Amazon Comprehend¶
Amazon Comprehend uses natural language processing (NLP) to extract insights about the content of documents. It develops insights by recognizing the entities, key phrases, language, sentiments, and other common elements in a document.
Prerequisite Tasks¶
To use these operators, you must do a few things:
Create necessary resources using AWS Console or AWS CLI.
Install API libraries via pip.
pip install 'apache-airflow[amazon]'Detailed information is available Installation of Airflow®
Generic Parameters¶
- aws_conn_id
Reference to Amazon Web Services Connection ID. If this parameter is set to
None
then the default boto3 behaviour is used without a connection lookup. Otherwise use the credentials stored in the Connection. Default:aws_default
- region_name
AWS Region Name. If this parameter is set to
None
or omitted then region_name from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default:None
- verify
Whether or not to verify SSL certificates.
False
- Do not validate SSL certificates.path/to/cert/bundle.pem - A filename of the CA cert bundle to use. You can specify this argument if you want to use a different CA cert bundle than the one used by botocore.
If this parameter is set to
None
or is omitted then verify from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default:None
- botocore_config
The provided dictionary is used to construct a botocore.config.Config. This configuration can be used to configure Avoid Throttling exceptions, timeouts, etc.
{ "signature_version": "unsigned", "s3": { "us_east_1_regional_endpoint": True, }, "retries": { "mode": "standard", "max_attempts": 10, }, "connect_timeout": 300, "read_timeout": 300, "tcp_keepalive": True, }
If this parameter is set to
None
or omitted then config_kwargs from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default:None
Note
Specifying an empty dictionary,
{}
, will overwrite the connection configuration for botocore.config.Config
Operators¶
Create an Amazon Comprehend Start PII Entities Detection Job¶
To create an Amazon Comprehend Start PII Entities Detection Job, you can use
ComprehendStartPiiEntitiesDetectionJobOperator
.
tests/system/amazon/aws/example_comprehend.py
start_pii_entities_detection_job = ComprehendStartPiiEntitiesDetectionJobOperator(
task_id="start_pii_entities_detection_job",
input_data_config=input_data_configurations,
output_data_config=output_data_configurations,
mode="ONLY_REDACTION",
data_access_role_arn=test_context[ROLE_ARN_KEY],
language_code="en",
start_pii_entities_kwargs=pii_entities_kwargs,
)
Create an Amazon Comprehend Document Classifier¶
To create an Amazon Comprehend Document Classifier, you can use
ComprehendCreateDocumentClassifierOperator
.
tests/system/amazon/aws/example_comprehend_document_classifier.py
create_document_classifier = ComprehendCreateDocumentClassifierOperator(
task_id="create_document_classifier",
document_classifier_name=classifier_name,
input_data_config=input_data_configurations,
output_data_config=output_data_configurations,
mode="MULTI_CLASS",
data_access_role_arn=test_context[ROLE_ARN_KEY],
language_code="en",
document_classifier_kwargs=document_classifier_kwargs,
)
Sensors¶
Wait for an Amazon Comprehend Start PII Entities Detection Job¶
To wait on the state of an Amazon Comprehend Start PII Entities Detection Job until it reaches a terminal
state you can use
ComprehendStartPiiEntitiesDetectionJobCompletedSensor
.
tests/system/amazon/aws/example_comprehend.py
await_start_pii_entities_detection_job = ComprehendStartPiiEntitiesDetectionJobCompletedSensor(
task_id="await_start_pii_entities_detection_job", job_id=start_pii_entities_detection_job.output
)
Wait for an Amazon Comprehend Document Classifier¶
To wait on the state of an Amazon Comprehend Document Classifier until it reaches a terminal
state you can use
ComprehendCreateDocumentClassifierCompletedSensor
.
tests/system/amazon/aws/example_comprehend_document_classifier.py
await_create_document_classifier = ComprehendCreateDocumentClassifierCompletedSensor(
task_id="await_create_document_classifier", document_classifier_arn=create_document_classifier.output
)