Change become_distributed to become_dask
It use to be the case that one should call `become_distributed` to get
a Distributed cluster to start on top of ipyparallel. However that
method is deprecated. So the correct way to do this with ipyparallel now
is to run `become_dask`.
ref:
@@ -22,7 +22,7 @@ An IPyParallel ``Client`` can launch a ``dask.distributed`` Scheduler and
Workers on those IPython engines, effectively launching a full dask.distributed
system.
-This is possible with the Client.become_distributed_ method::
+This is possible with the Client.become_dask_ method::
$ ipcluster start
@@ -31,11 +31,11 @@ This is possible with the Client.become_distributed_ method::
>>> from ipyparallel import Client
>>> c = Client() # connect to IPyParallel cluster
- >>> e = c.become_distributed() # start dask on top of IPyParallel
+ >>> e = c.become_dask() # start dask on top of IPyParallel
>>> e
<Client: scheduler="127.0.0.1:59683" processes=8 cores=8>
-.. _Client.become_distributed: https://ipyparallel.readthedocs.io/en/latest/api/ipyparallel.html#ipyparallel.Client.become_distributed
+.. _Client.become_dask: https://ipyparallel.readthedocs.io/en/latest/api/ipyparallel.html#ipyparallel.Client.become_dask
Launch IPython within Dask Workers
