobuf.field_mask_pb2.FieldMask
Required. The update mask applies to the resource. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.api_core.operation.Operation | An object representing a long-running operation. The result type for the operation will be SpecialistPool SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console. |