Replace 'Airbnb Airflow' with 'Apache Airflow' (apache#3845)

airflow/contrib/example_dags/example_twitter_README.md

@@ -50,6 +50,6 @@ CREATE TABLE toTwitter_A(id BIGINT, id_str STRING
 ```
 When you review the code for the DAG, you will notice that these tasks are generated using for loop. These two for loops could be combined into one loop. However, in most cases, you will be running different analysis on your incoming incoming and outgoing tweets, and hence they are kept separated in this example.
 Final step is a running the broker script, brokerapi.py, which will run queries in Hive and store the summarized data to MySQL in our case. To connect to Hive, pyhs2 library is extremely useful and easy to use. To insert data into MySQL from Python, sqlalchemy is also a good one to use.
-I hope you find this tutorial useful. If you have question feel free to ask me on [Twitter](https://twitter.com/EkhtiarSyed) or via the live Airflow chatroom room in [Gitter](https://gitter.im/airbnb/airflow).<p>
+I hope you find this tutorial useful. If you have question feel free to ask me on [Twitter](https://twitter.com/EkhtiarSyed) or via the live Airflow chatroom room in [Gitter](https://gitter.im/apache/incubator-airflow).<p>
 -Ekhtiar Syed
 Last Update: 8-April-2016

airflow/models.py

@@ -3866,8 +3866,7 @@ def subdags(self):
         """
         Returns a list of the subdag objects associated to this DAG
         """
-        # Check SubDag for class but don't check class directly, see
-        # https://github.com/airbnb/airflow/issues/1168
+        # Check SubDag for class but don't check class directly
         from airflow.operators.subdag_operator import SubDagOperator
         subdag_lst = []
         for task in self.tasks:

airflow/operators/slack_operator.py

@@ -115,8 +115,8 @@ def __init__(self,
                  text='No message has been set.\n'
                       'Here is a cat video instead\n'
                       'https://www.youtube.com/watch?v=J---aiyznGQ',
-                 icon_url='https://raw.githubusercontent.com'
-                          '/airbnb/airflow/master/airflow/www/static/pin_100.png',
+                 icon_url='https://raw.githubusercontent.com/apache/'
+                          'incubator-airflow/master/airflow/www/static/pin_100.jpg',
                  attachments=None,
                  *args, **kwargs):
         self.method = 'chat.postMessage'

docs/scheduler.rst

@@ -114,7 +114,7 @@ interval series.
 
     """
     Code that goes along with the Airflow tutorial located at:
-    https://github.com/airbnb/airflow/blob/master/airflow/example_dags/tutorial.py
+    https://github.com/apache/incubator-airflow/blob/master/airflow/example_dags/tutorial.py
     """
     from airflow import DAG
     from airflow.operators.bash_operator import BashOperator

tests/jobs.py

@@ -421,8 +421,6 @@ def test_backfill_ordered_concurrent_execute(self):
     def test_backfill_pooled_tasks(self):
         """
         Test that queued tasks are executed by BackfillJob
-
-        Test for https://github.com/airbnb/airflow/pull/1225
         """
         session = settings.Session()
         pool = Pool(pool='test_backfill_pooled_task_pool', slots=1)

tests/sensors/test_http_sensor.py

@@ -140,7 +140,7 @@ class FakeSession(object):
     def __init__(self):
         self.response = requests.Response()
         self.response.status_code = 200
-        self.response._content = 'airbnb/airflow'.encode('ascii', 'ignore')
+        self.response._content = 'apache/incubator-airflow'.encode('ascii', 'ignore')
 
     def send(self, request, **kwargs):
         return self.response
@@ -178,7 +178,7 @@ def test_get_response_check(self):
             method='GET',
             endpoint='/search',
             data={"client": "ubuntu", "q": "airflow"},
-            response_check=lambda response: ("airbnb/airflow" in response.text),
+            response_check=lambda response: ("apache/incubator-airflow" in response.text),
             headers={},
             dag=self.dag)
         t.run(start_date=DEFAULT_DATE, end_date=DEFAULT_DATE, ignore_ti_state=True)
@@ -192,7 +192,7 @@ def test_sensor(self):
             request_params={"client": "ubuntu", "q": "airflow", 'date': '{{ds}}'},
             headers={},
             response_check=lambda response: (
-                "airbnb/airflow/" + DEFAULT_DATE.strftime('%Y-%m-%d')
+                "apache/incubator-airflow/" + DEFAULT_DATE.strftime('%Y-%m-%d')
                 in response.text),
             poke_interval=5,
             timeout=15,