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#
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#
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from __future__ import annotations
from datetime import datetime
from airflow import DAG
from airflow.decorators import task, task_group
from airflow.models.baseoperator import chain
from airflow.providers.amazon.aws.hooks.comprehend import ComprehendHook
from airflow.providers.amazon.aws.operators.comprehend import (
ComprehendCreateDocumentClassifierOperator,
)
from airflow.providers.amazon.aws.operators.s3 import (
S3CopyObjectOperator,
S3CreateBucketOperator,
S3CreateObjectOperator,
S3DeleteBucketOperator,
)
from airflow.providers.amazon.aws.sensors.comprehend import (
ComprehendCreateDocumentClassifierCompletedSensor,
)
from airflow.utils.trigger_rule import TriggerRule
from providers.tests.system.amazon.aws.utils import SystemTestContextBuilder
[docs]ROLE_ARN_KEY = "ROLE_ARN"
[docs]BUCKET_NAME_KEY = "BUCKET_NAME"
[docs]BUCKET_KEY_DISCHARGE_KEY = "BUCKET_KEY_DISCHARGE"
[docs]BUCKET_KEY_DOCTORS_NOTES = "BUCKET_KEY_DOCTORS_NOTES"
[docs]sys_test_context_task = (
SystemTestContextBuilder()
.add_variable(ROLE_ARN_KEY)
.add_variable(BUCKET_NAME_KEY)
.add_variable(BUCKET_KEY_DISCHARGE_KEY)
.add_variable(BUCKET_KEY_DOCTORS_NOTES)
.build()
)
[docs]DAG_ID = "example_comprehend_document_classifier"
[docs]ANNOTATION_BUCKET_KEY = "training-labels/label.csv"
[docs]TRAINING_DATA_PREFIX = "training-docs"
# Annotations file won't allow headers
# label,document name,page number
[docs]ANNOTATIONS = """DISCHARGE_SUMMARY,discharge-summary-0.pdf,1
DISCHARGE_SUMMARY,discharge-summary-1.pdf,1
DISCHARGE_SUMMARY,discharge-summary-2.pdf,1
DISCHARGE_SUMMARY,discharge-summary-3.pdf,1
DISCHARGE_SUMMARY,discharge-summary-4.pdf,1
DISCHARGE_SUMMARY,discharge-summary-5.pdf,1
DISCHARGE_SUMMARY,discharge-summary-6.pdf,1
DISCHARGE_SUMMARY,discharge-summary-7.pdf,1
DISCHARGE_SUMMARY,discharge-summary-8.pdf,1
DISCHARGE_SUMMARY,discharge-summary-9.pdf,1
DOCTOR_NOTES,doctors-notes-0.pdf,1
DOCTOR_NOTES,doctors-notes-1.pdf,1
DOCTOR_NOTES,doctors-notes-2.pdf,1
DOCTOR_NOTES,doctors-notes-3.pdf,1
DOCTOR_NOTES,doctors-notes-4.pdf,1
DOCTOR_NOTES,doctors-notes-5.pdf,1
DOCTOR_NOTES,doctors-notes-6.pdf,1
DOCTOR_NOTES,doctors-notes-7.pdf,1
DOCTOR_NOTES,doctors-notes-8.pdf,1
DOCTOR_NOTES,doctors-notes-9.pdf,1"""
@task_group
[docs]def document_classifier_workflow():
# [START howto_operator_create_document_classifier]
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,
)
# [END howto_operator_create_document_classifier]
create_document_classifier.wait_for_completion = False
# [START howto_sensor_create_document_classifier]
await_create_document_classifier = ComprehendCreateDocumentClassifierCompletedSensor(
task_id="await_create_document_classifier", document_classifier_arn=create_document_classifier.output
)
# [END howto_sensor_create_document_classifier]
@task(trigger_rule=TriggerRule.ALL_DONE)
def delete_classifier(document_classifier_arn: str):
ComprehendHook().conn.delete_document_classifier(DocumentClassifierArn=document_classifier_arn)
chain(
create_document_classifier,
await_create_document_classifier,
delete_classifier(create_document_classifier.output),
)
@task
[docs]def create_kwargs_discharge():
return [
{
"source_bucket_key": str(test_context[BUCKET_KEY_DISCHARGE_KEY]),
"dest_bucket_key": f"{TRAINING_DATA_PREFIX}/discharge-summary-{counter}.pdf",
}
for counter in range(10)
]
@task
[docs]def create_kwargs_doctors_notes():
return [
{
"source_bucket_key": str(test_context[BUCKET_KEY_DOCTORS_NOTES]),
"dest_bucket_key": f"{TRAINING_DATA_PREFIX}/doctors-notes-{counter}.pdf",
}
for counter in range(10)
]
with DAG(
dag_id=DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
tags=["example"],
catchup=False,
) as dag:
[docs] test_context = sys_test_context_task()
env_id = test_context["ENV_ID"]
classifier_name = f"{env_id}-custom-document-classifier"
bucket_name = f"{env_id}-comprehend-document-classifier"
input_data_configurations = {
"S3Uri": f"s3://{bucket_name}/{ANNOTATION_BUCKET_KEY}",
"DataFormat": "COMPREHEND_CSV",
"DocumentType": "SEMI_STRUCTURED_DOCUMENT",
"Documents": {"S3Uri": f"s3://{bucket_name}/{TRAINING_DATA_PREFIX}/"},
"DocumentReaderConfig": {
"DocumentReadAction": "TEXTRACT_DETECT_DOCUMENT_TEXT",
"DocumentReadMode": "SERVICE_DEFAULT",
},
}
output_data_configurations = {"S3Uri": f"s3://{bucket_name}/output/"}
document_classifier_kwargs = {"VersionName": "v1"}
create_bucket = S3CreateBucketOperator(
task_id="create_bucket",
bucket_name=bucket_name,
)
discharge_kwargs = create_kwargs_discharge()
s3_copy_discharge_task = S3CopyObjectOperator.partial(
task_id="s3_copy_discharge_task",
source_bucket_name=test_context[BUCKET_NAME_KEY],
dest_bucket_name=bucket_name,
meta_data_directive="REPLACE",
).expand_kwargs(discharge_kwargs)
doctors_notes_kwargs = create_kwargs_doctors_notes()
s3_copy_doctors_notes_task = S3CopyObjectOperator.partial(
task_id="s3_copy_doctors_notes_task",
source_bucket_name=test_context[BUCKET_NAME_KEY],
dest_bucket_name=bucket_name,
meta_data_directive="REPLACE",
).expand_kwargs(doctors_notes_kwargs)
upload_annotation_file = S3CreateObjectOperator(
task_id="upload_annotation_file",
s3_bucket=bucket_name,
s3_key=ANNOTATION_BUCKET_KEY,
data=ANNOTATIONS.encode("utf-8"),
)
delete_bucket = S3DeleteBucketOperator(
task_id="delete_bucket",
trigger_rule=TriggerRule.ALL_DONE,
bucket_name=bucket_name,
force_delete=True,
)
chain(
test_context,
create_bucket,
s3_copy_discharge_task,
s3_copy_doctors_notes_task,
upload_annotation_file,
# TEST BODY
document_classifier_workflow(),
# TEST TEARDOWN
delete_bucket,
)
from tests_common.test_utils.watcher import watcher
# This test needs watcher in order to properly mark success/failure
# when "tearDown" task with trigger rule is part of the DAG
list(dag.tasks) >> watcher()
from tests_common.test_utils.system_tests import get_test_run # noqa: E402
# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)