prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  Inconsistent 'owner' field in examples
  Dear Airflow Maintainers,
  ### Environment
  - Version of Airflow (e.g. a release version, running your own fork, running off master -- provide a git log snippet): **1.7.0**
  - Screen shots of your DAG's graph and tree views:
    ![owner field](http://i.imgur.com/9U8rzil.png)
  - Operating System: (Windows Version or `$ uname -a`) **Ubuntu 14.04**
  - Python Version: `$ python --version` **2.7**
  ### Description of Issue
  - What did you expect to happen? **All of the examples have a consistent owner, probably 'airflow'**
  - What happened instead? **[Some](https://github.com/airbnb/airflow/blob/master/airflow/example_dags/example_python_operator.py) examples have `airflow`, [some](https://github.com/airbnb/airflow/blob/master/airflow/example_dags/example_passing_params_via_test_command.py) have `me`**
  ### Reproduction Steps
  1. install airflow 1.7.0 via pip
  2. start the webserver
  3. look at the web UI, probably http://localhost:8080
  
  **Inconsistent hard-coding in the examples will likely lead to confusion for new users.**
  
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `airflow/example_dags/example_trigger_controller_dag.py`
  Content:
  ```
  1 
  2 """This example illustrates the use of the TriggerDagRunOperator. There are 2
  3 entities at work in this scenario:
  4 1. The Controller DAG - the DAG that conditionally executes the trigger
  5 2. The Target DAG - DAG being triggered (in example_trigger_target_dag.py)
  6 
  7 This example illustrates the following features :
  8 1. A TriggerDagRunOperator that takes:
  9   a. A python callable that decides whether or not to trigger the Target DAG
  10   b. An optional params dict passed to the python callable to help in
  11      evaluating whether or not to trigger the Target DAG
  12   c. The id (name) of the Target DAG
  13   d. The python callable can add contextual info to the DagRun created by
  14      way of adding a Pickleable payload (e.g. dictionary of primitives). This
  15      state is then made available to the TargetDag
  16 2. A Target DAG : c.f. example_trigger_target_dag.py
  17 """
  18 
  19 from airflow import DAG
  20 from airflow.operators import TriggerDagRunOperator
  21 from datetime import datetime
  22 
  23 import pprint
  24 
  25 pp = pprint.PrettyPrinter(indent=4)
  26 
  27 
  28 def conditionally_trigger(context, dag_run_obj):
  29     """This function decides whether or not to Trigger the remote DAG"""
  30     c_p =context['params']['condition_param']
  31     print("Controller DAG : conditionally_trigger = {}".format(c_p))
  32     if context['params']['condition_param']:
  33         dag_run_obj.payload = {'message': context['params']['message']}
  34         pp.pprint(dag_run_obj.payload)
  35         return dag_run_obj
  36 
  37 
  38 # Define the DAG
  39 dag = DAG(dag_id='example_trigger_controller_dag',
  40           default_args={"owner": "me",
  41                         "start_date": datetime.now()},
  42           schedule_interval='@once')
  43 
  44 
  45 # Define the single task in this controller example DAG
  46 trigger = TriggerDagRunOperator(task_id='test_trigger_dagrun',
  47                                 trigger_dag_id="example_trigger_target_dag",
  48                                 python_callable=conditionally_trigger,
  49                                 params={'condition_param': True,
  50                                         'message': 'Hello World'},
  51                                 dag=dag)
  52
  ```
  --- END FILES ---
  
  Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.
  
  Here is an example:
  
  ```diff
  diff --git a/examples/server_async.py b/examples/server_async.py
  --- a/examples/server_async.py
  +++ b/examples/server_async.py
  @@ -313,4 +313,4 @@
   
   
   if __name__ == "__main__":
  -    asyncio.run(run_async_server("."), debug=True)
  +    asyncio.run(run_async_server(), debug=True)
  diff --git a/examples/server_sync.py b/examples/server_sync.py
  --- a/examples/server_sync.py
  +++ b/examples/server_sync.py
  @@ -313,5 +313,5 @@
   
   
   if __name__ == "__main__":
  -    server = run_sync_server(".")
  +    server = run_sync_server()
       server.shutdown()
  
  ```
  
golden_diff: diff --git a/airflow/example_dags/example_trigger_controller_dag.py b/airflow/example_dags/example_trigger_controller_dag.py
  --- a/airflow/example_dags/example_trigger_controller_dag.py
  +++ b/airflow/example_dags/example_trigger_controller_dag.py
  @@ -37,7 +37,7 @@
   
   # Define the DAG
   dag = DAG(dag_id='example_trigger_controller_dag',
  -          default_args={"owner": "me",
  +          default_args={"owner": "airflow",
                           "start_date": datetime.now()},
             schedule_interval='@once')
  
