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2 changes: 1 addition & 1 deletion airflow/example_dags/tutorial.py
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Expand Up @@ -95,7 +95,7 @@
You can document your task using the attributes `doc_md` (markdown),
`doc` (plain text), `doc_rst`, `doc_json`, `doc_yaml` which gets
rendered in the UI's Task Instance Details page.
![img](http://montcs.bloomu.edu/~bobmon/Semesters/2012-01/491/import%20soul.png)
![img](https://imgs.xkcd.com/comics/fixing_problems.png)
**Image Credit:** Randall Munroe, [XKCD](https://xkcd.com/license.html)
"""
)
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8 changes: 8 additions & 0 deletions docs/apache-airflow/core-concepts/dag-run.rst
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Expand Up @@ -252,8 +252,16 @@ Using CLI
Using UI
^^^^^^^^^^

In the UI the parameters to trigger a DAG can be better represented via ``params`` definition as described in
:ref:`concepts:params` documentation. Via defined params a proper form for value entry is rendered.

If the DAG does not define ``params``the form is usually skipped, via the configuration option ``show_trigger_form_if_no_params``
it is possible to force the display the classic form of a dict-only entry to pass configuration options.

.. image:: ../img/example_passing_conf.png

Please consider to convert such usage to ``params`` as this is the more convenient way and allows also validation of user input.

To Keep in Mind
''''''''''''''''
* Marking task instances as failed can be done through the UI. This can be used to stop running task instances.
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10 changes: 5 additions & 5 deletions docs/apache-airflow/tutorial/pipeline.rst
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Expand Up @@ -196,7 +196,7 @@ We've developed our tasks, now we need to wrap them in a DAG, which enables us t
* only run once in the event that days are missed, and
* timeout after 60 minutes

And from the last line in the definition of the ``process-employees`` DAG, we see:
And from the last line in the definition of the ``process_employees`` DAG, we see:

.. code-block:: python

Expand All @@ -221,7 +221,7 @@ Putting all of the pieces together, we have our completed DAG.


@dag(
dag_id="process-employees",
dag_id="process_employees",
schedule_interval="0 0 * * *",
start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
catchup=False,
Expand Down Expand Up @@ -308,15 +308,15 @@ Putting all of the pieces together, we have our completed DAG.

dag = ProcessEmployees()

Save this code to a python file in the ``/dags`` folder (e.g. ``dags/process-employees.py``) and (after a `brief delay <https://airflow.apache.org/docs/apache-airflow/stable/configurations-ref.html#dag-dir-list-interval>`_), the ``process-employees`` DAG will be included in the list of available DAGs on the web UI.
Save this code to a python file in the ``/dags`` folder (e.g. ``dags/process_employees.py``) and (after a `brief delay <https://airflow.apache.org/docs/apache-airflow/stable/configurations-ref.html#dag-dir-list-interval>`_), the ``process_employees`` DAG will be included in the list of available DAGs on the web UI.

.. image:: ../img/tutorial-pipeline-1.png

You can trigger the ``process-employees`` DAG by unpausing it (via the slider on the left end) and running it (via the Run button under **Actions**).
You can trigger the ``process_employees`` DAG by unpausing it (via the slider on the left end) and running it (via the Run button under **Actions**).

.. image:: ../img/tutorial-pipeline-2.png

In the ``process-employees`` DAG's **Grid** view, we see all that all tasks ran successfully in all executed runs. Success!
In the ``process_employees`` DAG's **Grid** view, we see all that all tasks ran successfully in all executed runs. Success!

What's Next?
-------------
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