close()

Close httplib2 connections.

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

Creates a Dataset.

Args:
parent: string, Required. The resource name of the Location to create the Dataset in. Format: `projects/{project}/locations/{location}` (required)
body: object, The request body.
The object takes the form of:

{ # A collection of DataItems and Annotations on them.
"createTime": "A String", # Output only. Timestamp when this Dataset was created.
"dataItemCount": "A String", # Output only. The number of DataItems in this Dataset. Only apply for non-structured Dataset.
"description": "A String", # The description of the Dataset.
"displayName": "A String", # Required. The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"etag": "A String", # Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title.
"a_key": "A String",
},
"metadata": "", # Required. Additional information about the Dataset.
"metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
"metadataSchemaUri": "A String", # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
"modelReference": "A String", # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
"name": "A String", # Output only. Identifier. The resource name of the Dataset.
"satisfiesPzi": True or False, # Output only. Reserved for future use.
"satisfiesPzs": True or False, # Output only. Reserved for future use.
"savedQueries": [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
{ # A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
"annotationFilter": "A String", # Output only. Filters on the Annotations in the dataset.
"annotationSpecCount": 42, # Output only. Number of AnnotationSpecs in the context of the SavedQuery.
"createTime": "A String", # Output only. Timestamp when this SavedQuery was created.
"displayName": "A String", # Required. The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"etag": "A String", # Used to perform a consistent read-modify-write update. If not set, a blind "overwrite" update happens.
"metadata": "", # Some additional information about the SavedQuery.
"name": "A String", # Output only. Resource name of the SavedQuery.
"problemType": "A String", # Required. Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING
"supportAutomlTraining": True or False, # Output only. If the Annotations belonging to the SavedQuery can be used for AutoML training.
"updateTime": "A String", # Output only. Timestamp when SavedQuery was last updated.
},
],
"updateTime": "A String", # Output only. Timestamp when this Dataset was last updated.
}

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

Returns:
An object of the form:

{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}

delete(name, x__xgafv=None)

Deletes a Dataset.

Args:
name: string, Required. The resource name of the Dataset to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}

export(name, body=None, x__xgafv=None)

Exports data from a Dataset.

Args:
name: string, Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}` (required)
body: object, The request body.
The object takes the form of:

{ # Request message for DatasetService.ExportData.
"exportConfig": { # Describes what part of the Dataset is to be exported, the destination of the export and how to export. # Required. The desired output location.
"annotationsFilter": "A String", # An expression for filtering what part of the Dataset is to be exported. Only Annotations that match this filter will be exported. The filter syntax is the same as in ListAnnotations.
"fractionSplit": { # Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test. # Split based on fractions defining the size of each set.
"testFraction": 3.14, # The fraction of the input data that is to be used to evaluate the Model.
"trainingFraction": 3.14, # The fraction of the input data that is to be used to train the Model.
"validationFraction": 3.14, # The fraction of the input data that is to be used to validate the Model.
},
"gcsDestination": { # The Google Cloud Storage location where the output is to be written to. # The Google Cloud Storage location where the output is to be written to. In the given directory a new directory will be created with name: `export-data--` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All export output will be written into that directory. Inside that directory, annotations with the same schema will be grouped into sub directories which are named with the corresponding annotations' schema title. Inside these sub directories, a schema.yaml will be created to describe the output format.
"outputUriPrefix": "A String", # Required. Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
},
},
}

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

Returns:
An object of the form:

{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}

get(name, readMask=None, x__xgafv=None)

Gets a Dataset.

Args:
  name: string, Required. The name of the Dataset resource. (required)
  readMask: string, Mask specifying which fields to read.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A collection of DataItems and Annotations on them.
  "createTime": "A String", # Output only. Timestamp when this Dataset was created.
  "dataItemCount": "A String", # Output only. The number of DataItems in this Dataset. Only apply for non-structured Dataset.
  "description": "A String", # The description of the Dataset.
  "displayName": "A String", # Required. The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.
  "encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key.
    "kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
  },
  "etag": "A String", # Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
  "labels": { # The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title.
    "a_key": "A String",
  },
  "metadata": "", # Required. Additional information about the Dataset.
  "metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
  "metadataSchemaUri": "A String", # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
  "modelReference": "A String", # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
  "name": "A String", # Output only. Identifier. The resource name of the Dataset.
  "satisfiesPzi": True or False, # Output only. Reserved for future use.
  "satisfiesPzs": True or False, # Output only. Reserved for future use.
  "savedQueries": [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
    { # A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
      "annotationFilter": "A String", # Output only. Filters on the Annotations in the dataset.
      "annotationSpecCount": 42, # Output only. Number of AnnotationSpecs in the context of the SavedQuery.
      "createTime": "A String", # Output only. Timestamp when this SavedQuery was created.
      "displayName": "A String", # Required. The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.
      "etag": "A String", # Used to perform a consistent read-modify-write update. If not set, a blind "overwrite" update happens.
      "metadata": "", # Some additional information about the SavedQuery.
      "name": "A String", # Output only. Resource name of the SavedQuery.
      "problemType": "A String", # Required. Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING
      "supportAutomlTraining": True or False, # Output only. If the Annotations belonging to the SavedQuery can be used for AutoML training.
      "updateTime": "A String", # Output only. Timestamp when SavedQuery was last updated.
    },
  ],
  "updateTime": "A String", # Output only. Timestamp when this Dataset was last updated.
}

import_(name, body=None, x__xgafv=None)

Imports data into a Dataset.

