Source code for airflow.example_dags.example_branch_operator

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"""Example DAG demonstrating the usage of the Classic branching Python operators.

It is showcasing the basic BranchPythonOperator and its sisters BranchExternalPythonOperator
and BranchPythonVirtualenvOperator."""

from __future__ import annotations

import random
import sys
import tempfile
from pathlib import Path

import pendulum

from airflow.operators.python import is_venv_installed

if is_venv_installed():
    from airflow.models.dag import DAG
    from airflow.operators.empty import EmptyOperator
    from airflow.operators.python import (
    from airflow.utils.edgemodifier import Label
    from airflow.utils.trigger_rule import TriggerRule

[docs] PATH_TO_PYTHON_BINARY = sys.executable
with DAG( dag_id="example_branch_operator", start_date=pendulum.datetime(2021, 1, 1, tz="UTC"), catchup=False, schedule="@daily", tags=["example", "example2"], orientation="TB", ) as dag: run_this_first = EmptyOperator( task_id="run_this_first", ) options = ["a", "b", "c", "d"] # Example branching on standard Python tasks # [START howto_operator_branch_python] branching = BranchPythonOperator( task_id="branching", python_callable=lambda: f"branch_{random.choice(options)}", ) # [END howto_operator_branch_python] run_this_first >> branching join = EmptyOperator( task_id="join", trigger_rule=TriggerRule.NONE_FAILED_MIN_ONE_SUCCESS, ) for option in options: t = PythonOperator( task_id=f"branch_{option}", python_callable=lambda: print("Hello World"), ) empty_follow = EmptyOperator( task_id="follow_" + option, ) # Label is optional here, but it can help identify more complex branches branching >> Label(option) >> t >> empty_follow >> join # Example the same with external Python calls # [START howto_operator_branch_ext_py] def branch_with_external_python(choices): import random return f"ext_py_{random.choice(choices)}" branching_ext_py = BranchExternalPythonOperator( task_id="branching_ext_python", python=PATH_TO_PYTHON_BINARY, python_callable=branch_with_external_python, op_args=[options], ) # [END howto_operator_branch_ext_py] join >> branching_ext_py join_ext_py = EmptyOperator( task_id="join_ext_python", trigger_rule=TriggerRule.NONE_FAILED_MIN_ONE_SUCCESS, ) def hello_world_with_external_python(): print("Hello World from external Python") for option in options: t = ExternalPythonOperator( task_id=f"ext_py_{option}", python=PATH_TO_PYTHON_BINARY, python_callable=hello_world_with_external_python, ) # Label is optional here, but it can help identify more complex branches branching_ext_py >> Label(option) >> t >> join_ext_py # Example the same with Python virtual environments # [START howto_operator_branch_virtualenv] # Note: Passing a caching dir allows to keep the virtual environment over multiple runs # Run the example a second time and see that it re-uses it and is faster. VENV_CACHE_PATH = Path(tempfile.gettempdir()) def branch_with_venv(choices): import random import numpy as np print(f"Some numpy stuff: {np.arange(6)}") return f"venv_{random.choice(choices)}" branching_venv = BranchPythonVirtualenvOperator( task_id="branching_venv", requirements=["numpy~=1.24.4"], venv_cache_path=VENV_CACHE_PATH, python_callable=branch_with_venv, op_args=[options], ) # [END howto_operator_branch_virtualenv] join_ext_py >> branching_venv join_venv = EmptyOperator( task_id="join_venv", trigger_rule=TriggerRule.NONE_FAILED_MIN_ONE_SUCCESS, ) def hello_world_with_venv(): import numpy as np print(f"Hello World with some numpy stuff: {np.arange(6)}") for option in options: t = PythonVirtualenvOperator( task_id=f"venv_{option}", requirements=["numpy~=1.24.4"], venv_cache_path=VENV_CACHE_PATH, python_callable=hello_world_with_venv, ) # Label is optional here, but it can help identify more complex branches branching_venv >> Label(option) >> t >> join_venv

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