| :py:mod:`airflow.providers.google.cloud.operators.automl` |
| ========================================================= |
| |
| .. py:module:: airflow.providers.google.cloud.operators.automl |
| |
| .. autoapi-nested-parse:: |
| |
| This module contains Google AutoML operators. |
| |
| |
| |
| Module Contents |
| --------------- |
| |
| Classes |
| ~~~~~~~ |
| |
| .. autoapisummary:: |
| |
| airflow.providers.google.cloud.operators.automl.AutoMLTrainModelOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLPredictOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLBatchPredictOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLCreateDatasetOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLImportDataOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLTablesListColumnSpecsOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLTablesUpdateDatasetOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLGetModelOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLDeleteModelOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLDeployModelOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLTablesListTableSpecsOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLListDatasetOperator |
| airflow.providers.google.cloud.operators.automl.AutoMLDeleteDatasetOperator |
| |
| |
| |
| |
| Attributes |
| ~~~~~~~~~~ |
| |
| .. autoapisummary:: |
| |
| airflow.providers.google.cloud.operators.automl.MetaData |
| |
| |
| .. py:data:: MetaData |
| |
| |
| |
| |
| .. py:class:: AutoMLTrainModelOperator(*, model, location, project_id = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Creates Google Cloud AutoML model. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLTrainModelOperator` |
| |
| :param model: Model definition. |
| :param project_id: ID of the Google Cloud project where model will be created if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['model', 'location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLPredictOperator(*, model_id, location, payload, operation_params = None, project_id = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Runs prediction operation on Google Cloud AutoML. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLPredictOperator` |
| |
| :param model_id: Name of the model requested to serve the batch prediction. |
| :param payload: Name od the model used for the prediction. |
| :param project_id: ID of the Google Cloud project where model is located if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param operation_params: Additional domain-specific parameters for the predictions. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['model_id', 'location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLBatchPredictOperator(*, model_id, input_config, output_config, location, project_id = None, prediction_params = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Perform a batch prediction on Google Cloud AutoML. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLBatchPredictOperator` |
| |
| :param project_id: ID of the Google Cloud project where model will be created if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param model_id: Name of the model_id requested to serve the batch prediction. |
| :param input_config: Required. The input configuration for batch prediction. |
| If a dict is provided, it must be of the same form as the protobuf message |
| `google.cloud.automl_v1beta1.types.BatchPredictInputConfig` |
| :param output_config: Required. The Configuration specifying where output predictions should be |
| written. If a dict is provided, it must be of the same form as the protobuf message |
| `google.cloud.automl_v1beta1.types.BatchPredictOutputConfig` |
| :param prediction_params: Additional domain-specific parameters for the predictions, |
| any string must be up to 25000 characters long. |
| :param project_id: ID of the Google Cloud project where model is located if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['model_id', 'input_config', 'output_config', 'location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLCreateDatasetOperator(*, dataset, location, project_id = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Creates a Google Cloud AutoML dataset. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLCreateDatasetOperator` |
| |
| :param dataset: The dataset to create. If a dict is provided, it must be of the |
| same form as the protobuf message Dataset. |
| :param project_id: ID of the Google Cloud project where dataset is located if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param params: Additional domain-specific parameters for the predictions. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['dataset', 'location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLImportDataOperator(*, dataset_id, location, input_config, project_id = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Imports data to a Google Cloud AutoML dataset. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLImportDataOperator` |
| |
| :param dataset_id: ID of dataset to be updated. |
| :param input_config: The desired input location and its domain specific semantics, if any. |
| If a dict is provided, it must be of the same form as the protobuf message InputConfig. |
| :param project_id: ID of the Google Cloud project where dataset is located if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param params: Additional domain-specific parameters for the predictions. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['dataset_id', 'input_config', 'location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLTablesListColumnSpecsOperator(*, dataset_id, table_spec_id, location, field_mask = None, filter_ = None, page_size = None, project_id = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Lists column specs in a table. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLTablesListColumnSpecsOperator` |
| |
| :param dataset_id: Name of the dataset. |
| :param table_spec_id: table_spec_id for path builder. |
| :param field_mask: Mask specifying which fields to read. If a dict is provided, it must be of the same |
| form as the protobuf message `google.cloud.automl_v1beta1.types.FieldMask` |
| :param filter_: Filter expression, see go/filtering. |
| :param page_size: The maximum number of resources contained in the |
| underlying API response. If page streaming is performed per |
| resource, this parameter does not affect the return value. If page |
| streaming is performed per page, this determines the maximum number |
| of resources in a page. |
