Source code for airflow.example_dags.tutorial_taskflow_templates
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from __future__ import annotations
# [START tutorial]
# [START import_module]
import pendulum
from airflow.decorators import dag, task
from airflow.operators.python import get_current_context
# [END import_module]
# [START instantiate_dag]
@dag(
schedule="@daily",
start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
catchup=False,
tags=["example"],
params={"foobar": "param_from_dag", "other_param": "from_dag"},
)
[docs]def tutorial_taskflow_templates():
"""
### TaskFlow API Tutorial Documentation
This is a simple data pipeline example which demonstrates the use of
the templates in the TaskFlow API.
Documentation that goes along with the Airflow TaskFlow API tutorial is
located
[here](https://airflow.apache.org/docs/apache-airflow/stable/tutorial_taskflow_api.html)
"""
# [END instantiate_dag]
# [START template_test]
@task(
# Causes variables that end with `.sql` to be read and templates
# within to be rendered.
templates_exts=[".sql"],
)
def template_test(sql, test_var, data_interval_end):
context = get_current_context()
# Will print...
# select * from test_data
# where 1=1
# and run_id = 'scheduled__2024-10-09T00:00:00+00:00'
# and something_else = 'param_from_task'
print(f"sql: {sql}")
# Will print `scheduled__2024-10-09T00:00:00+00:00`
print(f"test_var: {test_var}")
# Will print `2024-10-10 00:00:00+00:00`.
# Note how we didn't pass this value when calling the task. Instead
# it was passed by the decorator from the context
print(f"data_interval_end: {data_interval_end}")
# Will print...
# run_id: scheduled__2024-10-09T00:00:00+00:00; params.other_param: from_dag
template_str = "run_id: {{ run_id }}; params.other_param: {{ params.other_param }}"
rendered_template = context["task"].render_template(
template_str,
context,
)
print(f"rendered template: {rendered_template}")
# Will print the full context dict
print(f"context: {context}")
# [END template_test]
# [START main_flow]
template_test.override(
# Will be merged with the dict defined in the dag
# and override existing parameters.
#
# Must be passed into the decorator's parameters
# through `.override()` not into the actual task
# function
params={"foobar": "param_from_task"},
)(
sql="sql/test.sql",
test_var="{{ run_id }}",
)
# [END main_flow]
# [START dag_invocation]
tutorial_taskflow_templates()
# [END dag_invocation]
# [END tutorial]