DAG: SierraGorda_ParametersStorage Functions that calculate parameters like fragmentation in SierraGorda

schedule: 45,45 12,0 * * *

Task Instance: fragmentation_AddFragmentation

Task Instance Details

Dependencies Blocking Task From Getting Scheduled
Dependency Reason
Dagrun Running Task instance's dagrun was not in the 'running' state but in the state 'failed'.
Task Instance State Task is in the 'success' state which is not a valid state for execution. The task must be cleared in order to be run.
Attribute: python_callable
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def cruce_con_fragmentacion(origin_wenco_file_container, origin_split_contianer, origin_split_blob,  origin_wenco_file_blob, final_container, final_blob):

    conn_origin_container_wenco = BlobClient.from_connection_string(conn_str=BLOB_CONNECT_STRING, container_name=origin_wenco_file_container, blob_name=origin_wenco_file_blob)
    download_stream_wenco = conn_origin_container_wenco.download_blob()
    df_wenco = pd.read_json(download_stream_wenco, orient='table')

    # Archivo Split
    conn_origin_container_split = BlobClient.from_connection_string(conn_str=BLOB_CONNECT_STRING, container_name=origin_split_contianer, blob_name=origin_split_blob)
    download_stream_split = conn_origin_container_split.download_blob().readall()
    data_split = json.loads(download_stream_split)
    df_split = pd.DataFrame(data_split['values'], columns=data_split['headers'])

    # Preparando los datos 
    df_split['fecha'] = df_split['TSP'].astype('datetime64[ns]')
    df_split['fecha'] = df_split['fecha'].dt.date

    df_split['P10'] = df_split['P10'].astype(float)
    df_split['P20'] = df_split['P20'].astype(float)
    df_split['P30'] = df_split['P30'].astype(float)
    df_split['P40'] = df_split['P40'].astype(float)
    df_split['P50'] = df_split['P50'].astype(float)
    df_split['P60'] = df_split['P60'].astype(float)
    df_split['P70'] = df_split['P70'].astype(float)
    df_split['P80'] = df_split['P80'].astype(float)
    df_split['P90'] = df_split['P90'].astype(float)
    
    ### Calculando las metricas
    df_split_mean = (df_split.groupby(['Pala', 'Hora', 'fecha'], as_index=False)         
        .agg(P10_mean = pd.NamedAgg(column="P10", aggfunc="mean"),
                P20_mean = pd.NamedAgg(column="P20", aggfunc="mean"),
                P30_mean = pd.NamedAgg(column="P30", aggfunc="mean"),
                P40_mean = pd.NamedAgg(column="P40", aggfunc="mean"),
                P50_mean = pd.NamedAgg(column="P50", aggfunc="mean"),
                P60_mean = pd.NamedAgg(column="P60", aggfunc="mean"),
                P70_mean = pd.NamedAgg(column="P70", aggfunc="mean"),
                P80_mean = pd.NamedAgg(column="P80", aggfunc="mean"),
                 P90_mean = pd.NamedAgg(column="P90", aggfunc="mean"),)       
        ) 

    df_wenco = df_wenco.drop_duplicates()

    df_split_mean['Pala'] = df_split_mean['Pala'].astype(int)
    df_wenco['LOADING_UNIT_IDENT'] = df_wenco['LOADING_UNIT_IDENT'].astype(int)

    df_wenco['fecha'] = df_wenco['fecha'].astype('datetime64[ns]')
    df_split_mean['fecha'] = df_split_mean['fecha'].astype('datetime64[ns]')

    df_join = df_wenco.merge(df_split_mean, how='left', left_on=['fecha', 'hora', 'LOADING_UNIT_IDENT'], right_on=['fecha', 'Hora', 'Pala'], indicator=True)
    df_join = df_join.drop(columns=['_merge'])