| :param project_id: ID of the Google Cloud project where dataset is located if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['dataset_id', 'table_spec_id', 'field_mask', 'filter_', 'location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLTablesUpdateDatasetOperator(*, dataset, location, update_mask = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Updates a dataset. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLTablesUpdateDatasetOperator` |
| |
| :param dataset: The dataset which replaces the resource on the server. |
| If a dict is provided, it must be of the same form as the protobuf message Dataset. |
| :param update_mask: The update mask applies to the resource. If a dict is provided, it must |
| be of the same form as the protobuf message FieldMask. |
| :param location: The location of the project. |
| :param params: Additional domain-specific parameters for the predictions. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['dataset', 'update_mask', 'location', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLGetModelOperator(*, model_id, location, project_id = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Get Google Cloud AutoML model. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLGetModelOperator` |
| |
| :param model_id: Name of the model requested to serve the prediction. |
| :param project_id: ID of the Google Cloud project where model is located if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param params: Additional domain-specific parameters for the predictions. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['model_id', 'location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLDeleteModelOperator(*, model_id, location, project_id = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Delete Google Cloud AutoML model. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLDeleteModelOperator` |
| |
| :param model_id: Name of the model requested to serve the prediction. |
| :param project_id: ID of the Google Cloud project where model is located if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param params: Additional domain-specific parameters for the predictions. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['model_id', 'location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLDeployModelOperator(*, model_id, location, project_id = None, image_detection_metadata = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Deploys a model. If a model is already deployed, deploying it with the same parameters |
| has no effect. Deploying with different parameters (as e.g. changing node_number) will |
| reset the deployment state without pausing the model_id’s availability. |
| |
| Only applicable for Text Classification, Image Object Detection and Tables; all other |
| domains manage deployment automatically. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLDeployModelOperator` |
| |
| :param model_id: Name of the model to be deployed. |
| :param image_detection_metadata: Model deployment metadata specific to Image Object Detection. |
| If a dict is provided, it must be of the same form as the protobuf message |
| ImageObjectDetectionModelDeploymentMetadata |
| :param project_id: ID of the Google Cloud project where model is located if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param params: Additional domain-specific parameters for the predictions. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['model_id', 'location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLTablesListTableSpecsOperator(*, dataset_id, location, page_size = None, filter_ = None, project_id = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Lists table specs in a dataset. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLTablesListTableSpecsOperator` |
| |
| :param dataset_id: Name of the dataset. |
| :param filter_: Filter expression, see go/filtering. |
| :param page_size: The maximum number of resources contained in the |
| underlying API response. If page streaming is performed per |
| resource, this parameter does not affect the return value. If page |
| streaming is performed per-page, this determines the maximum number |
| of resources in a page. |
| :param project_id: ID of the Google Cloud project if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['dataset_id', 'filter_', 'location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLListDatasetOperator(*, location, project_id = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Lists AutoML Datasets in project. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLListDatasetOperator` |
| |
| :param project_id: ID of the Google Cloud project where datasets are located if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
| .. py:class:: AutoMLDeleteDatasetOperator(*, dataset_id, location, project_id = None, metadata = (), timeout = None, retry = DEFAULT, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs) |
| |
| Bases: :py:obj:`airflow.models.BaseOperator` |
| |
| Deletes a dataset and all of its contents. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:AutoMLDeleteDatasetOperator` |
| |
| :param dataset_id: Name of the dataset_id, list of dataset_id or string of dataset_id |
| coma separated to be deleted. |
| :param project_id: ID of the Google Cloud project where dataset is located if None then |
| default project_id is used. |
| :param location: The location of the project. |
| :param retry: A retry object used to retry requests. If `None` is specified, requests will not be |
| retried. |
| :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if |
| `retry` is specified, the timeout applies to each individual attempt. |
| :param metadata: Additional metadata that is provided to the method. |
| :param gcp_conn_id: The connection ID to use to connect to Google Cloud. |
| :param impersonation_chain: Optional service account to impersonate using short-term |
| credentials, or chained list of accounts required to get the access_token |
| of the last account in the list, which will be impersonated in the request. |
| If set as a string, the account must grant the originating account |
| the Service Account Token Creator IAM role. |
| If set as a sequence, the identities from the list must grant |
| Service Account Token Creator IAM role to the directly preceding identity, with first |
| account from the list granting this role to the originating account (templated). |
| |
| .. py:attribute:: template_fields |
| :annotation: :Sequence[str] = ['dataset_id', 'location', 'project_id', 'impersonation_chain'] |
| |
| |
| |
| .. py:method:: execute(self, context) |
| |
| This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates. |
| |
| Refer to get_template_context for more context. |
| |
| |
| |
