# Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# --------------------------------------------------------------------------------
# Load The Dependencies
# --------------------------------------------------------------------------------

import datetime

from airflow import models
from airflow.models.variable import Variable
from airflow.operators import empty
from airflow.providers.google.cloud.operators.dataflow import DataflowTemplatedJobStartOperator

# --------------------------------------------------------------------------------
# Set variables - Needed for the DEMO
# --------------------------------------------------------------------------------
BQ_LOCATION = Variable.get("BQ_LOCATION")
CURATED_PRJ = Variable.get("CURATED_PRJ")
CURATED_BQ_DATASET = Variable.get("CURATED_BQ_DATASET")
CURATED_GCS = Variable.get("CURATED_GCS")
LAND_PRJ = Variable.get("LAND_PRJ")
LAND_GCS = Variable.get("LAND_GCS")
PROCESSING_GCS = Variable.get("PROCESSING_GCS")
PROCESSING_SA = Variable.get("PROCESSING_SA")
PROCESSING_PRJ = Variable.get("PROCESSING_PRJ")
PROCESSING_SUBNET = Variable.get("PROCESSING_SUBNET")
PROCESSING_VPC = Variable.get("PROCESSING_VPC")
DP_KMS_KEY = Variable.get("DP_KMS_KEY", "")
DP_REGION = Variable.get("DP_REGION")
DP_ZONE = Variable.get("DP_REGION") + "-b"

# --------------------------------------------------------------------------------
# Set default arguments
# --------------------------------------------------------------------------------

# If you are running Airflow in more than one time zone
# see https://airflow.apache.org/docs/apache-airflow/stable/timezone.html
# for best practices
yesterday = datetime.datetime.now() - datetime.timedelta(days=1)

default_args = {
  'owner': 'airflow',
  'start_date': yesterday,
  'depends_on_past': False,
  'email': [''],
  'email_on_failure': False,
  'email_on_retry': False,
  'retries': 1,
  'retry_delay': datetime.timedelta(minutes=5),
  'dataflow_default_options': {
    'location': DP_REGION,
    'zone': DP_ZONE,
    'stagingLocation': PROCESSING_GCS + "/staging",
    'tempLocation': PROCESSING_GCS + "/tmp",
    'serviceAccountEmail': PROCESSING_SA,
    'subnetwork': PROCESSING_SUBNET,
    'ipConfiguration': "WORKER_IP_PRIVATE",
    'kmsKeyName' : DP_KMS_KEY
  },
}

# --------------------------------------------------------------------------------
# Main DAG
# --------------------------------------------------------------------------------

with models.DAG(
    'dataflow_gcs2bq',
    default_args=default_args,
    schedule_interval=None) as dag:
  start = empty.EmptyOperator(
    task_id='start',
    trigger_rule='all_success'
  )

  end = empty.EmptyOperator(
    task_id='end',
    trigger_rule='all_success'
  )

  # Bigquery Tables automatically created for demo porpuse. 
  # Consider a dedicated pipeline or tool for a real life scenario.
  customers_import = DataflowTemplatedJobStartOperator(
    task_id="dataflow_customers_import",
    template="gs://dataflow-templates/latest/GCS_Text_to_BigQuery",
    project_id=PROCESSING_PRJ,
    location=DP_REGION,
    parameters={
      "javascriptTextTransformFunctionName": "transform",
      "JSONPath": PROCESSING_GCS + "/customers_schema.json",
      "javascriptTextTransformGcsPath": PROCESSING_GCS + "/customers_udf.js",
      "inputFilePattern": LAND_GCS + "/customers.csv",
      "outputTable": CURATED_PRJ + ":" + CURATED_BQ_DATASET + ".customers",
      "bigQueryLoadingTemporaryDirectory": PROCESSING_GCS + "/tmp/bq/",
    },
  )

  start >> customers_import >> end