Args:
name: string, Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}` (required)
body: object, The request body.
The object takes the form of:

{ # Request message for DatasetService.ImportData.
"importConfigs": [ # Required. The desired input locations. The contents of all input locations will be imported in one batch.
{ # Describes the location from where we import data into a Dataset, together with the labels that will be applied to the DataItems and the Annotations.
"annotationLabels": { # Labels that will be applied to newly imported Annotations. If two Annotations are identical, one of them will be deduped. Two Annotations are considered identical if their payload, payload_schema_uri and all of their labels are the same. These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file.
"a_key": "A String",
},
"dataItemLabels": { # Labels that will be applied to newly imported DataItems. If an identical DataItem as one being imported already exists in the Dataset, then these labels will be appended to these of the already existing one, and if labels with identical key is imported before, the old label value will be overwritten. If two DataItems are identical in the same import data operation, the labels will be combined and if key collision happens in this case, one of the values will be picked randomly. Two DataItems are considered identical if their content bytes are identical (e.g. image bytes or pdf bytes). These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file.
"a_key": "A String",
},
"gcsSource": { # The Google Cloud Storage location for the input content. # The Google Cloud Storage location for the input content.
"uris": [ # Required. Google Cloud Storage URI(-s) to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames.
"A String",
],
},
"importSchemaUri": "A String", # Required. Points to a YAML file stored on Google Cloud Storage describing the import format. Validation will be done against the schema. The schema is defined as an [OpenAPI 3.0.2 Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
},
],
}

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

Returns:
An object of the form:

{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}

list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, readMask=None, x__xgafv=None)

Lists Datasets in a Location.

Args:
  parent: string, Required. The name of the Dataset's parent resource. Format: `projects/{project}/locations/{location}` (required)
  filter: string, An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `display_name`: supports = and != * `metadata_schema_uri`: supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels."a key"`. Some examples: * `displayName="myDisplayName"` * `labels.myKey="myValue"`
  orderBy: string, A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time`
  pageSize: integer, The standard list page size.
  pageToken: string, The standard list page token.
  readMask: string, Mask specifying which fields to read.
  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 DatasetService.ListDatasets.
  "datasets": [ # A list of Datasets that matches the specified filter in the request.
    { # A collection of DataItems and Annotations on them.
      "createTime": "A String", # Output only. Timestamp when this Dataset was created.
      "dataItemCount": "A String", # Output only. The number of DataItems in this Dataset. Only apply for non-structured Dataset.
      "description": "A String", # The description of the Dataset.
      "displayName": "A String", # Required. The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.
      "encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key.
        "kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
      },
      "etag": "A String", # Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
      "labels": { # The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title.
        "a_key": "A String",
      },
      "metadata": "", # Required. Additional information about the Dataset.
      "metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
      "metadataSchemaUri": "A String", # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
      "modelReference": "A String", # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
      "name": "A String", # Output only. Identifier. The resource name of the Dataset.
      "satisfiesPzi": True or False, # Output only. Reserved for future use.
      "satisfiesPzs": True or False, # Output only. Reserved for future use.
      "savedQueries": [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
        { # A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
          "annotationFilter": "A String", # Output only. Filters on the Annotations in the dataset.
          "annotationSpecCount": 42, # Output only. Number of AnnotationSpecs in the context of the SavedQuery.
          "createTime": "A String", # Output only. Timestamp when this SavedQuery was created.
          "displayName": "A String", # Required. The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.
          "etag": "A String", # Used to perform a consistent read-modify-write update. If not set, a blind "overwrite" update happens.
          "metadata": "", # Some additional information about the SavedQuery.
          "name": "A String", # Output only. Resource name of the SavedQuery.
          "problemType": "A String", # Required. Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING
          "supportAutomlTraining": True or False, # Output only. If the Annotations belonging to the SavedQuery can be used for AutoML training.
          "updateTime": "A String", # Output only. Timestamp when SavedQuery was last updated.
        },
      ],
      "updateTime": "A String", # Output only. Timestamp when this Dataset was last updated.
    },
  ],
  "nextPageToken": "A String", # The standard List next-page token.
}

list_next()

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.

patch(name, body=None, updateMask=None, x__xgafv=None)

Updates a Dataset.