    # Configuracion para subir al blob
    blob = BlobClient.from_connection_string(conn_str=BLOB_CONNECT_STRING, container_name=final_container, blob_name=final_blob)
    ## Subir la data 
    json_data = df_join.to_json(index=False, orient='table')
    blob.upload_blob(json_data, overwrite=True)
Task Instance Attributes
Attribute Value
dag_id SierraGorda_ParametersStorage
duration 1.692275
end_date 2025-12-23 12:48:40.643344+00:00
execution_date 2025-12-23T00:45:00+00:00
executor_config {}
generate_command <function TaskInstance.generate_command at 0x7783d3ac3040>
hostname 447b87b210b3
is_premature False
job_id 8922
key ('SierraGorda_ParametersStorage', 'fragmentation_AddFragmentation', <Pendulum [2025-12-23T00:45:00+00:00]>, 2)
log <Logger airflow.task (INFO)>
log_filepath /usr/local/airflow/logs/SierraGorda_ParametersStorage/fragmentation_AddFragmentation/2025-12-23T00:45:00+00:00.log
log_url http://localhost:8080/admin/airflow/log?execution_date=2025-12-23T00%3A45%3A00%2B00%3A00&task_id=fragmentation_AddFragmentation&dag_id=SierraGorda_ParametersStorage
logger <Logger airflow.task (INFO)>
mark_success_url http://localhost:8080/success?task_id=fragmentation_AddFragmentation&dag_id=SierraGorda_ParametersStorage&execution_date=2025-12-23T00%3A45%3A00%2B00%3A00&upstream=false&downstream=false
max_tries 0
metadata MetaData(bind=None)
next_try_number 2
operator PythonOperator
pid 1897494
pool default_pool
prev_attempted_tries 1
previous_execution_date_success 2025-12-22 12:45:00+00:00
previous_start_date_success 2025-12-23 00:49:05.458912+00:00
previous_ti <TaskInstance: SierraGorda_ParametersStorage.fragmentation_AddFragmentation 2025-12-22 12:45:00+00:00 [success]>
previous_ti_success <TaskInstance: SierraGorda_ParametersStorage.fragmentation_AddFragmentation 2025-12-22 12:45:00+00:00 [success]>
priority_weight 2
queue default
queued_dttm 2025-12-23 12:48:36.806396+00:00
raw False
run_as_user None
start_date 2025-12-23 12:48:38.951069+00:00
state success
task <Task(PythonOperator): fragmentation_AddFragmentation>
task_id fragmentation_AddFragmentation
test_mode False
try_number 2
unixname airflow
Task Attributes
Attribute Value
dag <DAG: SierraGorda_ParametersStorage>
dag_id SierraGorda_ParametersStorage
depends_on_past False
deps {<TIDep(Not In Retry Period)>, <TIDep(Trigger Rule)>, <TIDep(Previous Dagrun State)>}
do_xcom_push True
downstream_list [<Task(PythonOperator): fragmentation_uploadToSQL>]
downstream_task_ids {'fragmentation_uploadToSQL'}
email None
email_on_failure True
email_on_retry True
end_date None
execution_timeout None
executor_config {}
extra_links []
global_operator_extra_link_dict {}
inlets []
lineage_data None
log <Logger airflow.task.operators (INFO)>
logger <Logger airflow.task.operators (INFO)>
max_retry_delay None
on_failure_callback None
on_retry_callback None
on_success_callback None
op_args []
op_kwargs {'origin_wenco_file_container': 'processed', 'origin_split_contianer': 'raw', 'origin_split_blob': 'SierraGorda/2026-01-02/Split.json', 'origin_wenco_file_blob': 'SierraGorda/Fragmentacion/2026-01-02/cruce_wenco_shovel_banco_tasa_excavacion.json', 'final_container': 'processed', 'final_blob': 'SierraGorda/Fragmentacion/2026-01-02/cruce_wenco_shovel_banco_tasa_excavacion_fragmentacion.json'}
operator_extra_link_dict {}
operator_extra_links ()
outlets []
owner pedro
params {}
pool default_pool
priority_weight 1
priority_weight_total 2
provide_context False
queue default
resources None
retries 0
retry_delay 0:05:00
retry_exponential_backoff False
run_as_user None
schedule_interval 45,45 12,0 * * *
shallow_copy_attrs ('python_callable', 'op_kwargs')
sla None
start_date 2023-04-22T00:00:00+00:00
subdag None
task_concurrency None
task_id fragmentation_AddFragmentation
task_type PythonOperator
template_ext []
template_fields ('templates_dict', 'op_args', 'op_kwargs')
templates_dict None
trigger_rule all_success
ui_color #ffefeb
ui_fgcolor #000
upstream_list [<Task(PythonOperator): fragmentation_AddExcavationRate>]
upstream_task_ids {'fragmentation_AddExcavationRate'}
wait_for_downstream False
weight_rule downstream