verification_info: {"golden_diff": "diff --git a/airflow/example_dags/example_trigger_controller_dag.py b/airflow/example_dags/example_trigger_controller_dag.py\n--- a/airflow/example_dags/example_trigger_controller_dag.py\n+++ b/airflow/example_dags/example_trigger_controller_dag.py\n@@ -37,7 +37,7 @@\n \n # Define the DAG\n dag = DAG(dag_id='example_trigger_controller_dag',\n-          default_args={\"owner\": \"me\",\n+          default_args={\"owner\": \"airflow\",\n                         \"start_date\": datetime.now()},\n           schedule_interval='@once')\n", "issue": "Inconsistent 'owner' field in examples\nDear Airflow Maintainers,\n### Environment\n- Version of Airflow (e.g. a release version, running your own fork, running off master -- provide a git log snippet): **1.7.0**\n- Screen shots of your DAG's graph and tree views:\n  ![owner field](http://i.imgur.com/9U8rzil.png)\n- Operating System: (Windows Version or `$ uname -a`) **Ubuntu 14.04**\n- Python Version: `$ python --version` **2.7**\n### Description of Issue\n- What did you expect to happen? **All of the examples have a consistent owner, probably 'airflow'**\n- What happened instead? **[Some](https://github.com/airbnb/airflow/blob/master/airflow/example_dags/example_python_operator.py) examples have `airflow`, [some](https://github.com/airbnb/airflow/blob/master/airflow/example_dags/example_passing_params_via_test_command.py) have `me`**\n### Reproduction Steps\n1. install airflow 1.7.0 via pip\n2. start the webserver\n3. look at the web UI, probably http://localhost:8080\n\n**Inconsistent hard-coding in the examples will likely lead to confusion for new users.**\n\n", "before_files": [{"content": "\n\"\"\"This example illustrates the use of the TriggerDagRunOperator. There are 2\nentities at work in this scenario:\n1. The Controller DAG - the DAG that conditionally executes the trigger\n2. The Target DAG - DAG being triggered (in example_trigger_target_dag.py)\n\nThis example illustrates the following features :\n1. A TriggerDagRunOperator that takes:\n  a. A python callable that decides whether or not to trigger the Target DAG\n  b. An optional params dict passed to the python callable to help in\n     evaluating whether or not to trigger the Target DAG\n  c. The id (name) of the Target DAG\n  d. The python callable can add contextual info to the DagRun created by\n     way of adding a Pickleable payload (e.g. dictionary of primitives). This\n     state is then made available to the TargetDag\n2. A Target DAG : c.f. example_trigger_target_dag.py\n\"\"\"\n\nfrom airflow import DAG\nfrom airflow.operators import TriggerDagRunOperator\nfrom datetime import datetime\n\nimport pprint\n\npp = pprint.PrettyPrinter(indent=4)\n\n\ndef conditionally_trigger(context, dag_run_obj):\n    \"\"\"This function decides whether or not to Trigger the remote DAG\"\"\"\n    c_p =context['params']['condition_param']\n    print(\"Controller DAG : conditionally_trigger = {}\".format(c_p))\n    if context['params']['condition_param']:\n        dag_run_obj.payload = {'message': context['params']['message']}\n        pp.pprint(dag_run_obj.payload)\n        return dag_run_obj\n\n\n# Define the DAG\ndag = DAG(dag_id='example_trigger_controller_dag',\n          default_args={\"owner\": \"me\",\n                        \"start_date\": datetime.now()},\n          schedule_interval='@once')\n\n\n# Define the single task in this controller example DAG\ntrigger = TriggerDagRunOperator(task_id='test_trigger_dagrun',\n                                trigger_dag_id=\"example_trigger_target_dag\",\n                                python_callable=conditionally_trigger,\n                                params={'condition_param': True,\n                                        'message': 'Hello World'},\n                                dag=dag)\n", "path": "airflow/example_dags/example_trigger_controller_dag.py"}], "after_files": [{"content": "\n\"\"\"This example illustrates the use of the TriggerDagRunOperator. There are 2\nentities at work in this scenario:\n1. The Controller DAG - the DAG that conditionally executes the trigger\n2. The Target DAG - DAG being triggered (in example_trigger_target_dag.py)\n\nThis example illustrates the following features :\n1. A TriggerDagRunOperator that takes:\n  a. A python callable that decides whether or not to trigger the Target DAG\n  b. An optional params dict passed to the python callable to help in\n     evaluating whether or not to trigger the Target DAG\n  c. The id (name) of the Target DAG\n  d. The python callable can add contextual info to the DagRun created by\n     way of adding a Pickleable payload (e.g. dictionary of primitives). This\n     state is then made available to the TargetDag\n2. A Target DAG : c.f. example_trigger_target_dag.py\n\"\"\"\n\nfrom airflow import DAG\nfrom airflow.operators import TriggerDagRunOperator\nfrom datetime import datetime\n\nimport pprint\n\npp = pprint.PrettyPrinter(indent=4)\n\n\ndef conditionally_trigger(context, dag_run_obj):\n    \"\"\"This function decides whether or not to Trigger the remote DAG\"\"\"\n    c_p =context['params']['condition_param']\n    print(\"Controller DAG : conditionally_trigger = {}\".format(c_p))\n    if context['params']['condition_param']:\n        dag_run_obj.payload = {'message': context['params']['message']}\n        pp.pprint(dag_run_obj.payload)\n        return dag_run_obj\n\n\n# Define the DAG\ndag = DAG(dag_id='example_trigger_controller_dag',\n          default_args={\"owner\": \"airflow\",\n                        \"start_date\": datetime.now()},\n          schedule_interval='@once')\n\n\n# Define the single task in this controller example DAG\ntrigger = TriggerDagRunOperator(task_id='test_trigger_dagrun',\n                                trigger_dag_id=\"example_trigger_target_dag\",\n                                python_callable=conditionally_trigger,\n                                params={'condition_param': True,\n                                        'message': 'Hello World'},\n                                dag=dag)\n", "path": "airflow/example_dags/example_trigger_controller_dag.py"}]}