Args:
  name: string, Output only. Identifier. The resource name of the Dataset. (required)
  body: object, The request body.
    The object takes the form of:

{ # A collection of DataItems and Annotations on them.
  "createTime": "A String", # Output only. Timestamp when this Dataset was created.
  "dataItemCount": "A String", # Output only. The number of DataItems in this Dataset. Only apply for non-structured Dataset.
  "description": "A String", # The description of the Dataset.
  "displayName": "A String", # Required. The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.
  "encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key.
    "kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
  },
  "etag": "A String", # Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
  "labels": { # The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title.
    "a_key": "A String",
  },
  "metadata": "", # Required. Additional information about the Dataset.
  "metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
  "metadataSchemaUri": "A String", # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
  "modelReference": "A String", # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
  "name": "A String", # Output only. Identifier. The resource name of the Dataset.
  "satisfiesPzi": True or False, # Output only. Reserved for future use.
  "satisfiesPzs": True or False, # Output only. Reserved for future use.
  "savedQueries": [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
    { # A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
      "annotationFilter": "A String", # Output only. Filters on the Annotations in the dataset.
      "annotationSpecCount": 42, # Output only. Number of AnnotationSpecs in the context of the SavedQuery.
      "createTime": "A String", # Output only. Timestamp when this SavedQuery was created.
      "displayName": "A String", # Required. The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.
      "etag": "A String", # Used to perform a consistent read-modify-write update. If not set, a blind "overwrite" update happens.
      "metadata": "", # Some additional information about the SavedQuery.
      "name": "A String", # Output only. Resource name of the SavedQuery.
      "problemType": "A String", # Required. Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING
      "supportAutomlTraining": True or False, # Output only. If the Annotations belonging to the SavedQuery can be used for AutoML training.
      "updateTime": "A String", # Output only. Timestamp when SavedQuery was last updated.
    },
  ],
  "updateTime": "A String", # Output only. Timestamp when this Dataset was last updated.
}

  updateMask: string, Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name` * `description` * `labels`
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A collection of DataItems and Annotations on them.
  "createTime": "A String", # Output only. Timestamp when this Dataset was created.
  "dataItemCount": "A String", # Output only. The number of DataItems in this Dataset. Only apply for non-structured Dataset.
  "description": "A String", # The description of the Dataset.
  "displayName": "A String", # Required. The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.
  "encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key.
    "kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
  },
  "etag": "A String", # Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
  "labels": { # The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title.
    "a_key": "A String",
  },
  "metadata": "", # Required. Additional information about the Dataset.
  "metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
  "metadataSchemaUri": "A String", # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
  "modelReference": "A String", # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
  "name": "A String", # Output only. Identifier. The resource name of the Dataset.
  "satisfiesPzi": True or False, # Output only. Reserved for future use.
  "satisfiesPzs": True or False, # Output only. Reserved for future use.
  "savedQueries": [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
    { # A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
      "annotationFilter": "A String", # Output only. Filters on the Annotations in the dataset.
      "annotationSpecCount": 42, # Output only. Number of AnnotationSpecs in the context of the SavedQuery.
      "createTime": "A String", # Output only. Timestamp when this SavedQuery was created.
      "displayName": "A String", # Required. The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.
      "etag": "A String", # Used to perform a consistent read-modify-write update. If not set, a blind "overwrite" update happens.
      "metadata": "", # Some additional information about the SavedQuery.
      "name": "A String", # Output only. Resource name of the SavedQuery.
      "problemType": "A String", # Required. Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING
      "supportAutomlTraining": True or False, # Output only. If the Annotations belonging to the SavedQuery can be used for AutoML training.
      "updateTime": "A String", # Output only. Timestamp when SavedQuery was last updated.
    },
  ],
  "updateTime": "A String", # Output only. Timestamp when this Dataset was last updated.
}

searchDataItems(dataset, annotationFilters=None, annotationsFilter=None, annotationsLimit=None, dataItemFilter=None, dataLabelingJob=None, fieldMask=None, orderBy=None, orderByAnnotation_orderBy=None, orderByAnnotation_savedQuery=None, orderByDataItem=None, pageSize=None, pageToken=None, savedQuery=None, x__xgafv=None)

Searches DataItems in a Dataset.

