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from __future__ import annotations
from datetime import datetime
import boto3
from airflow.decorators import task
from airflow.models.baseoperator import chain
from airflow.models.dag import DAG
from airflow.providers.amazon.aws.operators.s3 import S3CreateBucketOperator, S3DeleteBucketOperator
from airflow.providers.amazon.aws.transfers.dynamodb_to_s3 import DynamoDBToS3Operator
from airflow.utils.trigger_rule import TriggerRule
from tests.system.providers.amazon.aws.utils import ENV_ID_KEY, SystemTestContextBuilder
[docs]DAG_ID = "example_dynamodb_to_s3" 
[docs]sys_test_context_task = SystemTestContextBuilder().build() 
[docs]TABLE_ATTRIBUTES = [
    {"AttributeName": "ID", "AttributeType": "S"},
    {"AttributeName": "Value", "AttributeType": "S"}, 
]
[docs]TABLE_KEY_SCHEMA = [
    {"AttributeName": "ID", "KeyType": "HASH"},
    {"AttributeName": "Value", "KeyType": "RANGE"}, 
]
[docs]TABLE_THROUGHPUT = {"ReadCapacityUnits": 1, "WriteCapacityUnits": 1} 
[docs]S3_KEY_PREFIX = "dynamodb-segmented-file" 
@task
[docs]def set_up_table(table_name: str):
    dynamo_resource = boto3.resource("dynamodb")
    table = dynamo_resource.create_table(
        AttributeDefinitions=TABLE_ATTRIBUTES,
        TableName=table_name,
        KeySchema=TABLE_KEY_SCHEMA,
        ProvisionedThroughput=TABLE_THROUGHPUT,
    )
    boto3.client("dynamodb").get_waiter("table_exists").wait(
        TableName=table_name, WaiterConfig={"Delay": 10, "MaxAttempts": 10}
    )
    table.put_item(Item={"ID": "123", "Value": "Testing"}) 
@task
[docs]def wait_for_bucket(s3_bucket_name):
    waiter = boto3.client("s3").get_waiter("bucket_exists")
    waiter.wait(Bucket=s3_bucket_name) 
@task(trigger_rule=TriggerRule.ALL_DONE)
[docs]def delete_dynamodb_table(table_name: str):
    boto3.resource("dynamodb").Table(table_name).delete()
    boto3.client("dynamodb").get_waiter("table_not_exists").wait(
        TableName=table_name, WaiterConfig={"Delay": 10, "MaxAttempts": 10} 
    )
with DAG(
    dag_id=DAG_ID,
    schedule="@once",
    start_date=datetime(2021, 1, 1),
    catchup=False,
    tags=["example"],
) as dag:
[docs]    test_context = sys_test_context_task() 
    env_id = test_context[ENV_ID_KEY]
    table_name = f"{env_id}-dynamodb-table"
    bucket_name = f"{env_id}-dynamodb-bucket"
    create_table = set_up_table(table_name=table_name)
    create_bucket = S3CreateBucketOperator(task_id="create_bucket", bucket_name=bucket_name)
    # [START howto_transfer_dynamodb_to_s3]
    backup_db = DynamoDBToS3Operator(
        task_id="backup_db",
        dynamodb_table_name=table_name,
        s3_bucket_name=bucket_name,
        # Max output file size in bytes.  If the Table is too large, multiple files will be created.
        file_size=20,
    )
    # [END howto_transfer_dynamodb_to_s3]
    # [START howto_transfer_dynamodb_to_s3_segmented]
    # Segmenting allows the transfer to be parallelized into {segment} number of parallel tasks.
    backup_db_segment_1 = DynamoDBToS3Operator(
        task_id="backup_db_segment_1",
        dynamodb_table_name=table_name,
        s3_bucket_name=bucket_name,
        # Max output file size in bytes.  If the Table is too large, multiple files will be created.
        file_size=1000,
        s3_key_prefix=f"{S3_KEY_PREFIX}-1-",
        dynamodb_scan_kwargs={
            "TotalSegments": 2,
            "Segment": 0,
        },
    )
    backup_db_segment_2 = DynamoDBToS3Operator(
        task_id="backup_db_segment_2",
        dynamodb_table_name=table_name,
        s3_bucket_name=bucket_name,
        # Max output file size in bytes.  If the Table is too large, multiple files will be created.
        file_size=1000,
        s3_key_prefix=f"{S3_KEY_PREFIX}-2-",
        dynamodb_scan_kwargs={
            "TotalSegments": 2,
            "Segment": 1,
        },
    )
    # [END howto_transfer_dynamodb_to_s3_segmented]
    delete_table = delete_dynamodb_table(table_name=table_name)
    delete_bucket = S3DeleteBucketOperator(
        task_id="delete_bucket",
        bucket_name=bucket_name,
        trigger_rule=TriggerRule.ALL_DONE,
        force_delete=True,
    )
    chain(
        # TEST SETUP
        test_context,
        create_table,
        create_bucket,
        wait_for_bucket(s3_bucket_name=bucket_name),
        # TEST BODY
        backup_db,
        backup_db_segment_1,
        backup_db_segment_2,
        # TEST TEARDOWN
        delete_table,
        delete_bucket,
    )
    from tests.system.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.system.utils 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)