Source code for airflow.example_dags.tutorial_taskflow_templates

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# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
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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]

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