Docs and docstrings edits

airflow/hooks/presto_hook.py

@@ -48,9 +48,11 @@ class PrestoHook(BaseHook):
             session.close()    # currently only a pass in pyhive
 
     def get_cursor(self):
-        '''
+        """
+
         Returns a cursor.
-        '''
+        """
+
         return self.cursor
 
     @staticmethod
@@ -58,9 +60,11 @@ class PrestoHook(BaseHook):
         return sql.strip().rstrip(';')
 
     def get_records(self, hql, parameters=None):
-        '''
+        """
+
         Get a set of records from Presto
-        '''
+        """
+
         try:
             self.cursor.execute(self._strip_sql(hql), parameters)
             records = self.cursor.fetchall()
@@ -70,10 +74,12 @@ class PrestoHook(BaseHook):
         return records
 
     def get_first(self, hql, parameters=None):
-        '''
+        """
+
         Returns only the first row, regardless of how many rows the query
         returns.
-        '''
+        """
+
         try:
             self.cursor.execute(self._strip_sql(hql), parameters)
             record = self.cursor.fetchone()
@@ -83,9 +89,11 @@ class PrestoHook(BaseHook):
         return record
 
     def get_pandas_df(self, hql, parameters=None):
-        '''
+        """
+
         Get a pandas dataframe from a sql query.
-        '''
+        """
+
         import pandas
         cursor = self.get_cursor()
         cursor.execute(self._strip_sql(hql), parameters)
@@ -103,7 +111,9 @@ class PrestoHook(BaseHook):
         return df
 
     def run(self, hql, parameters=None):
-        '''
+        """
+
         Execute the statement against Presto. Can be used to create views.
-        '''
+        """
+
         self.cursor.execute(self._strip_sql(hql), parameters)

airflow/operators/hive_to_mysql.py

@@ -18,7 +18,7 @@ class HiveToMySqlTransfer(BaseOperator):
     :type mysql_table: str
     :param mysql_conn_id: source mysql connection
     :type mysql_conn_id: str
-    :param hive_conn_id: desctination hive connection
+    :param hive_conn_id: destination hive connection
     :type hive_conn_id: str
     :param mysql_preoperator: sql statement to run against mysql prior to
         import, typically use to truncate of delete in place of the data

docs/code.rst

@@ -30,6 +30,7 @@ There are 3 main types of operators:
         Hive2SambaOperator,
         HiveOperator,
         HivePartitionSensor,
+        HiveToMySqlTransfer,
         MySqlOperator,
         MySqlToHiveTransfer,
         PostgresOperator,
@@ -37,6 +38,7 @@ There are 3 main types of operators:
         PrestoIntervalCheckOperator,
         PrestoValueCheckOperator,
         PythonOperator,
+        S3KeySensor,
         S3ToHiveTransfer,
         SqlSensor,
         SubDagOperator,
@@ -108,7 +110,7 @@ Hooks
 -----
 .. automodule:: airflow.hooks
     :show-inheritance:
-    :members: MySqlHook, PostgresHook, PrestoHook, HiveCliHook, HiveServer2Hook, HiveMetastoreHook, S3Hook
+    :members: MySqlHook, PostgresHook, PrestoHook, HiveCliHook, HiveServer2Hook, HiveMetastoreHook, S3Hook, SqliteHook
 
 Executors
 ---------

docs/start.rst

@@ -1,10 +1,10 @@
 Quick Start
 '''''''''''
-The installation is quick and straightforward. 
+The installation is quick and straightforward.
 
 .. code-block:: bash
 
-    # airflow needs a home, ~/airflow is the default, 
+    # airflow needs a home, ~/airflow is the default,
     # but you can lay foundation somewhere else if you prefer
     # (optional)
     export AIRFLOW_HOME=~/airflow
@@ -18,28 +18,28 @@ The installation is quick and straightforward.
     # start the web server, default port is 8080
     airflow webserver -p 8080
 
-Upon running these commands, airflow will create the ``$AIRFLOW_HOME`` folder 
+Upon running these commands, airflow will create the ``$AIRFLOW_HOME`` folder
 and lay a "airflow.cfg" files with defaults that get you going fast. You can
-inspect the file either in ``$AIRFLOW_HOME/airflow.cfg``, or through the UI in 
+inspect the file either in ``$AIRFLOW_HOME/airflow.cfg``, or through the UI in
 the ``Admin->Configuration`` menu.
 
-Out of the box, airflow uses a sqlite database, which you should outgrow 
+Out of the box, airflow uses a sqlite database, which you should outgrow
 fairly quickly since no parallelization is possible using this database
-backend. It works in conjunction with the ``SequentialExecutor`` which will 
+backend. It works in conjunction with the ``SequentialExecutor`` which will
 only run task instances sequentially. While this is very limiting, it allows
-you to get up and running quickly and take a tour of the UI and the 
+you to get up and running quickly and take a tour of the UI and the
 command line utilities.
 
 Here are a few commands that will trigger a few task instances. You should
-be able to see the status of the jobs change in the ``example1`` DAG as you 
+be able to see the status of the jobs change in the ``example1`` DAG as you
 run the commands below.
 
 .. code-block:: bash
 
     # run your first task instance
-    airflow run example1 runme_0 2015-01-01
+    airflow run example_bash_operator runme_0 2015-01-01
     # run a backfill over 2 days
-    airflow backfill example1 -s 2015-01-01 -e 2015-01-02
+    airflow backfill example_bash_operator -s 2015-01-01 -e 2015-01-02
 
 From this point, you can move on to the :doc:`tutorial` section, and come back
 if/when you are ready to make your Airflow sandbox more of a serious