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fix ImportError on examples dags (#37571)
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* fix(main): fix ImportError on examples dags

* thanks @eladkal

* @Taragolis thanks for the review, you absoultly right. bad styling, overthinking.

* Fix static check failure

* Update tests/system/README.md

* Update dev/PROJECT_GUIDELINES.md

---------

Co-authored-by: Elad Kalif <45845474+eladkal@users.noreply.github.com>
(cherry picked from commit e0fc803)
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@xionams @ephraimbuddy
xionams authored and ephraimbuddy committed Mar 6, 2024
1 parent 00922c0 commit 7334d20
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217 changes: 110 additions & 107 deletions airflow/example_dags/example_branch_operator.py
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Expand Up @@ -28,140 +28,143 @@

import pendulum

from airflow.models.dag import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.python import (
BranchExternalPythonOperator,
BranchPythonOperator,
BranchPythonVirtualenvOperator,
ExternalPythonOperator,
PythonOperator,
PythonVirtualenvOperator,
)
from airflow.utils.edgemodifier import Label
from airflow.utils.trigger_rule import TriggerRule

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",
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 (
BranchExternalPythonOperator,
BranchPythonOperator,
BranchPythonVirtualenvOperator,
ExternalPythonOperator,
PythonOperator,
PythonVirtualenvOperator,
)
from airflow.utils.edgemodifier import Label
from airflow.utils.trigger_rule import TriggerRule

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
options = ["a", "b", "c", "d"]

# [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,
)
# Example branching on standard Python tasks

for option in options:
t = PythonOperator(
task_id=f"branch_{option}",
python_callable=lambda: print("Hello World"),
# [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

empty_follow = EmptyOperator(
task_id="follow_" + option,
join = EmptyOperator(
task_id="join",
trigger_rule=TriggerRule.NONE_FAILED_MIN_ONE_SUCCESS,
)

# Label is optional here, but it can help identify more complex branches
branching >> Label(option) >> t >> empty_follow >> join
for option in options:
t = PythonOperator(
task_id=f"branch_{option}",
python_callable=lambda: print("Hello World"),
)

# Example the same with external Python calls
empty_follow = EmptyOperator(
task_id="follow_" + option,
)

# [START howto_operator_branch_ext_py]
def branch_with_external_python(choices):
import random
# Label is optional here, but it can help identify more complex branches
branching >> Label(option) >> t >> empty_follow >> join

return f"ext_py_{random.choice(choices)}"
# Example the same with external Python calls

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,
)
# [START howto_operator_branch_ext_py]
def branch_with_external_python(choices):
import random

def hello_world_with_external_python():
print("Hello World from external Python")
return f"ext_py_{random.choice(choices)}"

for option in options:
t = ExternalPythonOperator(
task_id=f"ext_py_{option}",
branching_ext_py = BranchExternalPythonOperator(
task_id="branching_ext_python",
python=PATH_TO_PYTHON_BINARY,
python_callable=hello_world_with_external_python,
python_callable=branch_with_external_python,
op_args=[options],
)
# [END howto_operator_branch_ext_py]
join >> branching_ext_py

# 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
join_ext_py = EmptyOperator(
task_id="join_ext_python",
trigger_rule=TriggerRule.NONE_FAILED_MIN_ONE_SUCCESS,
)

# [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 hello_world_with_external_python():
print("Hello World from external Python")

def branch_with_venv(choices):
import random
for option in options:
t = ExternalPythonOperator(
task_id=f"ext_py_{option}",
python=PATH_TO_PYTHON_BINARY,
python_callable=hello_world_with_external_python,
)

import numpy as np
# Label is optional here, but it can help identify more complex branches
branching_ext_py >> Label(option) >> t >> join_ext_py

print(f"Some numpy stuff: {np.arange(6)}")
return f"venv_{random.choice(choices)}"
# Example the same with Python virtual environments

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
# [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())

join_venv = EmptyOperator(
task_id="join_venv",
trigger_rule=TriggerRule.NONE_FAILED_MIN_ONE_SUCCESS,
)
def branch_with_venv(choices):
import random

def hello_world_with_venv():
import numpy as np
import numpy as np

print(f"Hello World with some numpy stuff: {np.arange(6)}")
print(f"Some numpy stuff: {np.arange(6)}")
return f"venv_{random.choice(choices)}"

for option in options:
t = PythonVirtualenvOperator(
task_id=f"venv_{option}",
branching_venv = BranchPythonVirtualenvOperator(
task_id="branching_venv",
requirements=["numpy~=1.24.4"],
venv_cache_path=VENV_CACHE_PATH,
python_callable=hello_world_with_venv,
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,
)

# Label is optional here, but it can help identify more complex branches
branching_venv >> Label(option) >> t >> join_venv
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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