Args:
dataset: string, Required. The resource name of the Dataset from which to search DataItems. Format: `projects/{project}/locations/{location}/datasets/{dataset}` (required)
annotationFilters: string, An expression that specifies what Annotations will be returned per DataItem. Annotations satisfied either of the conditions will be returned. * `annotation_spec_id` - for = or !=. Must specify `saved_query_id=` - saved query id that annotations should belong to. (repeated)
annotationsFilter: string, An expression for filtering the Annotations that will be returned per DataItem. * `annotation_spec_id` - for = or !=.
annotationsLimit: integer, If set, only up to this many of Annotations will be returned per DataItemView. The maximum value is 1000. If not set, the maximum value will be used.
dataItemFilter: string, An expression for filtering the DataItem that will be returned. * `data_item_id` - for = or !=. * `labeled` - for = or !=. * `has_annotation(ANNOTATION_SPEC_ID)` - true only for DataItem that have at least one annotation with annotation_spec_id = `ANNOTATION_SPEC_ID` in the context of SavedQuery or DataLabelingJob. For example: * `data_item=1` * `has_annotation(5)`
dataLabelingJob: string, The resource name of a DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}` If this field is set, all of the search will be done in the context of this DataLabelingJob.
fieldMask: string, Mask specifying which fields of DataItemView to read.
orderBy: string, A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending.
orderByAnnotation_orderBy: string, A comma-separated list of annotation fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Must also specify saved_query.
orderByAnnotation_savedQuery: string, Required. Saved query of the Annotation. Only Annotations belong to this saved query will be considered for ordering.
orderByDataItem: string, A comma-separated list of data item fields to order by, sorted in ascending order. Use "desc" after a field name for descending.
pageSize: integer, Requested page size. Server may return fewer results than requested. Default and maximum page size is 100.
pageToken: string, A token identifying a page of results for the server to return Typically obtained via SearchDataItemsResponse.next_page_token of the previous DatasetService.SearchDataItems call.
savedQuery: string, The resource name of a SavedQuery(annotation set in UI). Format: `projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}` All of the search will be done in the context of this SavedQuery.
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 DatasetService.SearchDataItems.
"dataItemViews": [ # The DataItemViews read.
{ # A container for a single DataItem and Annotations on it.
"annotations": [ # The Annotations on the DataItem. If too many Annotations should be returned for the DataItem, this field will be truncated per annotations_limit in request. If it was, then the has_truncated_annotations will be set to true.
{ # Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem.
"annotationSource": { # References an API call. It contains more information about long running operation and Jobs that are triggered by the API call. # Output only. The source of the Annotation.
"dataLabelingJob": "A String", # For API calls that start a LabelingJob. Resource name of the LabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`
"method": "A String", # The method name of the API RPC call. For example, "/google.cloud.aiplatform.{apiVersion}.DatasetService.CreateDataset"
"operation": "A String", # For API calls that return a long running operation. Resource name of the long running operation. Format: `projects/{project}/locations/{location}/operations/{operation}`
},
"createTime": "A String", # Output only. Timestamp when this Annotation was created.
"etag": "A String", # Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # Optional. The labels with user-defined metadata to organize your Annotations. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Annotation(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Annotation: * "aiplatform.googleapis.com/annotation_set_name": optional, name of the UI's annotation set this Annotation belongs to. If not set, the Annotation is not visible in the UI. * "aiplatform.googleapis.com/payload_schema": output only, its value is the payload_schema's title.
"a_key": "A String",
},
"name": "A String", # Output only. Resource name of the Annotation.
"payload": "", # Required. The schema of the payload can be found in payload_schema.
"payloadSchemaUri": "A String", # Required. Google Cloud Storage URI points to a YAML file describing payload. The schema is defined as an [OpenAPI 3.0.2 Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/, note that the chosen schema must be consistent with the parent Dataset's metadata.
"updateTime": "A String", # Output only. Timestamp when this Annotation was last updated.
},
],
"dataItem": { # A piece of data in a Dataset. Could be an image, a video, a document or plain text. # The DataItem.
"createTime": "A String", # Output only. Timestamp when this DataItem was created.
"etag": "A String", # Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # Optional. The labels with user-defined metadata to organize your DataItems. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one DataItem(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of the DataItem.
"payload": "", # Required. The data that the DataItem represents (for example, an image or a text snippet). The schema of the payload is stored in the parent Dataset's metadata schema's dataItemSchemaUri field.
"satisfiesPzi": True or False, # Output only. Reserved for future use.
"satisfiesPzs": True or False, # Output only. Reserved for future use.
"updateTime": "A String", # Output only. Timestamp when this DataItem was last updated.
},
"hasTruncatedAnnotations": True or False, # True if and only if the Annotations field has been truncated. It happens if more Annotations for this DataItem met the request's annotation_filter than are allowed to be returned by annotations_limit. Note that if Annotations field is not being returned due to field mask, then this field will not be set to true no matter how many Annotations are there.
},
],
"nextPageToken": "A String", # A token to retrieve next page of results. Pass to SearchDataItemsRequest.page_token to obtain that page.
}

searchDataItems_next()

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.

Vertex AI API . projects . locations . datasets

Instance Methods

Method Details