Automatically add relevant directories to Python paths of workers (#380)

* Make ray.init set python paths of workers.

* Decouple starting cluster from copying user source code

* also add current directory to path

* Add comments about deallocation.

* Add test for new code path.

doc/using-ray-on-a-cluster.md

@@ -127,14 +127,9 @@ the tests.
     python test/array_test.py  # This tests some array libraries.
     ```
 
-6. Start the cluster with `cluster.start_ray()`. If you would like to deploy
-source code to it, you can pass in the local path to the directory that contains
-your Python code. For example, `cluster.start_ray("~/example_ray_code")`. This
-will copy your source code to each node on the cluster, placing it in a
-directory on the PYTHONPATH.
-The `cluster.start_ray` command will start the Ray scheduler, object stores, and
-workers, and before finishing it will print instructions for connecting to the
-cluster via ssh.
+6. Start the cluster with `cluster.start_ray()`. The `cluster.start_ray` command
+will start the Ray scheduler, object stores, and workers, and before finishing
+it will print instructions for connecting to the cluster via ssh.
 
 7. To connect to the cluster (either with a Python shell or with a script), ssh
 to the cluster's head node (as described by the output of the
@@ -146,7 +141,6 @@ to the cluster's head node (as described by the output of the
 
     Then run the following commands.
 
-        cd $HOME/ray
         source $HOME/ray/setup-env.sh  # Add Ray to your Python path.
 
     Then within a Python interpreter, run the following commands.
@@ -177,11 +171,14 @@ need to install a few more Python packages. This can be done, within
 
     - `cluster.install_ray()` - This pulls the Ray source code on each node,
       builds all of the third party libraries, and builds the project itself.
-    - `cluster.start_ray(user_source_directory=None, num_workers_per_node=10)` -
-      This starts a scheduler process on the head node, and it starts an object
-      store and some workers on each node.
+    - `cluster.start_ray(num_workers_per_node=10)` - This starts a scheduler
+      process on the head node, and it starts an object store and some workers
+      on each node.
     - `cluster.stop_ray()` - This shuts down the cluster (killing all of the
       processes).
+    - `cluster.copy_code_to_cluster(user_source_directory)` - This copies the
+      contents of `user_source_directory` locally to the cluster under
+      `~/ray_source_files/`.
     - `cluster.update_ray()` - This pulls the latest Ray source code and builds
       it.
     - `cluster.run_command_over_ssh_on_all_nodes_in_parallel(command)` - This