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.. contents:: :local:
Setup your project
##################
1. Open your IDE or source code editor and select the option to clone the repository
.. raw:: html
<div align="center" style="padding-bottom:10px">
<img src="images/quick_start/pycharm_clone.png"
alt="Cloning github fork to Pycharm">
</div>
2. Paste the repository link in the URL field and submit.
.. raw:: html
<div align="center" style="padding-bottom:10px">
<img src="images/quick_start/click_on_clone.png"
alt="Cloning github fork to Pycharm">
</div>
Setting up debugging
####################
It requires "airflow-env" virtual environment configured locally.
1. Configuring Airflow database connection
- Airflow is by default configured to use SQLite database. Configuration can be seen on local machine
``~/airflow/airflow.cfg`` under ``sql_alchemy_conn``.
- Installing required dependency for MySQL connection in ``airflow-env`` on local machine.
.. code-block:: bash
$ pyenv activate airflow-env
$ pip install PyMySQL
- Now set ``sql_alchemy_conn = mysql+pymysql://root:@127.0.0.1:23306/airflow?charset=utf8mb4`` in file
``~/airflow/airflow.cfg`` on local machine.
2. Debugging an example DAG
- Add Interpreter to PyCharm pointing interpreter path to ``~/.pyenv/versions/airflow-env/bin/python``, which is virtual
environment ``airflow-env`` created with pyenv earlier. For adding an Interpreter go to ``File -> Setting -> Project:
airflow -> Python Interpreter``.
.. raw:: html
<div align="center" style="padding-bottom:10px">
<img src="images/quick_start/add Interpreter.png"
alt="Adding existing interpreter">
</div>
- In PyCharm IDE open airflow project, directory ``/files/dags`` of local machine is by default mounted to docker
machine when breeze airflow is started. So any DAG file present in this directory will be picked automatically by
scheduler running in docker machine and same can be seen on ``http://127.0.0.1:28080``.
- Copy any example DAG present in the ``/airflow/example_dags`` directory to ``/files/dags/``.
- Add a ``__main__`` block at the end of your DAG file to make it runnable. It will run a ``back_fill`` job:
.. code-block:: python
if __name__ == "__main__":
dag.clear()
dag.run()
- Add ``AIRFLOW__CORE__EXECUTOR=DebugExecutor`` to Environment variable of Run Configuration.
- Click on Add configuration
.. raw:: html
<div align="center" style="padding-bottom:10px">
<img src="images/quick_start/add_configuration.png"
alt="Add Configuration pycharm">
</div>
- Add Script Path and Environment Variable to new Python configuration
.. raw:: html
<div align="center" style="padding-bottom:10px">
<img src="images/quick_start/add_env_variable.png"
alt="Add environment variable pycharm">
</div>
- Now Debug an example dag and view the entries in tables such as ``dag_run, xcom`` etc in MySQL Workbench.
Creating a branch
#################
1. Click on the branch symbol in the status bar
.. raw:: html
<div align="center" style="padding-bottom:10px">
<img src="images/quick_start/creating_branch_1.png"
alt="Creating a new branch">
</div>
2. Give a name to a branch and checkout
.. raw:: html
<div align="center" style="padding-bottom:10px">
<img src="images/quick_start/creating_branch_2.png"
alt="Giving a name to a branch">
</div>
Follow the `Quick start <CONTRIBUTORS_QUICK_START.rst>`_ for typical development tasks.