DAG: SG_Metrics Functions that calculated metrics related to models in Sierra Gorda

schedule: 30 12 * * 1

SG_Metrics

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# Airflow dependencies
from asyncio import Task
from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from airflow.utils.dates import days_ago
from airflow.models import Variable
from airflow.operators.dagrun_operator import TriggerDagRunOperator

# Python dependencies
import sys
import os

from datetime import timedelta
from datetime import datetime 
from datetime import timedelta

# Dependencias propias

from utils.settings import RAW_CONTAINER, METRICS_CONTAINER, YEAR, MONTH, DAY
from utils.metrics import calculate_estimated_bench_metric

# Default arguments
default_args = {
    'owner': 'Pedro',
    'start_date': datetime(2024, 4, 26, 0, 0, 0)
}

# Instanciate the DAG object
sg_metric_dag = DAG( ## Cambiar esto a cammel case.
    'SG_Metrics',
    default_args=default_args,
    description='Functions that calculated metrics related to models in Sierra Gorda',
    schedule_interval= '30 12 * * 1', # Viernes a las 12:30 todas las semanas
    catchup=False,
    is_paused_upon_creation=False
)

"""
    Tareas de cruce entre Perforaciones y Opit
"""
metrics_sg_task1 = PythonOperator(
    task_id = 'Metrics_GenerateScore_BenchEstimation',
    python_callable = calculate_estimated_bench_metric,
    op_kwargs = {"app_points_container": RAW_CONTAINER, 
                 "app_points_blob": f"SierraGorda/dxf/puntos_app_2024_01.json",
                 "mine_opit": "'SG'",
                 "mine_dxf_polygon": "SierraGorda",
                 "classifier_model_path": "utils/models/SG/clasificador.pkl",
                 "final_container": METRICS_CONTAINER,
                 "final_blob": f"SierraGorda/Estimate bench/{YEAR}/{MONTH}/{DAY}/BenchEstimation_v1.json"},
    dag = sg_metric_dag,
)

# Define task secuence 
metrics_sg_task1