class_docstr: NOTE: This class is auto generated by OpenAPI Generator
  Ref: https://openapi-generator.tech
  
  Do not edit the class manually.
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docstr: get_active_learning_v2_scores_by_dataset_id  # noqa: E501
  
  Get all AL score types by datasetId and predictionUUIDTimestamp  # noqa: E501
  This method makes a synchronous HTTP request by default. To make an
  asynchronous HTTP request, please pass async_req=True
  
  >>> thread = api.get_active_learning_v2_scores_by_dataset_id(dataset_id, prediction_uuid_timestamp, async_req=True)
  >>> result = thread.get()
  
  :param dataset_id: ObjectId of the dataset (required)
  :type dataset_id: str
  :param prediction_uuid_timestamp: Deprecated, currently ignored. The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. 
  :type prediction_uuid_timestamp: int
  :param async_req: Whether to execute the request asynchronously.
  :type async_req: bool, optional
  :param _request_timeout: timeout setting for this request. If one
                           number provided, it will be total request
                           timeout. It can also be a pair (tuple) of
                           (connection, read) timeouts.
  :return: Returns the result object.
           If the method is called asynchronously,
           returns the request thread.
  :rtype: List[ActiveLearningScoreTypesV2Data]
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code: def get_active_learning_v2_scores_by_dataset_id(
      self,
      dataset_id: Annotated[
          constr(strict=True),
          Field(..., description="ObjectId of the dataset"),
      ],
      prediction_uuid_timestamp: Annotated[
          Optional[conint(strict=True, ge=0)],
          Field(
              description="Deprecated, currently ignored. The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset. "
          ),
      ] = None,
      **kwargs,
  ) -> List[ActiveLearningScoreTypesV2Data]:  # noqa: E501
      """get_active_learning_v2_scores_by_dataset_id  # noqa: E501
  
      Get all AL score types by datasetId and predictionUUIDTimestamp  # noqa: E501
      This method makes a synchronous HTTP request by default. To make an
      asynchronous HTTP request, please pass async_req=True
  
      >>> thread = api.get_active_learning_v2_scores_by_dataset_id(dataset_id, prediction_uuid_timestamp, async_req=True)
      >>> result = thread.get()
  
      :param dataset_id: ObjectId of the dataset (required)
      :type dataset_id: str
      :param prediction_uuid_timestamp: Deprecated, currently ignored. The timestamp of when the actual predictions were created. This is used as a peg to version predictions. E.g one could upload predictions on day 1 and then create new predictions with an improved model on day 30. One can then upload the new predictions to the same dataset.
      :type prediction_uuid_timestamp: int
      :param async_req: Whether to execute the request asynchronously.
      :type async_req: bool, optional
      :param _request_timeout: timeout setting for this request. If one
                               number provided, it will be total request
                               timeout. It can also be a pair (tuple) of
                               (connection, read) timeouts.
      :return: Returns the result object.
               If the method is called asynchronously,
               returns the request thread.
      :rtype: List[ActiveLearningScoreTypesV2Data]
      """
      kwargs["_return_http_data_only"] = True
      if "_preload_content" in kwargs:
          raise ValueError(
              "Error! Please call the get_active_learning_v2_scores_by_dataset_id_with_http_info method with `_preload_content` instead and obtain raw data from ApiResponse.raw_data"
          )
      return self.get_active_learning_v2_scores_by_dataset_id_with_http_info(
          dataset_id, prediction_uuid_timestamp, **kwargs
      )
  
imports: import re
  import io
  import warnings
  from pydantic import validate_arguments, ValidationError
  from typing_extensions import Annotated
  from pydantic import Field, conint, constr, validator
  from typing import List, Optional
  from lightly.openapi_generated.swagger_client.models.active_learning_score_create_request import ActiveLearningScoreCreateRequest
  from lightly.openapi_generated.swagger_client.models.active_learning_score_data import ActiveLearningScoreData
  from lightly.openapi_generated.swagger_client.models.active_learning_score_types_v2_data import ActiveLearningScoreTypesV2Data
  from lightly.openapi_generated.swagger_client.models.active_learning_score_v2_data import ActiveLearningScoreV2Data
  from lightly.openapi_generated.swagger_client.models.create_entity_response import CreateEntityResponse
  from lightly.openapi_generated.swagger_client.models.tag_active_learning_scores_data import TagActiveLearningScoresData
  from lightly.openapi_generated.swagger_client.api_client import ApiClient
  from lightly.openapi_generated.swagger_client.api_response import ApiResponse
  from lightly.openapi_generated.swagger_client.exceptions import ApiTypeError, ApiValueError
label_desc: Use image node_id 12 for calling the ScoresApi obj's underlying member method code with example usage: obj.get_active_learning_v2_scores_by_dataset_id(dataset_id, prediction_uuid_timestamp) and returns: self